blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4d805f6c5759f328c56ac3b1f0ef110c034b0360 | [
"super(EmRecoverNode, self).__init__()\nself.service = GlobalModule.SERVICE_RECOVER_NODE\nself._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]\nself.scenario_name = 'RecoverNode'",
"json_message = super(EmRecoverNode, self)._creating_json(device_message)\ndevice_json_message = json.loads(json_message... | <|body_start_0|>
super(EmRecoverNode, self).__init__()
self.service = GlobalModule.SERVICE_RECOVER_NODE
self._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]
self.scenario_name = 'RecoverNode'
<|end_body_0|>
<|body_start_1|>
json_message = super(EmRecoverNode, self).... | Scenario class for recover node | EmRecoverNode | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmRecoverNode:
"""Scenario class for recover node"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""Merges EC message(XML) devided into that in each device and device registration information received from DB convert... | stack_v2_sparse_classes_36k_train_020600 | 4,887 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Merges EC message(XML) devided into that in each device and device registration information received from DB converts them to JSDN and sets QOS information for service resetting Argument: devic... | 5 | stack_v2_sparse_classes_30k_train_004460 | Implement the Python class `EmRecoverNode` described below.
Class description:
Scenario class for recover node
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): Merges EC message(XML) devided into that in each device and device registration information rec... | Implement the Python class `EmRecoverNode` described below.
Class description:
Scenario class for recover node
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): Merges EC message(XML) devided into that in each device and device registration information rec... | e550d1b5ec9419f1fb3eb6e058ce46b57c92ee2f | <|skeleton|>
class EmRecoverNode:
"""Scenario class for recover node"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""Merges EC message(XML) devided into that in each device and device registration information received from DB convert... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmRecoverNode:
"""Scenario class for recover node"""
def __init__(self):
"""Constructor"""
super(EmRecoverNode, self).__init__()
self.service = GlobalModule.SERVICE_RECOVER_NODE
self._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]
self.scenario_name = ... | the_stack_v2_python_sparse | lib/Scenario/EmRecoverNode.py | lixiaochun/element-manager | train | 0 |
154a503a816eee2159e5a6e0b514bf4e7adba173 | [
"self._using_source = None\nself._using_destination = None\nself.device = device\nself.server_device_id = kwargs.get('server_device_id', device.central_server_id)\nif using_source == using_destination:\n raise UsingError(\"Arguments '<source>' and '<destination'> cannot be the same. Got '{0}' and '{1}'\".format(... | <|body_start_0|>
self._using_source = None
self._using_destination = None
self.device = device
self.server_device_id = kwargs.get('server_device_id', device.central_server_id)
if using_source == using_destination:
raise UsingError("Arguments '<source>' and '<destinati... | BaseUsing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseUsing:
def __init__(self, using_source, using_destination, **kwargs):
"""Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.DATABASE key for source. Source is the server so must be 'default' if running on the server and 'se... | stack_v2_sparse_classes_36k_train_020601 | 4,751 | no_license | [
{
"docstring": "Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.DATABASE key for source. Source is the server so must be 'default' if running on the server and 'server' if running on the device. ``using_destination``: settings.DATABASE key for dest... | 6 | null | Implement the Python class `BaseUsing` described below.
Class description:
Implement the BaseUsing class.
Method signatures and docstrings:
- def __init__(self, using_source, using_destination, **kwargs): Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.D... | Implement the Python class `BaseUsing` described below.
Class description:
Implement the BaseUsing class.
Method signatures and docstrings:
- def __init__(self, using_source, using_destination, **kwargs): Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.D... | 4f75336ff572babd39d431185677a65bece9e524 | <|skeleton|>
class BaseUsing:
def __init__(self, using_source, using_destination, **kwargs):
"""Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.DATABASE key for source. Source is the server so must be 'default' if running on the server and 'se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseUsing:
def __init__(self, using_source, using_destination, **kwargs):
"""Initializes and verifies arguments ``using_source`` and ``using_destination``. Args: ``using_source``: settings.DATABASE key for source. Source is the server so must be 'default' if running on the server and 'server' if runni... | the_stack_v2_python_sparse | edc/core/bhp_using/classes/base_using.py | botswana-harvard/edc | train | 0 | |
3dbefb0d2ab526ee1fc8217417bbbca449c4e33a | [
"serializer = PasswordSetSerializer(data=request.data, context={'request': request})\nserializer.is_valid(raise_exception=True)\nplain_password = serializer.validated_data['password']\nPasswordService.set_pasword(request.user, plain_password)\nreturn Response(AccountsResponses.PASSWORD_ADDED, status=status.HTTP_201... | <|body_start_0|>
serializer = PasswordSetSerializer(data=request.data, context={'request': request})
serializer.is_valid(raise_exception=True)
plain_password = serializer.validated_data['password']
PasswordService.set_pasword(request.user, plain_password)
return Response(Accounts... | Contains all accounts endpoints. | PasswordActionsViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordActionsViewSet:
"""Contains all accounts endpoints."""
def set_password(self, request):
"""Sets the user password."""
<|body_0|>
def update_password(self, request):
"""Updates the useer passwrod."""
<|body_1|>
def reset_password(self, request... | stack_v2_sparse_classes_36k_train_020602 | 3,392 | permissive | [
{
"docstring": "Sets the user password.",
"name": "set_password",
"signature": "def set_password(self, request)"
},
{
"docstring": "Updates the useer passwrod.",
"name": "update_password",
"signature": "def update_password(self, request)"
},
{
"docstring": "Request a password res... | 4 | null | Implement the Python class `PasswordActionsViewSet` described below.
Class description:
Contains all accounts endpoints.
Method signatures and docstrings:
- def set_password(self, request): Sets the user password.
- def update_password(self, request): Updates the useer passwrod.
- def reset_password(self, request): R... | Implement the Python class `PasswordActionsViewSet` described below.
Class description:
Contains all accounts endpoints.
Method signatures and docstrings:
- def set_password(self, request): Sets the user password.
- def update_password(self, request): Updates the useer passwrod.
- def reset_password(self, request): R... | 3fdc01eabdff459b31e016f9f6d1cafc19c5a292 | <|skeleton|>
class PasswordActionsViewSet:
"""Contains all accounts endpoints."""
def set_password(self, request):
"""Sets the user password."""
<|body_0|>
def update_password(self, request):
"""Updates the useer passwrod."""
<|body_1|>
def reset_password(self, request... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordActionsViewSet:
"""Contains all accounts endpoints."""
def set_password(self, request):
"""Sets the user password."""
serializer = PasswordSetSerializer(data=request.data, context={'request': request})
serializer.is_valid(raise_exception=True)
plain_password = seri... | the_stack_v2_python_sparse | apps/accounts/api/v1/views/password.py | jimialex/django-wise | train | 0 |
5ba6e3554063e263c24297241943151e3f6634c1 | [
"try:\n job = self.build_objects_async(build_table=build_table, delete_dataset_contents=delete_dataset_contents, delete_templates=delete_templates)\nexcept IngestionException as e:\n if self.raise_errors:\n raise e\n else:\n return IngestionStatus.from_exception(e)\nstatus = self.poll_for_job... | <|body_start_0|>
try:
job = self.build_objects_async(build_table=build_table, delete_dataset_contents=delete_dataset_contents, delete_templates=delete_templates)
except IngestionException as e:
if self.raise_errors:
raise e
else:
return... | [ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and delete objects in the dataset. Attributes ---------- uid: UUID Unique uuid4... | Ingestion | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ingestion:
"""[ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and delete objects in the dataset. Attribu... | stack_v2_sparse_classes_36k_train_020603 | 18,706 | permissive | [
{
"docstring": "[ALPHA] Perform a complete ingestion operation, from start to finish. Initiates an ingestion operation, polls the server to determine when the job has finished, and returns the outcome. Parameters ---------- build_table: bool Whether to build a table immediately after ingestion. Default : False ... | 4 | stack_v2_sparse_classes_30k_train_015615 | Implement the Python class `Ingestion` described below.
Class description:
[ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and... | Implement the Python class `Ingestion` described below.
Class description:
[ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and... | 43898bfc66edbe10fab00f614ee68c9ea20c4c52 | <|skeleton|>
class Ingestion:
"""[ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and delete objects in the dataset. Attribu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ingestion:
"""[ALPHA] A job that uploads new information to the platform. Datasets are the basic unit of access control. A user with read access to a dataset can view every object in that dataset. A user with write access to a dataset can create, update, and delete objects in the dataset. Attributes ---------... | the_stack_v2_python_sparse | src/citrine/resources/ingestion.py | CitrineInformatics/citrine-python | train | 30 |
80833736cc9046af69fe29a3a92578b345443be2 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn BlobEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .blob_container_evidence import BlobContainerEvidence\nfrom .file_hash import FileHash\nfrom .alert_evidence import AlertEvidence\nfrom .blob_container_evidence import B... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return BlobEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .blob_container_evidence import BlobContainerEvidence
from .file_hash import FileHas... | BlobEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlobEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BlobEvidence:
"""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: ... | stack_v2_sparse_classes_36k_train_020604 | 3,308 | 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: BlobEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(... | 3 | null | Implement the Python class `BlobEvidence` described below.
Class description:
Implement the BlobEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BlobEvidence: Creates a new instance of the appropriate class based on discriminator value Ar... | Implement the Python class `BlobEvidence` described below.
Class description:
Implement the BlobEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BlobEvidence: Creates a new instance of the appropriate class based on discriminator value Ar... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class BlobEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BlobEvidence:
"""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: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlobEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BlobEvidence:
"""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: BlobEvidence""... | the_stack_v2_python_sparse | msgraph/generated/models/security/blob_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
bc20bea485cdde9ef5c50c7ac33a8b7714b7db5e | [
"super(MaskHeadNetwork, self).__init__()\nself._net = _get_deepmac_network_by_type(network_type, num_init_channels, mask_size)\nself._use_instance_embedding = use_instance_embedding\nself.project_out = tf.keras.layers.Conv2D(filters=1, kernel_size=1, activation=None)",
"height = tf.shape(pixel_embedding)[1]\nwidt... | <|body_start_0|>
super(MaskHeadNetwork, self).__init__()
self._net = _get_deepmac_network_by_type(network_type, num_init_channels, mask_size)
self._use_instance_embedding = use_instance_embedding
self.project_out = tf.keras.layers.Conv2D(filters=1, kernel_size=1, activation=None)
<|end_b... | Mask head class for DeepMAC. | MaskHeadNetwork | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskHeadNetwork:
"""Mask head class for DeepMAC."""
def __init__(self, network_type, num_init_channels=64, use_instance_embedding=True, mask_size=None):
"""Initializes the network. Args: network_type: A string denoting the kind of network we want to use internally. num_init_channels:... | stack_v2_sparse_classes_36k_train_020605 | 35,958 | permissive | [
{
"docstring": "Initializes the network. Args: network_type: A string denoting the kind of network we want to use internally. num_init_channels: int, the number of channels in the first block. The number of channels in the following blocks depend on the network type used. use_instance_embedding: bool, if set, w... | 2 | null | Implement the Python class `MaskHeadNetwork` described below.
Class description:
Mask head class for DeepMAC.
Method signatures and docstrings:
- def __init__(self, network_type, num_init_channels=64, use_instance_embedding=True, mask_size=None): Initializes the network. Args: network_type: A string denoting the kind... | Implement the Python class `MaskHeadNetwork` described below.
Class description:
Mask head class for DeepMAC.
Method signatures and docstrings:
- def __init__(self, network_type, num_init_channels=64, use_instance_embedding=True, mask_size=None): Initializes the network. Args: network_type: A string denoting the kind... | 192ae544169c1230c21141c033800aa1bd94e9b6 | <|skeleton|>
class MaskHeadNetwork:
"""Mask head class for DeepMAC."""
def __init__(self, network_type, num_init_channels=64, use_instance_embedding=True, mask_size=None):
"""Initializes the network. Args: network_type: A string denoting the kind of network we want to use internally. num_init_channels:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaskHeadNetwork:
"""Mask head class for DeepMAC."""
def __init__(self, network_type, num_init_channels=64, use_instance_embedding=True, mask_size=None):
"""Initializes the network. Args: network_type: A string denoting the kind of network we want to use internally. num_init_channels: int, the num... | the_stack_v2_python_sparse | object_detection/meta_architectures/deepmac_meta_arch.py | DemonDamon/mask-detection-based-on-tf2odapi | train | 2 |
d67c2c88a6bfd0ed6550aa5232cb9d3d92a74f3c | [
"root = TreeNode(preorder[0])\nstk = [root]\nfor a in preorder[1:]:\n node = TreeNode(a)\n if a < stk[-1].val:\n stk[-1].left = node\n else:\n while len(stk) >= 2 and stk[-2].val < a:\n stk.pop()\n stk[-1].right = node\n stk.pop()\n stk.append(node)\nreturn root",
... | <|body_start_0|>
root = TreeNode(preorder[0])
stk = [root]
for a in preorder[1:]:
node = TreeNode(a)
if a < stk[-1].val:
stk[-1].left = node
else:
while len(stk) >= 2 and stk[-2].val < a:
stk.pop()
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def bstFromPreorder2(self, preorder: List[int]) -> TreeNode:
"""need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) maintain a stack After walking through example, left child can be determined quickly since it is ... | stack_v2_sparse_classes_36k_train_020606 | 2,292 | no_license | [
{
"docstring": "need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) maintain a stack After walking through example, left child can be determined quickly since it is pre-order. Left comes first. Stack maintain a node that is missing right child dec... | 2 | stack_v2_sparse_classes_30k_train_012772 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bstFromPreorder2(self, preorder: List[int]) -> TreeNode: need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bstFromPreorder2(self, preorder: List[int]) -> TreeNode: need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) ... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def bstFromPreorder2(self, preorder: List[int]) -> TreeNode:
"""need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) maintain a stack After walking through example, left child can be determined quickly since it is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def bstFromPreorder2(self, preorder: List[int]) -> TreeNode:
"""need to be BST scan the list to break left and right part F(n) = 2 F(n/2) + O(n), then it is O(n log n) Make it O(n) maintain a stack After walking through example, left child can be determined quickly since it is pre-order. Lef... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/1008 Construct Binary Search Tree from Preorder Traversal.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
c0be08f7221bcc06fcfd245da0c480d03c642443 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs. | OfflineUserDataJobServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfflineUserDataJobServiceServicer:
"""Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs."""
def CreateOfflineUserDataJob(self, request, context):
"""Creates an offline user data job."""
<|body_0|>
def GetOfflineUserDataJob(self... | stack_v2_sparse_classes_36k_train_020607 | 6,246 | permissive | [
{
"docstring": "Creates an offline user data job.",
"name": "CreateOfflineUserDataJob",
"signature": "def CreateOfflineUserDataJob(self, request, context)"
},
{
"docstring": "Returns the offline user data job.",
"name": "GetOfflineUserDataJob",
"signature": "def GetOfflineUserDataJob(sel... | 4 | stack_v2_sparse_classes_30k_train_009715 | Implement the Python class `OfflineUserDataJobServiceServicer` described below.
Class description:
Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs.
Method signatures and docstrings:
- def CreateOfflineUserDataJob(self, request, context): Creates an offline user data job.
... | Implement the Python class `OfflineUserDataJobServiceServicer` described below.
Class description:
Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs.
Method signatures and docstrings:
- def CreateOfflineUserDataJob(self, request, context): Creates an offline user data job.
... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class OfflineUserDataJobServiceServicer:
"""Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs."""
def CreateOfflineUserDataJob(self, request, context):
"""Creates an offline user data job."""
<|body_0|>
def GetOfflineUserDataJob(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfflineUserDataJobServiceServicer:
"""Proto file describing the OfflineUserDataJobService. Service to manage offline user data jobs."""
def CreateOfflineUserDataJob(self, request, context):
"""Creates an offline user data job."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
con... | the_stack_v2_python_sparse | google/ads/google_ads/v3/proto/services/offline_user_data_job_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
2009ec73734a942cf5072a14be018edd1550ac39 | [
"if not root:\n return 0\nleft = right = root\nd = 0\nwhile left and right:\n d += 1\n left = left.left\n right = right.right\nif not left:\n return (1 << d) - 1\nreturn 1 + self.countNodes(root.left) + self.countNodes(root.right)",
"def height(node):\n cnt = 0\n while node:\n node = n... | <|body_start_0|>
if not root:
return 0
left = right = root
d = 0
while left and right:
d += 1
left = left.left
right = right.right
if not left:
return (1 << d) - 1
return 1 + self.countNodes(root.left) + self.cou... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return 0
left = ... | stack_v2_sparse_classes_36k_train_020608 | 1,481 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "countNodes",
"signature": "def countNodes(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "countNodes",
"signature": "def countNodes(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countNodes(self, root): :type root: TreeNode :rtype: int
- def countNodes(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countNodes(self, root): :type root: TreeNode :rtype: int
- def countNodes(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def countNodes(self... | 3a7f20f79281fcaedb10696723dcb39c816ce258 | <|skeleton|>
class Solution:
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countNodes(self, root):
""":type root: TreeNode :rtype: int"""
if not root:
return 0
left = right = root
d = 0
while left and right:
d += 1
left = left.left
right = right.right
if not left:
... | the_stack_v2_python_sparse | 222_count_complete_treenodes.py | haohanz/Leetcode-Solution | train | 1 | |
c50aad0a5485fdcd5c06801aca94751854e9e8a3 | [
"n = len(nums)\nres = [0] * n\ni, j, pos = (0, n - 1, n - 1)\nwhile i <= j:\n if nums[i] ** 2 > nums[j] ** 2:\n res[pos] = nums[i] ** 2\n i += 1\n else:\n res[pos] = nums[j] ** 2\n j -= 1\n pos -= 1\nreturn res",
"tmp1 = []\ntmp = [0] * len(nums)\nj = 0\nfor i in range(len(num... | <|body_start_0|>
n = len(nums)
res = [0] * n
i, j, pos = (0, n - 1, n - 1)
while i <= j:
if nums[i] ** 2 > nums[j] ** 2:
res[pos] = nums[i] ** 2
i += 1
else:
res[pos] = nums[j] ** 2
j -= 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int] 双指针"""
<|body_0|>
def sortedSquares0(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
re... | stack_v2_sparse_classes_36k_train_020609 | 1,494 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int] 双指针",
"name": "sortedSquares",
"signature": "def sortedSquares(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "sortedSquares0",
"signature": "def sortedSquares0(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedSquares(self, nums): :type nums: List[int] :rtype: List[int] 双指针
- def sortedSquares0(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedSquares(self, nums): :type nums: List[int] :rtype: List[int] 双指针
- def sortedSquares0(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Solution:... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int] 双指针"""
<|body_0|>
def sortedSquares0(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int] 双指针"""
n = len(nums)
res = [0] * n
i, j, pos = (0, n - 1, n - 1)
while i <= j:
if nums[i] ** 2 > nums[j] ** 2:
res[pos] = nums[i] ** 2
i += 1
... | the_stack_v2_python_sparse | 977.有序数组的平方.py | yangyuxiang1996/leetcode | train | 0 | |
1db4f57ddb282be18d823a1d9e9d5849cf3075cd | [
"temp_list = []\nwith open(cls.ingested_file) as txt:\n for line in txt:\n temp_list.append(line.rstrip())\nreturn list(sorted(temp_list))",
"def wrapper_loop(*args, **kwargs):\n pln_list = os.listdir(cls.input_dir)\n cls.nasa_frame = CustomNASA(cls.nasa_data_file, *args)\n results_list = []\n ... | <|body_start_0|>
temp_list = []
with open(cls.ingested_file) as txt:
for line in txt:
temp_list.append(line.rstrip())
return list(sorted(temp_list))
<|end_body_0|>
<|body_start_1|>
def wrapper_loop(*args, **kwargs):
pln_list = os.listdir(cls.input... | We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_list_to_skip ..synopsis:: Read in a list of planets that have already been ingeste... | NewPlnDecorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewPlnDecorator:
"""We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_list_to_skip ..synopsis:: Read in a lis... | stack_v2_sparse_classes_36k_train_020610 | 30,643 | no_license | [
{
"docstring": "Read in a list of planets that have already been ingested to EOD so we can skip these.",
"name": "_get_list_to_skip",
"signature": "def _get_list_to_skip(cls)"
},
{
"docstring": "Insert the provided function into a loop that iterates through all .pln files found in input_dir.",
... | 3 | stack_v2_sparse_classes_30k_train_009123 | Implement the Python class `NewPlnDecorator` described below.
Class description:
We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_... | Implement the Python class `NewPlnDecorator` described below.
Class description:
We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_... | a2daec6ec4a85fc15e6a9a602b94eb9f847381f1 | <|skeleton|>
class NewPlnDecorator:
"""We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_list_to_skip ..synopsis:: Read in a lis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewPlnDecorator:
"""We want to define a decorator that will loop through some or all of the .pln files we've created, since just about every finalization routine will need to do this. New subclasses can be defined for different file schemes. ..module:: _get_list_to_skip ..synopsis:: Read in a list of planets ... | the_stack_v2_python_sparse | python/Reconciler.py | pforshay/exoplanets_org_work | train | 0 |
60014608146cb20e89e8802abb2693fffeec27da | [
"res = 0\nfor i in range(len(s) + 1):\n temp = self.helper(s, i)\n res = max(res, temp)\nreturn res",
"res = len(s)\nfor i in range(len(s)):\n if s[i] == '0' and i < left_end:\n res += 1\n elif s[i] == '1' and i >= left_end:\n res += 1\nreturn res"
] | <|body_start_0|>
res = 0
for i in range(len(s) + 1):
temp = self.helper(s, i)
res = max(res, temp)
return res
<|end_body_0|>
<|body_start_1|>
res = len(s)
for i in range(len(s)):
if s[i] == '0' and i < left_end:
res += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
<|body_0|>
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
for i in range(len(s) + 1):
... | stack_v2_sparse_classes_36k_train_020611 | 744 | no_license | [
{
"docstring": "Args: s: list[int] Return: int",
"name": "func",
"signature": "def func(self, s)"
},
{
"docstring": "Args: s: str left_end: int Return: int",
"name": "helper",
"signature": "def helper(self, s, left_end)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006625 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def func(self, s): Args: s: list[int] Return: int
- def helper(self, s, left_end): Args: s: str left_end: int Return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def func(self, s): Args: s: list[int] Return: int
- def helper(self, s, left_end): Args: s: str left_end: int Return: int
<|skeleton|>
class Solution:
def func(self, s):
... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
<|body_0|>
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def func(self, s):
"""Args: s: list[int] Return: int"""
res = 0
for i in range(len(s) + 1):
temp = self.helper(s, i)
res = max(res, temp)
return res
def helper(self, s, left_end):
"""Args: s: str left_end: int Return: int"""
... | the_stack_v2_python_sparse | 秋招/网易/网易云音乐/1.py | AiZhanghan/Leetcode | train | 0 | |
5183e6a0b106040bf9348fc4e1a71ae8553c5b27 | [
"super(PetscTgtVecWrapper, self).setup(parent_params_vec, params_dict, srcvec, my_params, connections, relevance=relevance, var_of_interest=var_of_interest, store_byobjs=store_byobjs, shared_vec=shared_vec, alloc_complex=alloc_complex)\nif trace:\n debug(\"'%s': creating tgt petsc_vec: (size %d) %s: vec=%s\" % (... | <|body_start_0|>
super(PetscTgtVecWrapper, self).setup(parent_params_vec, params_dict, srcvec, my_params, connections, relevance=relevance, var_of_interest=var_of_interest, store_byobjs=store_byobjs, shared_vec=shared_vec, alloc_complex=alloc_complex)
if trace:
debug("'%s': creating tgt pets... | PetscTgtVecWrapper | [
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PetscTgtVecWrapper:
def setup(self, parent_params_vec, params_dict, srcvec, my_params, connections, relevance, var_of_interest=None, store_byobjs=False, shared_vec=None, alloc_complex=False):
"""Configure this vector to store a flattened array of the variables in params_dict. Variable sh... | stack_v2_sparse_classes_36k_train_020612 | 19,322 | permissive | [
{
"docstring": "Configure this vector to store a flattened array of the variables in params_dict. Variable shape and value are retrieved from srcvec. Args ---- parent_params_vec : `VecWrapper` or None `VecWrapper` of parameters from the parent `System`. params_dict : `OrderedDict` Dictionary of parameter absolu... | 2 | null | Implement the Python class `PetscTgtVecWrapper` described below.
Class description:
Implement the PetscTgtVecWrapper class.
Method signatures and docstrings:
- def setup(self, parent_params_vec, params_dict, srcvec, my_params, connections, relevance, var_of_interest=None, store_byobjs=False, shared_vec=None, alloc_co... | Implement the Python class `PetscTgtVecWrapper` described below.
Class description:
Implement the PetscTgtVecWrapper class.
Method signatures and docstrings:
- def setup(self, parent_params_vec, params_dict, srcvec, my_params, connections, relevance, var_of_interest=None, store_byobjs=False, shared_vec=None, alloc_co... | bc7a05e04c7901f477fe553c59e478a837116d92 | <|skeleton|>
class PetscTgtVecWrapper:
def setup(self, parent_params_vec, params_dict, srcvec, my_params, connections, relevance, var_of_interest=None, store_byobjs=False, shared_vec=None, alloc_complex=False):
"""Configure this vector to store a flattened array of the variables in params_dict. Variable sh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PetscTgtVecWrapper:
def setup(self, parent_params_vec, params_dict, srcvec, my_params, connections, relevance, var_of_interest=None, store_byobjs=False, shared_vec=None, alloc_complex=False):
"""Configure this vector to store a flattened array of the variables in params_dict. Variable shape and value ... | the_stack_v2_python_sparse | bin/Python27/Lib/site-packages/openmdao/core/petsc_impl.py | metamorph-inc/meta-core | train | 25 | |
3b836ce73039cac230755071f731eec10196b938 | [
"if len(nums1) > len(nums2):\n return self.intersect_1(nums2, nums1)\nm = collections.Counter()\nfor num in nums1:\n m[num] += 1\nintersection = list()\nfor num in nums2:\n if m.get(num, 0) > 0:\n intersection.append(num)\n m[num] -= 1\n if m[num] == 0:\n m.pop(num)\nreturn ... | <|body_start_0|>
if len(nums1) > len(nums2):
return self.intersect_1(nums2, nums1)
m = collections.Counter()
for num in nums1:
m[num] += 1
intersection = list()
for num in nums2:
if m.get(num, 0) > 0:
intersection.append(num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersect_1(self, nums1: List[int], nums2: List[int]) -> List[int]:
"""方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂度：O(min(m,n))，其中 m 和 n 分别是两个数组的长度。对较短的数组进行哈希表的操作， 哈希表的大小不会超过较短的数组的长度。为返回值创建一个数组 intersection，其长度为... | stack_v2_sparse_classes_36k_train_020613 | 3,064 | no_license | [
{
"docstring": "方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂度：O(min(m,n))，其中 m 和 n 分别是两个数组的长度。对较短的数组进行哈希表的操作， 哈希表的大小不会超过较短的数组的长度。为返回值创建一个数组 intersection，其长度为较短的数组的长度。 :param nums1: :param nums2: :return:",
"name": "intersect_1",
"signature": ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect_1(self, nums1: List[int], nums2: List[int]) -> List[int]: 方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect_1(self, nums1: List[int], nums2: List[int]) -> List[int]: 方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def intersect_1(self, nums1: List[int], nums2: List[int]) -> List[int]:
"""方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂度：O(min(m,n))，其中 m 和 n 分别是两个数组的长度。对较短的数组进行哈希表的操作， 哈希表的大小不会超过较短的数组的长度。为返回值创建一个数组 intersection，其长度为... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intersect_1(self, nums1: List[int], nums2: List[int]) -> List[int]:
"""方法一：哈希表 时间复杂度：O(m+n)，其中 m 和 n 分别是两个数组的长度。需要遍历两个数组并对哈希表进行操作， 哈希表操作的时间复杂度是 O(1)，因此总时间复杂度与两个数组的长度和呈线性关系。 空间复杂度：O(min(m,n))，其中 m 和 n 分别是两个数组的长度。对较短的数组进行哈希表的操作， 哈希表的大小不会超过较短的数组的长度。为返回值创建一个数组 intersection，其长度为较短的数组的长度。 :par... | the_stack_v2_python_sparse | 软件开发岗刷题（华为笔试准备）/哈希表/intersect.py | MaoningGuan/LeetCode | train | 3 | |
da814904d40b66b3e6bd2b8a43af2e420a90ad77 | [
"super(DecoderLayer, self).__init__()\nself.masked_multi_head_attention = MultiHeadAttention(d_model, number_of_heads)\nself.multi_head_attention = MultiHeadAttention(d_model, number_of_heads)\nself.feed_forward_network = point_wise_feed_forward_network(d_model, dff)\nself.normalization_layer1 = tf.keras.layers.Lay... | <|body_start_0|>
super(DecoderLayer, self).__init__()
self.masked_multi_head_attention = MultiHeadAttention(d_model, number_of_heads)
self.multi_head_attention = MultiHeadAttention(d_model, number_of_heads)
self.feed_forward_network = point_wise_feed_forward_network(d_model, dff)
... | Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer | DecoderLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderLayer:
"""Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer"""
def __init__(self, d_model, number_of_heads, dff, rate=0.1):
... | stack_v2_sparse_classes_36k_train_020614 | 11,425 | no_license | [
{
"docstring": "Constructor for decoder layer :param d_model: dimension of the word embedding vector :param number_of_heads: number of heads to work in parallel :param dff: inner-layer dimensionality :param rate: dropout rate",
"name": "__init__",
"signature": "def __init__(self, d_model, number_of_head... | 2 | stack_v2_sparse_classes_30k_train_017721 | Implement the Python class `DecoderLayer` described below.
Class description:
Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer
Method signatures and docstrings... | Implement the Python class `DecoderLayer` described below.
Class description:
Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer
Method signatures and docstrings... | f164c21ed852dfd10a4701f4050d72dc87bd302a | <|skeleton|>
class DecoderLayer:
"""Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer"""
def __init__(self, d_model, number_of_heads, dff, rate=0.1):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderLayer:
"""Decoder layer consists of masked multi-head attention followed by normalization layer, multi-head attention followed by normalization layer and point wise feed forward network followed by normalization layer"""
def __init__(self, d_model, number_of_heads, dff, rate=0.1):
"""Const... | the_stack_v2_python_sparse | backend/code/transformer_model.py | sovaso/NewsHeadlineGenerator | train | 3 |
352133aa362159d87233d28cc876028e2850040b | [
"dp = [False] * len(nums)\ndp[0] = True\nfor i in range(1, len(nums)):\n dp[i] = any([j + nums[j] >= i if dp[j] else False for j in range(i)])\nreturn dp[-1]",
"dp = [0] * len(nums)\nfor i in range(1, len(nums)):\n dp[i] = max(dp[i - 1], nums[i - 1]) - 1\n if dp[i] < 0:\n return False\nreturn True... | <|body_start_0|>
dp = [False] * len(nums)
dp[0] = True
for i in range(1, len(nums)):
dp[i] = any([j + nums[j] >= i if dp[j] else False for j in range(i)])
return dp[-1]
<|end_body_0|>
<|body_start_1|>
dp = [0] * len(nums)
for i in range(1, len(nums)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canJump(self, nums):
"""dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool"""
<|body_0|>
def canJump(self, nums):
"""dp[i] 表示达到 i 位置时剩余的跳力 当前位置的剩余跳力（dp 值）和当前位置新的跳力中较大的决定... | stack_v2_sparse_classes_36k_train_020615 | 2,700 | no_license | [
{
"docstring": "dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool",
"name": "canJump",
"signature": "def canJump(self, nums)"
},
{
"docstring": "dp[i] 表示达到 i 位置时剩余的跳力 当前位置的剩余跳力（dp 值）和当前位置新的跳力中较大的决定了当前能到的最远距离 下一个... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canJump(self, nums): dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool
- def canJump(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canJump(self, nums): dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool
- def canJump(self... | 860590239da0618c52967a55eda8d6bbe00bfa96 | <|skeleton|>
class Solution:
def canJump(self, nums):
"""dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool"""
<|body_0|>
def canJump(self, nums):
"""dp[i] 表示达到 i 位置时剩余的跳力 当前位置的剩余跳力（dp 值）和当前位置新的跳力中较大的决定... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canJump(self, nums):
"""dp[i] 表示是否能从 [0,i) 跳到 i 能跳到 i 的条件是存在一个从 [0,i) 的某处+当时的最大跳力比 i 大 dp[i] = any(j+nums[j]>=i) 0 <= j < i :type nums: List[int] :rtype: bool"""
dp = [False] * len(nums)
dp[0] = True
for i in range(1, len(nums)):
dp[i] = any([j + nums[... | the_stack_v2_python_sparse | LeetCode/p0055/II/jump-game.py | Ynjxsjmh/PracticeMakesPerfect | train | 0 | |
44fd550eb28b4d9130dbf0576184c3d845b68210 | [
"self.words = ['Titan', 'Jupiter', 'Titan', 'Titan', 'Huygens', 'Jupiter']\nself.r = ranking.Ranking('not_existing.txt')\nfor w in self.words:\n self.r.add(w)\nself.r.save()",
"try:\n os.remove('not_existing.txt')\nexcept:\n pass",
"self.failUnless(self.r.getRank('Titan') == 1)\nself.failUnless(self.r.... | <|body_start_0|>
self.words = ['Titan', 'Jupiter', 'Titan', 'Titan', 'Huygens', 'Jupiter']
self.r = ranking.Ranking('not_existing.txt')
for w in self.words:
self.r.add(w)
self.r.save()
<|end_body_0|>
<|body_start_1|>
try:
os.remove('not_existing.txt')
... | Funktionstests | TestRanking1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRanking1:
"""Funktionstests"""
def setUp(self):
"""Erzeuge Testdaten und Ranking-Objekt"""
<|body_0|>
def tearDown(self):
"""Lösche Testdatei"""
<|body_1|>
def testRank(self):
"""Prüfe, ob Rang richtig berechnet wird"""
<|body_2|>... | stack_v2_sparse_classes_36k_train_020616 | 2,660 | no_license | [
{
"docstring": "Erzeuge Testdaten und Ranking-Objekt",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Lösche Testdatei",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "Prüfe, ob Rang richtig berechnet wird",
"name": "testRank",
... | 5 | null | Implement the Python class `TestRanking1` described below.
Class description:
Funktionstests
Method signatures and docstrings:
- def setUp(self): Erzeuge Testdaten und Ranking-Objekt
- def tearDown(self): Lösche Testdatei
- def testRank(self): Prüfe, ob Rang richtig berechnet wird
- def testSave(self): Pruefe, ob all... | Implement the Python class `TestRanking1` described below.
Class description:
Funktionstests
Method signatures and docstrings:
- def setUp(self): Erzeuge Testdaten und Ranking-Objekt
- def tearDown(self): Lösche Testdatei
- def testRank(self): Prüfe, ob Rang richtig berechnet wird
- def testSave(self): Pruefe, ob all... | 6acc4cc3ca1a7ed8143f5533a956d11fc3a76dff | <|skeleton|>
class TestRanking1:
"""Funktionstests"""
def setUp(self):
"""Erzeuge Testdaten und Ranking-Objekt"""
<|body_0|>
def tearDown(self):
"""Lösche Testdatei"""
<|body_1|>
def testRank(self):
"""Prüfe, ob Rang richtig berechnet wird"""
<|body_2|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestRanking1:
"""Funktionstests"""
def setUp(self):
"""Erzeuge Testdaten und Ranking-Objekt"""
self.words = ['Titan', 'Jupiter', 'Titan', 'Titan', 'Huygens', 'Jupiter']
self.r = ranking.Ranking('not_existing.txt')
for w in self.words:
self.r.add(w)
self... | the_stack_v2_python_sparse | book/kap_25/wort_des_jahres/rankingtest_fortgeschritten.py | Nachtalb/python_book_exercises | train | 0 |
683aa450de08efbc5807f226a4e7b562771af962 | [
"super(LazyProperty, self).__init__()\nself.dependency = depends_on\nself.handlers = WeakKeyDictionary()\nif trait is not None:\n self.default_value_type = trait.default_value_type",
"cache_name = '_%s_lazy_property_cache' % name\ndct = obj.__dict__\nif cache_name not in dct:\n method_name = '_get_%s' % nam... | <|body_start_0|>
super(LazyProperty, self).__init__()
self.dependency = depends_on
self.handlers = WeakKeyDictionary()
if trait is not None:
self.default_value_type = trait.default_value_type
<|end_body_0|>
<|body_start_1|>
cache_name = '_%s_lazy_property_cache' % na... | A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated during component instantiation. | LazyProperty | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LazyProperty:
"""A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated during component instantiation."""
... | stack_v2_sparse_classes_36k_train_020617 | 20,546 | permissive | [
{
"docstring": "Initialize a LazyProperty. Parameters ---------- trait : TraitType, optional An optional trait type for the values returned by the property. List is required if using extending trait name syntax for e.g. list listeners. depends_on : string, optional The traits notification string for the depende... | 3 | null | Implement the Python class `LazyProperty` described below.
Class description:
A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated... | Implement the Python class `LazyProperty` described below.
Class description:
A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated... | 96828b254ac9fdfa2e5b6b31eff93a4933cbc0aa | <|skeleton|>
class LazyProperty:
"""A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated during component instantiation."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LazyProperty:
"""A trait which behaves like a read-only cached property, but which lazily defers binding the dependency notifiers until the first time the value is retrieved. It is used to avoid situations where a property dependency in prematurely evaluated during component instantiation."""
def __init_... | the_stack_v2_python_sparse | enaml/core/trait_types.py | agrawalprash/enaml | train | 0 |
01429cf2f85a8c1b0b70cc09bc86cecabd6fb5c8 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties. | RPCApiServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
<|body_0|>
def Decide(self, request, context):
... | stack_v2_sparse_classes_36k_train_020618 | 12,917 | no_license | [
{
"docstring": "Get a list of all logs published/subscribed by this node",
"name": "Logs",
"signature": "def Logs(self, request, context)"
},
{
"docstring": "Decide on an output for key based on the configured decision method",
"name": "Decide",
"signature": "def Decide(self, request, co... | 3 | stack_v2_sparse_classes_30k_train_005427 | Implement the Python class `RPCApiServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties.
Method signatures and docstrings:
- def Logs(self, request, context): Get a list of all logs published/subscribed by this node
- def Decid... | Implement the Python class `RPCApiServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties.
Method signatures and docstrings:
- def Logs(self, request, context): Get a list of all logs published/subscribed by this node
- def Decid... | 9bf6f32ab9b28c49fdc12c6e7a847a2b6dc1aa00 | <|skeleton|>
class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
<|body_0|>
def Decide(self, request, context):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RPCApiServicer:
"""RPCApi are "private" rpc methods for an instance. This should only be available to trusted parties."""
def Logs(self, request, context):
"""Get a list of all logs published/subscribed by this node"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_de... | the_stack_v2_python_sparse | packages/trustix-python/trustix_python/rpc/rpc_pb2_grpc.py | daotlresearch/trustix | train | 0 |
7e967f9dee523d2cfea0f0eb6ec019c763ca8106 | [
"self.current_frame_index = None\nself.packets_data = []\nself.remaining_packets = None",
"full_frame = b''\nis_first_packet = self.current_frame_index is None\nif is_first_packet or p.frame_index > self.current_frame_index:\n if not is_first_packet and self.remaining_packets != 0:\n full_frame = b''\n ... | <|body_start_0|>
self.current_frame_index = None
self.packets_data = []
self.remaining_packets = None
<|end_body_0|>
<|body_start_1|>
full_frame = b''
is_first_packet = self.current_frame_index is None
if is_first_packet or p.frame_index > self.current_frame_index:
... | Definition of the class UdpPacketsHandler. | UdpPacketsHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UdpPacketsHandler:
"""Definition of the class UdpPacketsHandler."""
def __init__(self):
"""Constructor."""
<|body_0|>
def process_packet(self, p: UdpPacket) -> Union[bytes, None]:
"""Processes a given packet. If all the packets were collected, returns the full fr... | stack_v2_sparse_classes_36k_train_020619 | 3,250 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Processes a given packet. If all the packets were collected, returns the full frame. Otherwise, returns None.",
"name": "process_packet",
"signature": "def process_packet(self, p: UdpP... | 3 | stack_v2_sparse_classes_30k_train_003281 | Implement the Python class `UdpPacketsHandler` described below.
Class description:
Definition of the class UdpPacketsHandler.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def process_packet(self, p: UdpPacket) -> Union[bytes, None]: Processes a given packet. If all the packets were collected... | Implement the Python class `UdpPacketsHandler` described below.
Class description:
Definition of the class UdpPacketsHandler.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def process_packet(self, p: UdpPacket) -> Union[bytes, None]: Processes a given packet. If all the packets were collected... | d88933620286e655c39776e0a4e99de9d9067172 | <|skeleton|>
class UdpPacketsHandler:
"""Definition of the class UdpPacketsHandler."""
def __init__(self):
"""Constructor."""
<|body_0|>
def process_packet(self, p: UdpPacket) -> Union[bytes, None]:
"""Processes a given packet. If all the packets were collected, returns the full fr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UdpPacketsHandler:
"""Definition of the class UdpPacketsHandler."""
def __init__(self):
"""Constructor."""
self.current_frame_index = None
self.packets_data = []
self.remaining_packets = None
def process_packet(self, p: UdpPacket) -> Union[bytes, None]:
"""Pro... | the_stack_v2_python_sparse | client/video/udp_packets_handler.py | HadarShahar/zoom | train | 0 |
ee76899e0695cdb1d9025f72a320cd7b53625418 | [
"self.queue_config = queue_config\nself.storage_obj = storage_obj\nif 'type' not in self.queue_config.keys():\n raise ValueError(f'Queue type not found. Please update creds.json with one of the following supported queue types.\\n{SUPPORTED_QUEUES}')\nself.queue_type = queue_config['type']\nassert self.queue_type... | <|body_start_0|>
self.queue_config = queue_config
self.storage_obj = storage_obj
if 'type' not in self.queue_config.keys():
raise ValueError(f'Queue type not found. Please update creds.json with one of the following supported queue types.\n{SUPPORTED_QUEUES}')
self.queue_type... | This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (locally run queuing service) | QueueLifecycleManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueueLifecycleManager:
"""This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (locally run queuing service)"""
def ... | stack_v2_sparse_classes_36k_train_020620 | 3,444 | no_license | [
{
"docstring": "The constructor will take in the queue and storage config files and validate them. :param queue_config: :param storage_obj:",
"name": "__init__",
"signature": "def __init__(self, queue_config, storage_obj=None)"
},
{
"docstring": "This function builds the queue object according t... | 3 | stack_v2_sparse_classes_30k_val_000192 | Implement the Python class `QueueLifecycleManager` described below.
Class description:
This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (lo... | Implement the Python class `QueueLifecycleManager` described below.
Class description:
This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (lo... | f21a89a011256047814e12ffc370c41a3346a3d7 | <|skeleton|>
class QueueLifecycleManager:
"""This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (locally run queuing service)"""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueueLifecycleManager:
"""This class will be sent a queue config dictionary and determine which queue to use by the information contained in that config. Acceptable queue types: - sqs (AWS Simple Queuing Service) - rmq (Rabbit MQ Queuing Service) - local (locally run queuing service)"""
def __init__(self... | the_stack_v2_python_sparse | queuingservices/managers/queue_lifecycle_manager.py | aj132608/CloudRunner | train | 0 |
238cef92c07aa1d5c8b7d6049c3d117346c8c5b5 | [
"super(Client, self).__init__()\nself.Unexport(['Alias'])\ntype(self).Chaddr.Set(self, chaddr)\nself.IPv4AddressList = {'1': ClientIPv4Address(ip=ipaddr, expiry=expiry)}\nself.next_ipv4 = 2\nself.OptionList = {}\nif clientid:\n self.OptionList['1'] = ClientOption(tag=CL, value=clientid)\nif hostname:\n self.O... | <|body_start_0|>
super(Client, self).__init__()
self.Unexport(['Alias'])
type(self).Chaddr.Set(self, chaddr)
self.IPv4AddressList = {'1': ClientIPv4Address(ip=ipaddr, expiry=expiry)}
self.next_ipv4 = 2
self.OptionList = {}
if clientid:
self.OptionList[... | tr-181 Device.DHCPv4.Server.{i}.Client.{i}. | Client | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}."""
def __init__(self, chaddr, ipaddr, expiry=0, clientid=None, hostname=None, userclassid=None, vendorclassid=None):
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: chaddr: a MAC address. ipaddr: a dotted-quad IP address. ex... | stack_v2_sparse_classes_36k_train_020621 | 4,090 | permissive | [
{
"docstring": "tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: chaddr: a MAC address. ipaddr: a dotted-quad IP address. expiry: an integer number of seconds since the epoch UTC when the lease will expire, OR a string timestamp, OR a datetime object. clientid: DHCP ClientID from the client, if any. hostname: ... | 2 | null | Implement the Python class `Client` described below.
Class description:
tr-181 Device.DHCPv4.Server.{i}.Client.{i}.
Method signatures and docstrings:
- def __init__(self, chaddr, ipaddr, expiry=0, clientid=None, hostname=None, userclassid=None, vendorclassid=None): tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: ch... | Implement the Python class `Client` described below.
Class description:
tr-181 Device.DHCPv4.Server.{i}.Client.{i}.
Method signatures and docstrings:
- def __init__(self, chaddr, ipaddr, expiry=0, clientid=None, hostname=None, userclassid=None, vendorclassid=None): tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: ch... | b01e4444f3c7f12b1af7837203b37060fd443bb7 | <|skeleton|>
class Client:
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}."""
def __init__(self, chaddr, ipaddr, expiry=0, clientid=None, hostname=None, userclassid=None, vendorclassid=None):
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: chaddr: a MAC address. ipaddr: a dotted-quad IP address. ex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Client:
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}."""
def __init__(self, chaddr, ipaddr, expiry=0, clientid=None, hostname=None, userclassid=None, vendorclassid=None):
"""tr-181 Device.DHCPv4.Server.{i}.Client.{i}. Args: chaddr: a MAC address. ipaddr: a dotted-quad IP address. expiry: an inte... | the_stack_v2_python_sparse | dm/dhcp.py | pombredanne/catawampus-1 | train | 0 |
4d447a9fb6e1ece148aefc5449b2b8de8bb3dee8 | [
"cls._check_subclass()\ncls._check_col_names(train_data, is_train=True)\ncls.user_unique_vals = np.sort(train_data['user'].unique())\ncls.item_unique_vals = np.sort(train_data['item'].unique())\nif shuffle:\n train_data = cls.shuffle_data(train_data, seed)\ntrain_transformed, user_indices, item_indices = _build_... | <|body_start_0|>
cls._check_subclass()
cls._check_col_names(train_data, is_train=True)
cls.user_unique_vals = np.sort(train_data['user'].unique())
cls.item_unique_vals = np.sort(train_data['item'].unique())
if shuffle:
train_data = cls.shuffle_data(train_data, seed)
... | Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_data) >>> test_data = DatasetPure.build_testset(test_data) | DatasetPure | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetPure:
"""Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_data) >>> test_data = DatasetPure.build_t... | stack_v2_sparse_classes_36k_train_020622 | 27,116 | permissive | [
{
"docstring": "Build transformed train data and data_info from original data. .. versionchanged:: 1.0.0 Data construction in :ref:`Model Retrain <retrain_data>` has been moved to :meth:`merge_trainset` Parameters ---------- train_data : pandas.DataFrame Data must contain at least three columns, i.e. ``user``, ... | 2 | null | Implement the Python class `DatasetPure` described below.
Class description:
Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_da... | Implement the Python class `DatasetPure` described below.
Class description:
Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_da... | 8d5fbe9c177f5b91c2b6f19a155a83320dd0e20c | <|skeleton|>
class DatasetPure:
"""Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_data) >>> test_data = DatasetPure.build_t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatasetPure:
"""Dataset class used for building pure collaborative filtering data. Examples -------- >>> from libreco.data import DatasetPure >>> train_data, data_info = DatasetPure.build_trainset(train_data) >>> eval_data = DatasetPure.build_evalset(eval_data) >>> test_data = DatasetPure.build_testset(test_d... | the_stack_v2_python_sparse | libreco/data/dataset.py | massquantity/LibRecommender | train | 251 |
5a1f619715fe8aa4dbed410b83d63e008bb246ad | [
"for i in range(n):\n nums1[m + i] = nums2[i]\nnums1.sort()",
"if n == 0:\n return None\nfor i in range(n):\n nums1[m + i] = nums2[i]\n for j in range(m + i, 0, -1):\n if nums1[j] < nums1[j - 1]:\n nums1[j], nums1[j - 1] = (nums1[j - 1], nums1[j])\n else:\n break"
] | <|body_start_0|>
for i in range(n):
nums1[m + i] = nums2[i]
nums1.sort()
<|end_body_0|>
<|body_start_1|>
if n == 0:
return None
for i in range(n):
nums1[m + i] = nums2[i]
for j in range(m + i, 0, -1):
if nums1[j] < nums1[j ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge2(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""双指针（插入排序思想）。 首先选择 nums2 第 1... | stack_v2_sparse_classes_36k_train_020623 | 5,205 | no_license | [
{
"docstring": "Do not return anything, modify nums1 in-place instead.",
"name": "merge",
"signature": "def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None"
},
{
"docstring": "双指针（插入排序思想）。 首先选择 nums2 第 1 个元素，将其插入到 nums1 中正确的位置； 然后再从 nums2 选择第 2 位元素，沿着 nums1 中上次插入的位置，向右寻找合... | 2 | stack_v2_sparse_classes_30k_train_017395 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None: Do not return anything, modify nums1 in-place instead.
- def merge2(self, nums1: List[int], m: int, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None: Do not return anything, modify nums1 in-place instead.
- def merge2(self, nums1: List[int], m: int, n... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
<|body_0|>
def merge2(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""双指针（插入排序思想）。 首先选择 nums2 第 1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
"""Do not return anything, modify nums1 in-place instead."""
for i in range(n):
nums1[m + i] = nums2[i]
nums1.sort()
def merge2(self, nums1: List[int], m: int, nums2: List[int], n: i... | the_stack_v2_python_sparse | 0088_merge-sorted-array.py | Nigirimeshi/leetcode | train | 0 | |
d3a6ce2f3d97d3e76d4d5f12bdc327f5fcac3f6f | [
"metrics = set(metrics)\npersist_metrics = set()\nwith self.get_cursor() as cursor:\n cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))\n for id, metric in cursor.fetchall():\n persist_metrics.add(metric)\n creates = [(stage, m) for m in metrics.difference(persist_metrics)]\n cursor.executeman... | <|body_start_0|>
metrics = set(metrics)
persist_metrics = set()
with self.get_cursor() as cursor:
cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))
for id, metric in cursor.fetchall():
persist_metrics.add(metric)
creates = [(stage, m) for m ... | MetricHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
<|body_0|>
def add_data(self, values):
"""Add a specified value for a specified metric id."""
<|body_1|>
def get_data(self, metric_id, start, end):
"""Get the metric times... | stack_v2_sparse_classes_36k_train_020624 | 6,662 | no_license | [
{
"docstring": "Get/Create metrics",
"name": "declare",
"signature": "def declare(self, stage, metrics)"
},
{
"docstring": "Add a specified value for a specified metric id.",
"name": "add_data",
"signature": "def add_data(self, values)"
},
{
"docstring": "Get the metric timeserie... | 5 | stack_v2_sparse_classes_30k_train_007550 | Implement the Python class `MetricHandler` described below.
Class description:
Implement the MetricHandler class.
Method signatures and docstrings:
- def declare(self, stage, metrics): Get/Create metrics
- def add_data(self, values): Add a specified value for a specified metric id.
- def get_data(self, metric_id, sta... | Implement the Python class `MetricHandler` described below.
Class description:
Implement the MetricHandler class.
Method signatures and docstrings:
- def declare(self, stage, metrics): Get/Create metrics
- def add_data(self, values): Add a specified value for a specified metric id.
- def get_data(self, metric_id, sta... | 02e482e00b8d6c09bdbd6cb1f99ce8f2617e47cd | <|skeleton|>
class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
<|body_0|>
def add_data(self, values):
"""Add a specified value for a specified metric id."""
<|body_1|>
def get_data(self, metric_id, start, end):
"""Get the metric times... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetricHandler:
def declare(self, stage, metrics):
"""Get/Create metrics"""
metrics = set(metrics)
persist_metrics = set()
with self.get_cursor() as cursor:
cursor.execute(self.GET_STAGE_METRICS_SQL, (stage,))
for id, metric in cursor.fetchall():
... | the_stack_v2_python_sparse | unshadow/server/metric.py | iakinsey/unshadow | train | 1 | |
ac3406a3f310aa7b6b23bc100254bf586e6f2fdd | [
"self.__logger = State().getLogger('Preprocessing_Component_Logger')\nself.__logger.info('Starting __init__()', 'AdaptiveThresholdBinarizationPreprocessor:__init__')\nself.__maxValue = maxValue\nself.__adaptiveMethode = adaptiveMethode\nself.__thresholdType = thresholdType\nself.__blockSize = blockSize\nself.__C = ... | <|body_start_0|>
self.__logger = State().getLogger('Preprocessing_Component_Logger')
self.__logger.info('Starting __init__()', 'AdaptiveThresholdBinarizationPreprocessor:__init__')
self.__maxValue = maxValue
self.__adaptiveMethode = adaptiveMethode
self.__thresholdType = threshol... | AdaptiveThresholdBinarizationPreprocessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveThresholdBinarizationPreprocessor:
def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
<|body_0|>
def preProcess(self, mat):
"""Führt die adaptive thre... | stack_v2_sparse_classes_36k_train_020625 | 2,935 | no_license | [
{
"docstring": "To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!",
"name": "__init__",
"signature": "def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False)"
},
{
"docstring": "Führt die adaptive threshold binarization auf eine Bildmatrix aus. Para... | 2 | stack_v2_sparse_classes_30k_train_017676 | Implement the Python class `AdaptiveThresholdBinarizationPreprocessor` described below.
Class description:
Implement the AdaptiveThresholdBinarizationPreprocessor class.
Method signatures and docstrings:
- def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False): To-Do: Bit... | Implement the Python class `AdaptiveThresholdBinarizationPreprocessor` described below.
Class description:
Implement the AdaptiveThresholdBinarizationPreprocessor class.
Method signatures and docstrings:
- def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False): To-Do: Bit... | 3daaa72b193ebfb55894b47b6a752cdc2192bb6b | <|skeleton|>
class AdaptiveThresholdBinarizationPreprocessor:
def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
<|body_0|>
def preProcess(self, mat):
"""Führt die adaptive thre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaptiveThresholdBinarizationPreprocessor:
def __init__(self, maxValue, adaptiveMethode, thresholdType, blockSize, C, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
self.__logger = State().getLogger('Preprocessing_Component_Logger')
self.__logger.i... | the_stack_v2_python_sparse | SheetMusicScanner/Preprocessing_Component/PreprocessingUnit/AdaptiveThresholdBinarizationPreProcessor.py | jadeskon/score-scan | train | 0 | |
bc79fa3ea8a668440f2fbd14fcb2021915be62de | [
"self.passages_extract = no_passages_to_extract\nself.outline_file = outline_file\nself.paragraph_file = paragraph_file\nself.pages = self.gather_pages()\nself.stop_words = stopwords.words('english')",
"with open(self.outline_file, 'rb') as f:\n pages = [p for p in itertools.islice(iter_annotations(f), 0, 1000... | <|body_start_0|>
self.passages_extract = no_passages_to_extract
self.outline_file = outline_file
self.paragraph_file = paragraph_file
self.pages = self.gather_pages()
self.stop_words = stopwords.words('english')
<|end_body_0|>
<|body_start_1|>
with open(self.outline_file... | PartialRanking | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartialRanking:
def __init__(self, outline_file, paragraph_file, no_passages_to_extract):
"""Constructor :param outline_file: path of the outline file :param paragraph_file: path of the paragraph file"""
<|body_0|>
def gather_pages(self):
"""Gets the pages from cbor ... | stack_v2_sparse_classes_36k_train_020626 | 3,433 | no_license | [
{
"docstring": "Constructor :param outline_file: path of the outline file :param paragraph_file: path of the paragraph file",
"name": "__init__",
"signature": "def __init__(self, outline_file, paragraph_file, no_passages_to_extract)"
},
{
"docstring": "Gets the pages from cbor :return: list of p... | 5 | stack_v2_sparse_classes_30k_train_011883 | Implement the Python class `PartialRanking` described below.
Class description:
Implement the PartialRanking class.
Method signatures and docstrings:
- def __init__(self, outline_file, paragraph_file, no_passages_to_extract): Constructor :param outline_file: path of the outline file :param paragraph_file: path of the... | Implement the Python class `PartialRanking` described below.
Class description:
Implement the PartialRanking class.
Method signatures and docstrings:
- def __init__(self, outline_file, paragraph_file, no_passages_to_extract): Constructor :param outline_file: path of the outline file :param paragraph_file: path of the... | 009707f9f0df81bc4b2163a474aae4244fbd3f77 | <|skeleton|>
class PartialRanking:
def __init__(self, outline_file, paragraph_file, no_passages_to_extract):
"""Constructor :param outline_file: path of the outline file :param paragraph_file: path of the paragraph file"""
<|body_0|>
def gather_pages(self):
"""Gets the pages from cbor ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PartialRanking:
def __init__(self, outline_file, paragraph_file, no_passages_to_extract):
"""Constructor :param outline_file: path of the outline file :param paragraph_file: path of the paragraph file"""
self.passages_extract = no_passages_to_extract
self.outline_file = outline_file
... | the_stack_v2_python_sparse | tc_modified_ranking_7million.py | shilpadhagat/TREC-complex-answer-retrieval | train | 4 | |
e53fa32c6f7514d55befe19faf7765d0c2746ca9 | [
"first, last = (0, len(nums) - 1)\nwhile first < last:\n if nums[first] % 2 == 1:\n first += 1\n continue\n if nums[last] % 2 == 0:\n last -= 1\n continue\n nums[first], nums[last] = (nums[last], nums[first])\nreturn nums",
"low = fast = 0\nwhile fast < len(nums):\n if nums... | <|body_start_0|>
first, last = (0, len(nums) - 1)
while first < last:
if nums[first] % 2 == 1:
first += 1
continue
if nums[last] % 2 == 0:
last -= 1
continue
nums[first], nums[last] = (nums[last], nums[fi... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n)... | stack_v2_sparse_classes_36k_train_020627 | 2,049 | no_license | [
{
"docstring": "前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)",
"name": "exchange",
"signature": "def exchange(self, nums: List[int]) -> List[int]"
},
{
"docstring": "快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n) 空间复杂度：O(1)",
"name": "exchange_2",
... | 2 | stack_v2_sparse_classes_30k_train_017470 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums: List[int]) -> List[int]: 前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)
- def exchange_2(self, nums: List[int]) -> List[int]: 快慢双指针法 low与fa... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums: List[int]) -> List[int]: 前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)
- def exchange_2(self, nums: List[int]) -> List[int]: 快慢双指针法 low与fa... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
first, last = (0, len(nums) - 1)
while first < last:
if nums[first] % 2 == 1:
first += 1
continue
if nu... | the_stack_v2_python_sparse | SwordOffer/SwordOffer_21.py | EachenKuang/LeetCode | train | 28 | |
f275cb47faca3b046385f94c356da4ad879ec7ac | [
"self.main_window = QtGui.QWidget()\nself.gui = Ui_StopwatchGui()\nself.gui.setupUi(self.main_window)\nself.gui.start_stop_button.clicked.connect(self.start_stop)\nself.stop_event = Event()\nself.stop_event.set()\nself.main_window.show()",
"if self.stop_event.is_set():\n self.stop_event.clear()\n self.timer... | <|body_start_0|>
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.clicked.connect(self.start_stop)
self.stop_event = Event()
self.stop_event.set()
self.main_window.show()
<|end_body_0|>
... | Application class to instantiate and control a StopwatchGui. | StopwatchApp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_020628 | 2,727 | no_license | [
{
"docstring": "Initialize and show the gui.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Start the stopwatch if it is not running; stop it if it is running.",
"name": "start_stop",
"signature": "def start_stop(self)"
},
{
"docstring": "Runs a stopwa... | 3 | stack_v2_sparse_classes_30k_train_001539 | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | e1ad9c8f3e09aec3ee72821bd8374c957f047589 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.cli... | the_stack_v2_python_sparse | DailyLabs/Lsn35/StopwatchApp.py | NathanRuprecht/CS210_IntroToProgramming | train | 0 |
3c8ca1d1107be824d97e590133b8f1d13d75c0a9 | [
"i, j = (0, 0)\nwhile nums[i] != val:\n i += 1\n j += 1\nwhile j != len(nums):\n print(i, j)\n while nums[j] == val:\n j += 1\n if j == len(nums):\n return i\n nums[i] = nums[j]\n i += 1\n j += 1\nreturn i",
"i = 0\nj = len(nums) - 1\nwhile i <= j:\n if nums[i] == ... | <|body_start_0|>
i, j = (0, 0)
while nums[i] != val:
i += 1
j += 1
while j != len(nums):
print(i, j)
while nums[j] == val:
j += 1
if j == len(nums):
return i
nums[i] = nums[j]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElement1(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int"""
<|body_0|>
def removeElement2(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int"""
<|body_1|>
def removeElement3(self, nums, val):
... | stack_v2_sparse_classes_36k_train_020629 | 3,223 | no_license | [
{
"docstring": ":type nums: List[int] :type val: int :rtype: int",
"name": "removeElement1",
"signature": "def removeElement1(self, nums, val)"
},
{
"docstring": ":type nums: List[int] :type val: int :rtype: int",
"name": "removeElement2",
"signature": "def removeElement2(self, nums, val... | 3 | stack_v2_sparse_classes_30k_train_017204 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement1(self, nums, val): :type nums: List[int] :type val: int :rtype: int
- def removeElement2(self, nums, val): :type nums: List[int] :type val: int :rtype: int
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement1(self, nums, val): :type nums: List[int] :type val: int :rtype: int
- def removeElement2(self, nums, val): :type nums: List[int] :type val: int :rtype: int
- de... | 416fed6e441612e1ad82467d07ee1b5570386a94 | <|skeleton|>
class Solution:
def removeElement1(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int"""
<|body_0|>
def removeElement2(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int"""
<|body_1|>
def removeElement3(self, nums, val):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeElement1(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int"""
i, j = (0, 0)
while nums[i] != val:
i += 1
j += 1
while j != len(nums):
print(i, j)
while nums[j] == val:
j += 1... | the_stack_v2_python_sparse | src/python/remove_element.py | liadbiz/Leetcode-Solutions | train | 1 | |
a601a5abae3309dc3df0559f4a6781dc766bbf5f | [
"res = requests.post(url=self.url, headers=self.headers, json=self.data)\nself.assertEquals(res.status_code, 200)\nself.assertEqual(res.json().get('user_info').get('id'), 378392)\nself.assertEqual(res.json().get('user_info').get('nickname'), '陈柏霖')",
"data = self.data.copy()\ndata['identity'] = ''\nres = requests... | <|body_start_0|>
res = requests.post(url=self.url, headers=self.headers, json=self.data)
self.assertEquals(res.status_code, 200)
self.assertEqual(res.json().get('user_info').get('id'), 378392)
self.assertEqual(res.json().get('user_info').get('nickname'), '陈柏霖')
<|end_body_0|>
<|body_sta... | wood登录接口 | Login | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Login:
"""wood登录接口"""
def test_01_wood_login01(self):
"""正常登录-账号密码正确"""
<|body_0|>
def test_02_wood_login02(self):
"""异常登录-账号/密码为空"""
<|body_1|>
def test_03_wood_login03(self):
"""异常登录-账号/密码错误"""
<|body_2|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_020630 | 1,706 | no_license | [
{
"docstring": "正常登录-账号密码正确",
"name": "test_01_wood_login01",
"signature": "def test_01_wood_login01(self)"
},
{
"docstring": "异常登录-账号/密码为空",
"name": "test_02_wood_login02",
"signature": "def test_02_wood_login02(self)"
},
{
"docstring": "异常登录-账号/密码错误",
"name": "test_03_wood_... | 3 | stack_v2_sparse_classes_30k_train_017385 | Implement the Python class `Login` described below.
Class description:
wood登录接口
Method signatures and docstrings:
- def test_01_wood_login01(self): 正常登录-账号密码正确
- def test_02_wood_login02(self): 异常登录-账号/密码为空
- def test_03_wood_login03(self): 异常登录-账号/密码错误 | Implement the Python class `Login` described below.
Class description:
wood登录接口
Method signatures and docstrings:
- def test_01_wood_login01(self): 正常登录-账号密码正确
- def test_02_wood_login02(self): 异常登录-账号/密码为空
- def test_03_wood_login03(self): 异常登录-账号/密码错误
<|skeleton|>
class Login:
"""wood登录接口"""
def test_01_w... | e75039fcd2361977a2a5dc7ea95b7fb2fbc96bb0 | <|skeleton|>
class Login:
"""wood登录接口"""
def test_01_wood_login01(self):
"""正常登录-账号密码正确"""
<|body_0|>
def test_02_wood_login02(self):
"""异常登录-账号/密码为空"""
<|body_1|>
def test_03_wood_login03(self):
"""异常登录-账号/密码错误"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Login:
"""wood登录接口"""
def test_01_wood_login01(self):
"""正常登录-账号密码正确"""
res = requests.post(url=self.url, headers=self.headers, json=self.data)
self.assertEquals(res.status_code, 200)
self.assertEqual(res.json().get('user_info').get('id'), 378392)
self.assertEqual(... | the_stack_v2_python_sparse | API_study/Wood/A_Login.py | JmeterChen/api_wood | train | 1 |
5d9aaa0422098bfa6a3c9002460492d59000f002 | [
"self.n = len(multipliers[0])\nassert binom(self.n, 2) == len(multipliers[1]), 'Wrong number of couplings.'\nassert binom(self.n, 3) == len(multipliers[2]), 'Wrong number of triplet interactions.'\nmultipliers = np.concatenate(multipliers)\nself.calc_e = define_triplet_helper_functions()[0]\ntry:\n ising = impor... | <|body_start_0|>
self.n = len(multipliers[0])
assert binom(self.n, 2) == len(multipliers[1]), 'Wrong number of couplings.'
assert binom(self.n, 3) == len(multipliers[2]), 'Wrong number of triplet interactions.'
multipliers = np.concatenate(multipliers)
self.calc_e = define_triple... | Third order maxent model constraining means, pairwise correlations, and triplet correlations. | Triplet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Triplet:
"""Third order maxent model constraining means, pairwise correlations, and triplet correlations."""
def __init__(self, multipliers, rng=None, n_cpus=None, verbose=False):
"""Parameters ---------- multipliers : list of ndarray or ndarray Can be a list of vectors [fields, coup... | stack_v2_sparse_classes_36k_train_020631 | 12,395 | permissive | [
{
"docstring": "Parameters ---------- multipliers : list of ndarray or ndarray Can be a list of vectors [fields, couplings], a vector of fields and couplings concatenated together, or a matrix of parameters where the diagonal entries are the fields.",
"name": "__init__",
"signature": "def __init__(self,... | 2 | stack_v2_sparse_classes_30k_train_018444 | Implement the Python class `Triplet` described below.
Class description:
Third order maxent model constraining means, pairwise correlations, and triplet correlations.
Method signatures and docstrings:
- def __init__(self, multipliers, rng=None, n_cpus=None, verbose=False): Parameters ---------- multipliers : list of ... | Implement the Python class `Triplet` described below.
Class description:
Third order maxent model constraining means, pairwise correlations, and triplet correlations.
Method signatures and docstrings:
- def __init__(self, multipliers, rng=None, n_cpus=None, verbose=False): Parameters ---------- multipliers : list of ... | f25863705f8e459771ef60ea51c4bd6587904c78 | <|skeleton|>
class Triplet:
"""Third order maxent model constraining means, pairwise correlations, and triplet correlations."""
def __init__(self, multipliers, rng=None, n_cpus=None, verbose=False):
"""Parameters ---------- multipliers : list of ndarray or ndarray Can be a list of vectors [fields, coup... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Triplet:
"""Third order maxent model constraining means, pairwise correlations, and triplet correlations."""
def __init__(self, multipliers, rng=None, n_cpus=None, verbose=False):
"""Parameters ---------- multipliers : list of ndarray or ndarray Can be a list of vectors [fields, couplings], a vec... | the_stack_v2_python_sparse | coniii/models.py | eltrompetero/coniii | train | 18 |
27497175e67a23b396b5523e6ddffdfe17ca787a | [
"if isinstance(hypothesis, str):\n hypothesis = {hypothesis}\n references = {references}\nelse:\n hypothesis = set(hypothesis)\n references = set(references)\nassert len(hypothesis) == len(references), 'Hypothesis and reference lists must have the same length'\nscore = self.metric(test=hypothesis, refer... | <|body_start_0|>
if isinstance(hypothesis, str):
hypothesis = {hypothesis}
references = {references}
else:
hypothesis = set(hypothesis)
references = set(references)
assert len(hypothesis) == len(references), 'Hypothesis and reference lists must hav... | NLTKScore template metric class | NLTKScore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NLTKScore:
"""NLTKScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute NLTKScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypot... | stack_v2_sparse_classes_36k_train_020632 | 7,252 | permissive | [
{
"docstring": "Compute NLTKScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypothesis sentences reference (str): a reference sentence or a list of reference sentences kwargs: see complete list at: https://www.nltk.org/_modules/nltk/metrics/scores.html R... | 2 | stack_v2_sparse_classes_30k_train_021020 | Implement the Python class `NLTKScore` described below.
Class description:
NLTKScore template metric class
Method signatures and docstrings:
- def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float: Compute NLTKScore score of a hypothesis and a reference. Params: h... | Implement the Python class `NLTKScore` described below.
Class description:
NLTKScore template metric class
Method signatures and docstrings:
- def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float: Compute NLTKScore score of a hypothesis and a reference. Params: h... | bef8033d9b9d7ea9797b5a0fdc7558d388bb0bfd | <|skeleton|>
class NLTKScore:
"""NLTKScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute NLTKScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypot... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NLTKScore:
"""NLTKScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute NLTKScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypothesis sentenc... | the_stack_v2_python_sparse | platiagro/metrics_nlp/base.py | platiagro/sdk | train | 1 |
6815c30386a904b0d1f9a12476307995e9fead0d | [
"self.ensure_one()\ndomain = [('product_id', '=', self.id), ('remaining_qty', '>', 0.0), ('location_dest_id', '=', location_id)] + self.env['stock.move']._get_in_base_domain()\ncandidates = self.env['stock.move'].search(domain, order='date, id')\nreturn candidates",
"self.ensure_one()\ndomain = [('product_id', '=... | <|body_start_0|>
self.ensure_one()
domain = [('product_id', '=', self.id), ('remaining_qty', '>', 0.0), ('location_dest_id', '=', location_id)] + self.env['stock.move']._get_in_base_domain()
candidates = self.env['stock.move'].search(domain, order='date, id')
return candidates
<|end_body... | ProductProduct | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductProduct:
def _get_fifo_candidates_in_move_location(self, location_id):
"""Buscar movimientos por ubicacion"""
<|body_0|>
def _get_fifo_candidates_in_move_location_lot(self, location_id, lot_id):
"""Buscar movimientos por ubicacion"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_020633 | 3,276 | no_license | [
{
"docstring": "Buscar movimientos por ubicacion",
"name": "_get_fifo_candidates_in_move_location",
"signature": "def _get_fifo_candidates_in_move_location(self, location_id)"
},
{
"docstring": "Buscar movimientos por ubicacion",
"name": "_get_fifo_candidates_in_move_location_lot",
"sign... | 2 | stack_v2_sparse_classes_30k_val_000166 | Implement the Python class `ProductProduct` described below.
Class description:
Implement the ProductProduct class.
Method signatures and docstrings:
- def _get_fifo_candidates_in_move_location(self, location_id): Buscar movimientos por ubicacion
- def _get_fifo_candidates_in_move_location_lot(self, location_id, lot_... | Implement the Python class `ProductProduct` described below.
Class description:
Implement the ProductProduct class.
Method signatures and docstrings:
- def _get_fifo_candidates_in_move_location(self, location_id): Buscar movimientos por ubicacion
- def _get_fifo_candidates_in_move_location_lot(self, location_id, lot_... | 6682e60630064641474ddb2d8cbc520e30f64832 | <|skeleton|>
class ProductProduct:
def _get_fifo_candidates_in_move_location(self, location_id):
"""Buscar movimientos por ubicacion"""
<|body_0|>
def _get_fifo_candidates_in_move_location_lot(self, location_id, lot_id):
"""Buscar movimientos por ubicacion"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductProduct:
def _get_fifo_candidates_in_move_location(self, location_id):
"""Buscar movimientos por ubicacion"""
self.ensure_one()
domain = [('product_id', '=', self.id), ('remaining_qty', '>', 0.0), ('location_dest_id', '=', location_id)] + self.env['stock.move']._get_in_base_doma... | the_stack_v2_python_sparse | poi_purchase_imports/models/product.py | blue-connect/illuminati | train | 0 | |
fe668ccd05a105915ac46ec0fcab245e1c1ef886 | [
"try:\n path = os.path.join(ROOT_DIR, '../tests/results.json')\n results = self.__get_mock_results(path)\nexcept Exception as ex:\n raise ex\nraise gen.Return(results)",
"try:\n results = '{\"$oid\": \"59dc3e8c8f54a9000d1fb89f\"}'\n if not results:\n raise Exception('Failed to write results ... | <|body_start_0|>
try:
path = os.path.join(ROOT_DIR, '../tests/results.json')
results = self.__get_mock_results(path)
except Exception as ex:
raise ex
raise gen.Return(results)
<|end_body_0|>
<|body_start_1|>
try:
results = '{"$oid": "59dc3... | Provides a testing mock for the mongo results handler | TestResultsProvider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestResultsProvider:
"""Provides a testing mock for the mongo results handler"""
def get_results(self, result_id=None):
"""Method implements the results mock of mongo args: result_id: key to get data from results db Returns: data responding to the result_id"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020634 | 3,775 | no_license | [
{
"docstring": "Method implements the results mock of mongo args: result_id: key to get data from results db Returns: data responding to the result_id",
"name": "get_results",
"signature": "def get_results(self, result_id=None)"
},
{
"docstring": "Method implements the write results mock of mong... | 6 | stack_v2_sparse_classes_30k_train_017222 | Implement the Python class `TestResultsProvider` described below.
Class description:
Provides a testing mock for the mongo results handler
Method signatures and docstrings:
- def get_results(self, result_id=None): Method implements the results mock of mongo args: result_id: key to get data from results db Returns: da... | Implement the Python class `TestResultsProvider` described below.
Class description:
Provides a testing mock for the mongo results handler
Method signatures and docstrings:
- def get_results(self, result_id=None): Method implements the results mock of mongo args: result_id: key to get data from results db Returns: da... | 7c3edfbb6c2708b96b8c8d61fe865dbb1357690e | <|skeleton|>
class TestResultsProvider:
"""Provides a testing mock for the mongo results handler"""
def get_results(self, result_id=None):
"""Method implements the results mock of mongo args: result_id: key to get data from results db Returns: data responding to the result_id"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestResultsProvider:
"""Provides a testing mock for the mongo results handler"""
def get_results(self, result_id=None):
"""Method implements the results mock of mongo args: result_id: key to get data from results db Returns: data responding to the result_id"""
try:
path = os.p... | the_stack_v2_python_sparse | results/webapi/providers/test_results_provider.py | KamilBabayev/webapi_temp | train | 0 |
f59c9bf73253544f8295c3f367fd0232caa4d9c0 | [
"memory = []\n\ndef add_coor(a, b):\n ans = 0\n while a != 0:\n ans += a % 10\n a //= 10\n while b != 0:\n ans += b % 10\n b //= 10\n return ans\n\ndef __dfs(col, row):\n if col >= m or row >= n:\n return\n if [col, row] in memory:\n return\n if add_coo... | <|body_start_0|>
memory = []
def add_coor(a, b):
ans = 0
while a != 0:
ans += a % 10
a //= 10
while b != 0:
ans += b % 10
b //= 10
return ans
def __dfs(col, row):
if col ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递归 巨慢无比"""
<|body_0|>
def movingCount1(self, m: int, n: int, k: int) -> int:
"""比递归快了十倍"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
memory = []
def add_coor(a, b):
... | stack_v2_sparse_classes_36k_train_020635 | 2,545 | no_license | [
{
"docstring": "递归 巨慢无比",
"name": "movingCount",
"signature": "def movingCount(self, m: int, n: int, k: int) -> int"
},
{
"docstring": "比递归快了十倍",
"name": "movingCount1",
"signature": "def movingCount1(self, m: int, n: int, k: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_021087 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m: int, n: int, k: int) -> int: 递归 巨慢无比
- def movingCount1(self, m: int, n: int, k: int) -> int: 比递归快了十倍 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m: int, n: int, k: int) -> int: 递归 巨慢无比
- def movingCount1(self, m: int, n: int, k: int) -> int: 比递归快了十倍
<|skeleton|>
class Solution:
def movingCount(... | 40726506802d2d60028fdce206696b1df2f63ece | <|skeleton|>
class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递归 巨慢无比"""
<|body_0|>
def movingCount1(self, m: int, n: int, k: int) -> int:
"""比递归快了十倍"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递归 巨慢无比"""
memory = []
def add_coor(a, b):
ans = 0
while a != 0:
ans += a % 10
a //= 10
while b != 0:
ans += b % 10
b ... | the_stack_v2_python_sparse | 二刷+题解/每日一题/movingCount.py | 1oser5/LeetCode | train | 0 | |
efee257ca15193f95673f1d5d97d2225691dedfb | [
"from django.contrib.auth.models import User\nu = User.objects.create(username='test', password='test')\nself.failUnless(u.get_profile())",
"from django.contrib.auth.models import User\nr = self.client.post('/account/register/', {'first_name': 'Test', 'last_name': 'Example', 'username': 'test', 'email': 'test.use... | <|body_start_0|>
from django.contrib.auth.models import User
u = User.objects.create(username='test', password='test')
self.failUnless(u.get_profile())
<|end_body_0|>
<|body_start_1|>
from django.contrib.auth.models import User
r = self.client.post('/account/register/', {'first_... | UserTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserTest:
def test_profile_created(self):
"""Tests that a new user gets a default profile"""
<|body_0|>
def test_profile_filled(self):
"""Test that registration profile values are populated in the Profile."""
<|body_1|>
def test_first_last_name(self):
... | stack_v2_sparse_classes_36k_train_020636 | 2,523 | permissive | [
{
"docstring": "Tests that a new user gets a default profile",
"name": "test_profile_created",
"signature": "def test_profile_created(self)"
},
{
"docstring": "Test that registration profile values are populated in the Profile.",
"name": "test_profile_filled",
"signature": "def test_prof... | 4 | null | Implement the Python class `UserTest` described below.
Class description:
Implement the UserTest class.
Method signatures and docstrings:
- def test_profile_created(self): Tests that a new user gets a default profile
- def test_profile_filled(self): Test that registration profile values are populated in the Profile.
... | Implement the Python class `UserTest` described below.
Class description:
Implement the UserTest class.
Method signatures and docstrings:
- def test_profile_created(self): Tests that a new user gets a default profile
- def test_profile_filled(self): Test that registration profile values are populated in the Profile.
... | 651da880a3d4295243205bdae4de88504edc91de | <|skeleton|>
class UserTest:
def test_profile_created(self):
"""Tests that a new user gets a default profile"""
<|body_0|>
def test_profile_filled(self):
"""Test that registration profile values are populated in the Profile."""
<|body_1|>
def test_first_last_name(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserTest:
def test_profile_created(self):
"""Tests that a new user gets a default profile"""
from django.contrib.auth.models import User
u = User.objects.create(username='test', password='test')
self.failUnless(u.get_profile())
def test_profile_filled(self):
"""Tes... | the_stack_v2_python_sparse | communityprofiles/account/tests.py | 216software/Profiles | train | 3 | |
2f8be3e29d5f38fee2c29cec8682943e6b6c626a | [
"try:\n query = self.request.dbsession.query(models.Service)\n one = query.filter(models.Service.name == name).first()\n if one:\n one.url = baseurl(url)\n one.type = kwargs.get('type', 'WPS')\n one.purl = kwargs.get('purl', '')\n one._verify = int(kwargs.get('verify', 1))\n ... | <|body_start_0|>
try:
query = self.request.dbsession.query(models.Service)
one = query.filter(models.Service.name == name).first()
if one:
one.url = baseurl(url)
one.type = kwargs.get('type', 'WPS')
one.purl = kwargs.get('purl',... | Stores a services. It inserts or updates the service with a given name. | ServiceStore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceStore:
"""Stores a services. It inserts or updates the service with a given name."""
def save_service(self, name, url, *args, **kwargs):
"""Stores an OWS service in database (insert or update). :param name: A service name string. :param url: A URL string."""
<|body_0|>... | stack_v2_sparse_classes_36k_train_020637 | 3,805 | permissive | [
{
"docstring": "Stores an OWS service in database (insert or update). :param name: A service name string. :param url: A URL string.",
"name": "save_service",
"signature": "def save_service(self, name, url, *args, **kwargs)"
},
{
"docstring": "Removes service identified by name.",
"name": "de... | 6 | stack_v2_sparse_classes_30k_train_000547 | Implement the Python class `ServiceStore` described below.
Class description:
Stores a services. It inserts or updates the service with a given name.
Method signatures and docstrings:
- def save_service(self, name, url, *args, **kwargs): Stores an OWS service in database (insert or update). :param name: A service nam... | Implement the Python class `ServiceStore` described below.
Class description:
Stores a services. It inserts or updates the service with a given name.
Method signatures and docstrings:
- def save_service(self, name, url, *args, **kwargs): Stores an OWS service in database (insert or update). :param name: A service nam... | aca67f1fb7f9014ccb8718666b865287da7c61d5 | <|skeleton|>
class ServiceStore:
"""Stores a services. It inserts or updates the service with a given name."""
def save_service(self, name, url, *args, **kwargs):
"""Stores an OWS service in database (insert or update). :param name: A service name string. :param url: A URL string."""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceStore:
"""Stores a services. It inserts or updates the service with a given name."""
def save_service(self, name, url, *args, **kwargs):
"""Stores an OWS service in database (insert or update). :param name: A service name string. :param url: A URL string."""
try:
query ... | the_stack_v2_python_sparse | twitcher/store.py | bird-house/twitcher | train | 16 |
718a5b320ad44ab875739eaca61bdb58f48e1bdf | [
"super(SrcmapsCatalog_SG, self).__init__(link, **kwargs)\nself._comp_dict_file = None\nself._comp_dict = None",
"for val in catalog_info_dict.values():\n val.roi_model.write_xml(val.srcmdl_name)\nfor val in comp_info_dict.values():\n for val2 in val.values():\n val2.roi_model.write_xml(val2.srcmdl_na... | <|body_start_0|>
super(SrcmapsCatalog_SG, self).__init__(link, **kwargs)
self._comp_dict_file = None
self._comp_dict = None
<|end_body_0|>
<|body_start_1|>
for val in catalog_info_dict.values():
val.roi_model.write_xml(val.srcmdl_name)
for val in comp_info_dict.value... | Small class to generate configurations for gtsrcmaps for catalog sources | SrcmapsCatalog_SG | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SrcmapsCatalog_SG:
"""Small class to generate configurations for gtsrcmaps for catalog sources"""
def __init__(self, link, **kwargs):
"""C'tor"""
<|body_0|>
def _make_xml_files(catalog_info_dict, comp_info_dict):
"""Make all the xml file for individual components... | stack_v2_sparse_classes_36k_train_020638 | 8,377 | permissive | [
{
"docstring": "C'tor",
"name": "__init__",
"signature": "def __init__(self, link, **kwargs)"
},
{
"docstring": "Make all the xml file for individual components",
"name": "_make_xml_files",
"signature": "def _make_xml_files(catalog_info_dict, comp_info_dict)"
},
{
"docstring": "H... | 3 | null | Implement the Python class `SrcmapsCatalog_SG` described below.
Class description:
Small class to generate configurations for gtsrcmaps for catalog sources
Method signatures and docstrings:
- def __init__(self, link, **kwargs): C'tor
- def _make_xml_files(catalog_info_dict, comp_info_dict): Make all the xml file for ... | Implement the Python class `SrcmapsCatalog_SG` described below.
Class description:
Small class to generate configurations for gtsrcmaps for catalog sources
Method signatures and docstrings:
- def __init__(self, link, **kwargs): C'tor
- def _make_xml_files(catalog_info_dict, comp_info_dict): Make all the xml file for ... | fbd4c95ffadbff31cbb9cc862ff84a78dc734ef5 | <|skeleton|>
class SrcmapsCatalog_SG:
"""Small class to generate configurations for gtsrcmaps for catalog sources"""
def __init__(self, link, **kwargs):
"""C'tor"""
<|body_0|>
def _make_xml_files(catalog_info_dict, comp_info_dict):
"""Make all the xml file for individual components... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SrcmapsCatalog_SG:
"""Small class to generate configurations for gtsrcmaps for catalog sources"""
def __init__(self, link, **kwargs):
"""C'tor"""
super(SrcmapsCatalog_SG, self).__init__(link, **kwargs)
self._comp_dict_file = None
self._comp_dict = None
def _make_xml_f... | the_stack_v2_python_sparse | fermipy/diffuse/gt_srcmaps_catalog.py | fermiPy/fermipy | train | 51 |
595aadebe16a5805138498eadec06422403841a0 | [
"if not (head and head.next):\n return head\nfirst = head.next\nsecond = head\nhead.next = None\nwhile first.next:\n p = first\n first = first.next\n p.next = second\n second = p\nfirst.next = second\nreturn first",
"if not head or not head.next:\n return head\ntail = self.reverseList2(head.next... | <|body_start_0|>
if not (head and head.next):
return head
first = head.next
second = head
head.next = None
while first.next:
p = first
first = first.next
p.next = second
second = p
first.next = second
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它next指针的位置 3. 调整p的next指针，将其指向second 4. second 指向 p. 返回值：first 边界情况1：头节点为空 或者 只有一个头节点 ---- 不满足，需单独处理... | stack_v2_sparse_classes_36k_train_020639 | 3,995 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它next指针的位置 3. 调整p的next指针，将其指向second 4. second 指向 p. 返回值：first 边界情况1：头节点为空 或者 只有一个头节点 ---- 不满足，需单独处理 易错点： 一定要记得把头节点的后继节点蛇者为空（None)否则会再链表中出现无限循环的环！",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它n... | ca88c13392e971b64fc1704351cfe654b905d586 | <|skeleton|>
class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它next指针的位置 3. 调整p的next指针，将其指向second 4. second 指向 p. 返回值：first 边界情况1：头节点为空 或者 只有一个头节点 ---- 不满足，需单独处理... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode 迭代思路： 两个指针 first(初始位置：head.next) second(初始位置：head) 迭代（循环）条件：first到达链表末尾 1. 设置中间指针：p.使得 p = first 2. first 前进到它next指针的位置 3. 调整p的next指针，将其指向second 4. second 指向 p. 返回值：first 边界情况1：头节点为空 或者 只有一个头节点 ---- 不满足，需单独处理 易错点： 一定要记得把头节... | the_stack_v2_python_sparse | linkedList_Part/leetcode206.py | Jackie1995/leetcode_answers | train | 0 | |
0b6b9fe093eda8c6aa22e7ba4f8f9f0fac416e14 | [
"self.cluster_id = cluster_id\nself.cluster_incarnation_id = cluster_incarnation_id\nself.document_ids = document_ids\nself.entity_id = entity_id\nself.job_id = job_id\nself.job_instance_ids = job_instance_ids\nself.tag_ids = tag_ids\nself.tags = tags",
"if dictionary is None:\n return None\ncluster_id = dicti... | <|body_start_0|>
self.cluster_id = cluster_id
self.cluster_incarnation_id = cluster_incarnation_id
self.document_ids = document_ids
self.entity_id = entity_id
self.job_id = job_id
self.job_instance_ids = job_instance_ids
self.tag_ids = tag_ids
self.tags = ... | Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterIncarnationId is the incarnation Id of the cluster used for constructing JobUid. document_ids ... | TagsOperationParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagsOperationParameters:
"""Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterIncarnationId is the incarnation Id of the ... | stack_v2_sparse_classes_36k_train_020640 | 3,511 | permissive | [
{
"docstring": "Constructor for the TagsOperationParameters class",
"name": "__init__",
"signature": "def __init__(self, cluster_id=None, cluster_incarnation_id=None, document_ids=None, entity_id=None, job_id=None, job_instance_ids=None, tag_ids=None, tags=None)"
},
{
"docstring": "Creates an in... | 2 | null | Implement the Python class `TagsOperationParameters` described below.
Class description:
Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterInca... | Implement the Python class `TagsOperationParameters` described below.
Class description:
Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterInca... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class TagsOperationParameters:
"""Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterIncarnationId is the incarnation Id of the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagsOperationParameters:
"""Implementation of the 'TagsOperationParameters' model. TODO: type description here. Attributes: cluster_id (long|int): ClusterId is the Id of the cluster used for constructing JobUid. cluster_incarnation_id (long|int): ClusterIncarnationId is the incarnation Id of the cluster used ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/tags_operation_parameters.py | cohesity/management-sdk-python | train | 24 |
31e5f727d55c324bd3931ceb70519d5533cd67e7 | [
"pagination = req.context.get('pagination')\npost_collection_dto = PostCollectionV2Dto(posts=[post_to_v2_dto(post, href=PostResource.url_to(req.netloc, post_id=post.id), links=get_post_links(req, post)) for post in get_posts(start=pagination.get('start'), count=pagination.get('count'))])\nresp.body = post_collectio... | <|body_start_0|>
pagination = req.context.get('pagination')
post_collection_dto = PostCollectionV2Dto(posts=[post_to_v2_dto(post, href=PostResource.url_to(req.netloc, post_id=post.id), links=get_post_links(req, post)) for post in get_posts(start=pagination.get('start'), count=pagination.get('count'))])
... | PostCollectionResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostCollectionResource:
def on_get(self, req, resp):
"""Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided via query args."""
<|body_0|>
def on_post(self, req, resp):
"""Create a new post resource.""... | stack_v2_sparse_classes_36k_train_020641 | 7,743 | permissive | [
{
"docstring": "Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided via query args.",
"name": "on_get",
"signature": "def on_get(self, req, resp)"
},
{
"docstring": "Create a new post resource.",
"name": "on_post",
"signa... | 2 | stack_v2_sparse_classes_30k_train_016741 | Implement the Python class `PostCollectionResource` described below.
Class description:
Implement the PostCollectionResource class.
Method signatures and docstrings:
- def on_get(self, req, resp): Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided vi... | Implement the Python class `PostCollectionResource` described below.
Class description:
Implement the PostCollectionResource class.
Method signatures and docstrings:
- def on_get(self, req, resp): Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided vi... | e507fe0307d1a7ea29d6c3e20be62fa82a8f109f | <|skeleton|>
class PostCollectionResource:
def on_get(self, req, resp):
"""Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided via query args."""
<|body_0|>
def on_post(self, req, resp):
"""Create a new post resource.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostCollectionResource:
def on_get(self, req, resp):
"""Fetch grid view for all post resources. Note: This endpoint supports pagination, pagination arguments must be provided via query args."""
pagination = req.context.get('pagination')
post_collection_dto = PostCollectionV2Dto(posts=[... | the_stack_v2_python_sparse | blog/resources/posts.py | neetjn/py-blog | train | 0 | |
52a66f541ca28c9c9f057087084ecc6a24d6bad5 | [
"super(Info, self).__init__(gis=gis, url=url)\nself._con = gis\nself._url = url\nif initialize:\n self._init(gis)",
"url = self._url + '/getAvailableTimeZones'\nparams = {'f': 'json'}\nreturn self._con.get(path=url, params=params)"
] | <|body_start_0|>
super(Info, self).__init__(gis=gis, url=url)
self._con = gis
self._url = url
if initialize:
self._init(gis)
<|end_body_0|>
<|body_start_1|>
url = self._url + '/getAvailableTimeZones'
params = {'f': 'json'}
return self._con.get(path=ur... | A read-only resource that returns meta information about the server. | Info | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Info:
"""A read-only resource that returns meta information about the server."""
def __init__(self, url, gis, initialize=False):
"""Constructor =============== ==================================================================== **Argument** **Description** --------------- ----------... | stack_v2_sparse_classes_36k_train_020642 | 1,998 | permissive | [
{
"docstring": "Constructor =============== ==================================================================== **Argument** **Description** --------------- -------------------------------------------------------------------- url Required string. The administration URL for the ArcGIS Server. --------------- --... | 2 | null | Implement the Python class `Info` described below.
Class description:
A read-only resource that returns meta information about the server.
Method signatures and docstrings:
- def __init__(self, url, gis, initialize=False): Constructor =============== ===================================================================... | Implement the Python class `Info` described below.
Class description:
A read-only resource that returns meta information about the server.
Method signatures and docstrings:
- def __init__(self, url, gis, initialize=False): Constructor =============== ===================================================================... | a874fe7e5c95196e4de68db2da0e2a05eb70e5d8 | <|skeleton|>
class Info:
"""A read-only resource that returns meta information about the server."""
def __init__(self, url, gis, initialize=False):
"""Constructor =============== ==================================================================== **Argument** **Description** --------------- ----------... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Info:
"""A read-only resource that returns meta information about the server."""
def __init__(self, url, gis, initialize=False):
"""Constructor =============== ==================================================================== **Argument** **Description** --------------- -----------------------... | the_stack_v2_python_sparse | arcpyenv/arcgispro-py3-clone/Lib/site-packages/arcgis/gis/server/admin/_info.py | SherbazHashmi/HackathonServer | train | 3 |
512fa7d7c5fe95444ef6b8b6d2eae9f9aea660cf | [
"assert not kwargs, kwargs\nattributes = AttributesHelper(self, attributes)\nif not attributes.iswildcard:\n warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')\n attributes = AttributesHelper(self)\nconfigurations = CliConfigBuilder()\nif Fa... | <|body_start_0|>
assert not kwargs, kwargs
attributes = AttributesHelper(self, attributes)
if not attributes.iswildcard:
warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')
attributes = AttributesHelper(s... | DeviceAttributes | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_36k_train_020643 | 7,073 | permissive | [
{
"docstring": "IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured.",
"name": "build_config",
"signature": "def build_config(self, apply=True, attributes=None, **kwargs)"
},
{
"docstring": "IOS-... | 2 | stack_v2_sparse_classes_30k_train_005983 | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | e42e51475cddcb10f5c7814d0fe892ac865742ba | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
assert not kwargs, kwargs
attributes = Attrib... | the_stack_v2_python_sparse | pkgs/conf-pkg/src/genie/libs/conf/community_set/iosxr/community_set.py | CiscoTestAutomation/genielibs | train | 109 | |
7ed0bfb8fe3b5a4bbcf560ff48a43f238a1a2414 | [
"edges = collections.defaultdict(list)\nindeg = [0] * numCourses\nresult = []\nfor info in prerequisites:\n edges[info[1]].append(info[0])\n indeg[info[0]] += 1\nq = collections.deque([u for u in range(numCourses) if indeg[u] == 0])\nvisited = 0\nwhile q:\n visited += 1\n u = q.popleft()\n result.app... | <|body_start_0|>
edges = collections.defaultdict(list)
indeg = [0] * numCourses
result = []
for info in prerequisites:
edges[info[1]].append(info[0])
indeg[info[0]] += 1
q = collections.deque([u for u in range(numCourses) if indeg[u] == 0])
visited... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]':
"""BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)"""
<|body_0|>
def findOrder_DFS(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]':
"""DFS 深度优先遍历 较难理解 每个节点有三... | stack_v2_sparse_classes_36k_train_020644 | 2,713 | no_license | [
{
"docstring": "BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)",
"name": "findOrder",
"signature": "def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]'"
},
{
"docstring": "DFS 深度优先遍历 较难理解 每个节点有三种状态 0:未搜索；京东：搜索中；2：搜索完毕",
"name": "findOrder_DFS",
"signature": "def f... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]': BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)
- def findOrder_DFS(self, numCourses: int, prerequisit... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]': BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)
- def findOrder_DFS(self, numCourses: int, prerequisit... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Solution:
def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]':
"""BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)"""
<|body_0|>
def findOrder_DFS(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]':
"""DFS 深度优先遍历 较难理解 每个节点有三... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findOrder(self, numCourses: int, prerequisites: 'List[List[int]]') -> 'List[int]':
"""BFS 广度优先遍历 时间复杂度 O(m+n) 空间复杂度 O(m+n)"""
edges = collections.defaultdict(list)
indeg = [0] * numCourses
result = []
for info in prerequisites:
edges[info[1]].a... | the_stack_v2_python_sparse | 4_LEETCODE/1_DataStructure/6_Graph/拓扑排序/210_课程表II.py | fzingithub/SwordRefers2Offer | train | 1 | |
97a6684f34c27af5775881fc8c889c5c3bf7234f | [
"self.project_id = project_id\nself.datastore = datastore\nself.filestore = filestore\nself.datasets: Dict[str, DatasetDescriptor] = {name: cast(DatasetDescriptor, artifacts[name]) for name in artifacts if artifacts[name].is_dataset}\nself.resources = resources\nself.dataobjects: Dict[str, ArtifactDescriptor] = {na... | <|body_start_0|>
self.project_id = project_id
self.datastore = datastore
self.filestore = filestore
self.datasets: Dict[str, DatasetDescriptor] = {name: cast(DatasetDescriptor, artifacts[name]) for name in artifacts if artifacts[name].is_dataset}
self.resources = resources
... | The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is represented as a mapping of user-defined dataset names to unique dataset identifie... | TaskContext | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskContext:
"""The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is represented as a mapping of user-defined da... | stack_v2_sparse_classes_36k_train_020645 | 5,610 | permissive | [
{
"docstring": "Initialize the components of the task context. Parameters ---------- project_id: string project_id of the task datastore: vizier.datastore.base.Datastore Datastore for the project that execute the task filestore: vizier.filestore.Filestore Filestore for the project that executes the task dataset... | 3 | null | Implement the Python class `TaskContext` described below.
Class description:
The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is repr... | Implement the Python class `TaskContext` described below.
Class description:
The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is repr... | e99f43df3df80ad5647f57d805c339257336ac73 | <|skeleton|>
class TaskContext:
"""The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is represented as a mapping of user-defined da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskContext:
"""The task context contains references to the datastore and filestore that are associated with the project that executes the task. The context also contains the current database state against which a task is executed. The database state is represented as a mapping of user-defined dataset names t... | the_stack_v2_python_sparse | vizier/engine/task/base.py | VizierDB/web-api-async | train | 2 |
558d56f7b12cc69848044feba82b7a4fb63f1586 | [
"self.cube = set_up_variable_cube(np.ones((5, 5), dtype=np.float32), spatial_grid='equalarea')\ncoord_points_x = np.linspace(10.0, 50.0, 5)\nx_bounds = np.array([coord_points_x - 5, coord_points_x + 5]).T\ncoord_points_y = np.linspace(5.0, 85.0, 5)\ny_bounds = np.array([coord_points_y - 10, coord_points_y + 10]).T\... | <|body_start_0|>
self.cube = set_up_variable_cube(np.ones((5, 5), dtype=np.float32), spatial_grid='equalarea')
coord_points_x = np.linspace(10.0, 50.0, 5)
x_bounds = np.array([coord_points_x - 5, coord_points_x + 5]).T
coord_points_y = np.linspace(5.0, 85.0, 5)
y_bounds = np.arra... | Test the padding of a coordinate. | Test_pad_coord | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_pad_coord:
"""Test the padding of a coordinate."""
def setUp(self):
"""Set up a cube."""
<|body_0|>
def test_add(self):
"""Test the functionality to add padding to the chosen coordinate. Includes a test that the coordinate bounds array is modified to reflect... | stack_v2_sparse_classes_36k_train_020646 | 25,212 | permissive | [
{
"docstring": "Set up a cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test the functionality to add padding to the chosen coordinate. Includes a test that the coordinate bounds array is modified to reflect the new values.",
"name": "test_add",
"signature": "... | 5 | null | Implement the Python class `Test_pad_coord` described below.
Class description:
Test the padding of a coordinate.
Method signatures and docstrings:
- def setUp(self): Set up a cube.
- def test_add(self): Test the functionality to add padding to the chosen coordinate. Includes a test that the coordinate bounds array i... | Implement the Python class `Test_pad_coord` described below.
Class description:
Test the padding of a coordinate.
Method signatures and docstrings:
- def setUp(self): Set up a cube.
- def test_add(self): Test the functionality to add padding to the chosen coordinate. Includes a test that the coordinate bounds array i... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_pad_coord:
"""Test the padding of a coordinate."""
def setUp(self):
"""Set up a cube."""
<|body_0|>
def test_add(self):
"""Test the functionality to add padding to the chosen coordinate. Includes a test that the coordinate bounds array is modified to reflect... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_pad_coord:
"""Test the padding of a coordinate."""
def setUp(self):
"""Set up a cube."""
self.cube = set_up_variable_cube(np.ones((5, 5), dtype=np.float32), spatial_grid='equalarea')
coord_points_x = np.linspace(10.0, 50.0, 5)
x_bounds = np.array([coord_points_x - 5, ... | the_stack_v2_python_sparse | improver_tests/utilities/test_pad_spatial.py | metoppv/improver | train | 101 |
445ebe2f8dedf5332f8e9ce4f94af0b56f7c848d | [
"params = dict({'quiet': ''})\nregressor = SupportVectorRegressor(len(self.fncs))\ninput_data = np.random.rand(self.input_vecs, self.input_length)\nassert len(regressor.regressors) == len(self.fncs)\ntestRegressor(regressor, input_data, self.fncs, params)",
"regressor = LinearRegressor()\ninput_data = np.random.r... | <|body_start_0|>
params = dict({'quiet': ''})
regressor = SupportVectorRegressor(len(self.fncs))
input_data = np.random.rand(self.input_vecs, self.input_length)
assert len(regressor.regressors) == len(self.fncs)
testRegressor(regressor, input_data, self.fncs, params)
<|end_body_0... | RegressorTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressorTestCase:
def testSupportVectorRegressor(self):
"""Test the Support Vector Regressor"""
<|body_0|>
def testLinearRegressor(self):
"""Test the Linear Regressor"""
<|body_1|>
def testFeedforwardNeuralNetworkRegressor(self):
"""Test the Fee... | stack_v2_sparse_classes_36k_train_020647 | 2,989 | no_license | [
{
"docstring": "Test the Support Vector Regressor",
"name": "testSupportVectorRegressor",
"signature": "def testSupportVectorRegressor(self)"
},
{
"docstring": "Test the Linear Regressor",
"name": "testLinearRegressor",
"signature": "def testLinearRegressor(self)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_014292 | Implement the Python class `RegressorTestCase` described below.
Class description:
Implement the RegressorTestCase class.
Method signatures and docstrings:
- def testSupportVectorRegressor(self): Test the Support Vector Regressor
- def testLinearRegressor(self): Test the Linear Regressor
- def testFeedforwardNeuralNe... | Implement the Python class `RegressorTestCase` described below.
Class description:
Implement the RegressorTestCase class.
Method signatures and docstrings:
- def testSupportVectorRegressor(self): Test the Support Vector Regressor
- def testLinearRegressor(self): Test the Linear Regressor
- def testFeedforwardNeuralNe... | 0486b769c8168a675d7fba25f90ae05c6759bee1 | <|skeleton|>
class RegressorTestCase:
def testSupportVectorRegressor(self):
"""Test the Support Vector Regressor"""
<|body_0|>
def testLinearRegressor(self):
"""Test the Linear Regressor"""
<|body_1|>
def testFeedforwardNeuralNetworkRegressor(self):
"""Test the Fee... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegressorTestCase:
def testSupportVectorRegressor(self):
"""Test the Support Vector Regressor"""
params = dict({'quiet': ''})
regressor = SupportVectorRegressor(len(self.fncs))
input_data = np.random.rand(self.input_vecs, self.input_length)
assert len(regressor.regresso... | the_stack_v2_python_sparse | pysandbox/minerva_test/regressor_test.py | yanatan16/minerva | train | 0 | |
cc1c2205217f75f37d71bda4f8d25b589c4b4e00 | [
"cur_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')\nprint('-------------------------------------------')\nprint('Start to test check ota update result', cur_time)\npath = judge_path()\nassert path",
"try:\n update_res = check_update_res_fumo()\n assert update_res\nexcept Exception as msg:\n ... | <|body_start_0|>
cur_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
print('-------------------------------------------')
print('Start to test check ota update result', cur_time)
path = judge_path()
assert path
<|end_body_0|>
<|body_start_1|>
try:
... | TestOtaSmokeClass | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all test cases"""
<|body_0|>
def test_check_update_result(self):
"""Usage: To verify the result after executing ota download and update action. Success Value: 90 or 100"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_020648 | 1,596 | permissive | [
{
"docstring": "Execute one time before run all test cases",
"name": "setup_class",
"signature": "def setup_class(self)"
},
{
"docstring": "Usage: To verify the result after executing ota download and update action. Success Value: 90 or 100",
"name": "test_check_update_result",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_014829 | Implement the Python class `TestOtaSmokeClass` described below.
Class description:
Implement the TestOtaSmokeClass class.
Method signatures and docstrings:
- def setup_class(self): Execute one time before run all test cases
- def test_check_update_result(self): Usage: To verify the result after executing ota download... | Implement the Python class `TestOtaSmokeClass` described below.
Class description:
Implement the TestOtaSmokeClass class.
Method signatures and docstrings:
- def setup_class(self): Execute one time before run all test cases
- def test_check_update_result(self): Usage: To verify the result after executing ota download... | e4afa8944785c1dc1dc80550073858d03a77d629 | <|skeleton|>
class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all test cases"""
<|body_0|>
def test_check_update_result(self):
"""Usage: To verify the result after executing ota download and update action. Success Value: 90 or 100"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all test cases"""
cur_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
print('-------------------------------------------')
print('Start to test check ota update result', cur_time)
path... | the_stack_v2_python_sparse | testcases/smoke/dongfeng/test_dongfeng_smoke/test_8check_update_result.py | uniquelover/ota_smoke_auto | train | 0 | |
3ee692616775e596d4aab8b84f2de73dd7f6369d | [
"self.init_config(app)\nif app.config['LOGGING_FS_LOGFILE'] is None:\n return\nself.install_handler(app)\napp.extensions['invenio-logging-fs'] = self",
"app.config.setdefault('LOGGING_FS_LEVEL', 'DEBUG' if app.debug else 'WARNING')\nfor k in dir(config):\n if k.startswith('LOGGING_FS'):\n app.config.... | <|body_start_0|>
self.init_config(app)
if app.config['LOGGING_FS_LOGFILE'] is None:
return
self.install_handler(app)
app.extensions['invenio-logging-fs'] = self
<|end_body_0|>
<|body_start_1|>
app.config.setdefault('LOGGING_FS_LEVEL', 'DEBUG' if app.debug else 'WARNI... | Invenio-Logging extension. Filesystem handler. | InvenioLoggingFS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvenioLoggingFS:
"""Invenio-Logging extension. Filesystem handler."""
def init_app(self, app):
"""Flask application initialization."""
<|body_0|>
def init_config(self, app):
"""Initialize config."""
<|body_1|>
def install_handler(self, app):
... | stack_v2_sparse_classes_36k_train_020649 | 3,344 | no_license | [
{
"docstring": "Flask application initialization.",
"name": "init_app",
"signature": "def init_app(self, app)"
},
{
"docstring": "Initialize config.",
"name": "init_config",
"signature": "def init_config(self, app)"
},
{
"docstring": "Install log handler on Flask application.",
... | 3 | stack_v2_sparse_classes_30k_train_010060 | Implement the Python class `InvenioLoggingFS` described below.
Class description:
Invenio-Logging extension. Filesystem handler.
Method signatures and docstrings:
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize config.
- def install_handler(self, app): Install log... | Implement the Python class `InvenioLoggingFS` described below.
Class description:
Invenio-Logging extension. Filesystem handler.
Method signatures and docstrings:
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize config.
- def install_handler(self, app): Install log... | 54eb34c7e1594cc50a5347ba93e12a991ba8b7f3 | <|skeleton|>
class InvenioLoggingFS:
"""Invenio-Logging extension. Filesystem handler."""
def init_app(self, app):
"""Flask application initialization."""
<|body_0|>
def init_config(self, app):
"""Initialize config."""
<|body_1|>
def install_handler(self, app):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InvenioLoggingFS:
"""Invenio-Logging extension. Filesystem handler."""
def init_app(self, app):
"""Flask application initialization."""
self.init_config(app)
if app.config['LOGGING_FS_LOGFILE'] is None:
return
self.install_handler(app)
app.extensions['i... | the_stack_v2_python_sparse | .virtualenvs/invenio/lib/python2.7/site-packages/invenio_logging/fs.py | N03/invenio | train | 0 |
67217bba10145e7e96089f3444cdf7d4ecf1451c | [
"from django.conf.urls import url\n\ndef wrap(view):\n\n def wrapper(*args, **kwargs):\n return self.admin_site.admin_view(view, cacheable=True)(*args, **kwargs)\n return update_wrapper(wrapper, view)\ninfo = self.get_model_info()\nurls = super(RMLModelReportMixin, self).get_urls()\nreport_url = [url('... | <|body_start_0|>
from django.conf.urls import url
def wrap(view):
def wrapper(*args, **kwargs):
return self.admin_site.admin_view(view, cacheable=True)(*args, **kwargs)
return update_wrapper(wrapper, view)
info = self.get_model_info()
urls = supe... | RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template | RMLModelReportMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RMLModelReportMixin:
"""RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template"""
def get_urls(self):
"""Get default django admin urls then add custom url for report link"""
<|body_0|>
def get_context_object_na... | stack_v2_sparse_classes_36k_train_020650 | 6,508 | no_license | [
{
"docstring": "Get default django admin urls then add custom url for report link",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Get the context name to used in template",
"name": "get_context_object_name",
"signature": "def get_context_object_name(self)"
},... | 6 | stack_v2_sparse_classes_30k_train_011390 | Implement the Python class `RMLModelReportMixin` described below.
Class description:
RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template
Method signatures and docstrings:
- def get_urls(self): Get default django admin urls then add custom url for report ... | Implement the Python class `RMLModelReportMixin` described below.
Class description:
RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template
Method signatures and docstrings:
- def get_urls(self): Get default django admin urls then add custom url for report ... | 0cf8fb1be8ac3c27304807ed7aac7eb0032c2cb6 | <|skeleton|>
class RMLModelReportMixin:
"""RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template"""
def get_urls(self):
"""Get default django admin urls then add custom url for report link"""
<|body_0|>
def get_context_object_na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RMLModelReportMixin:
"""RML Admin Mixin for django admin to Generate model object detail in pdf format report with ReportLab *.rml template"""
def get_urls(self):
"""Get default django admin urls then add custom url for report link"""
from django.conf.urls import url
def wrap(vie... | the_stack_v2_python_sparse | reporting/admin.py | andrewidya/littleerp | train | 1 |
f94f13bdc2496c726a5ec344fef0b2274ee8e13c | [
"self.NAME = EVITA\nself.tarsqidoc = tarsqidoc\nself.docelement = docelement\nself.doctree = None\nself.imported_events = imported_events",
"self.doctree = create_tarsqi_tree(self.tarsqidoc, self.docelement)\nfor sentence in self.doctree:\n logger.debug('SENTENCE: %s' % get_words_as_string(sentence))\n for ... | <|body_start_0|>
self.NAME = EVITA
self.tarsqidoc = tarsqidoc
self.docelement = docelement
self.doctree = None
self.imported_events = imported_events
<|end_body_0|>
<|body_start_1|>
self.doctree = create_tarsqi_tree(self.tarsqidoc, self.docelement)
for sentence i... | Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element and not for the whole document or string. | Evita | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Evita:
"""Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element and not for the whole document or string... | stack_v2_sparse_classes_36k_train_020651 | 1,998 | permissive | [
{
"docstring": "Set the NAME instance variable. The doctree variables is filled in during processing.",
"name": "__init__",
"signature": "def __init__(self, tarsqidoc, docelement, imported_events)"
},
{
"docstring": "Process the element slice of the TarsqiDocument. Loop through all sentences in ... | 2 | stack_v2_sparse_classes_30k_test_000988 | Implement the Python class `Evita` described below.
Class description:
Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element a... | Implement the Python class `Evita` described below.
Class description:
Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element a... | 085007047ab591426d5c08b123906c070deb6627 | <|skeleton|>
class Evita:
"""Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element and not for the whole document or string... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Evita:
"""Class that implements Evita's event recognizer. Instance variables contain the name of the component, the TarsqiDocument, a docelement Tag and a TarsqiTree instance. The TarsqiTree instance in the doctree variable is the tree for just one element and not for the whole document or string."""
def... | the_stack_v2_python_sparse | components/evita/main.py | tarsqi/ttk | train | 26 |
957b78e29cf69664f62a167ca39a226dfb80fadc | [
"self.M_min = -20\nself.M_max = -18\nself.a_min = -20\nself.a_max = 20\nself.b_min = -20\nself.b_max = 20\nif g_lim != None:\n self.g_min = g_lim[0]\n self.g_max = g_lim[1]",
"m = rng.rand()\nM = 1000.0 * rng.rand()\nM = dnest4.wrap(M, self.M_min, self.M_max)\na = 1000.0 * rng.rand()\na = dnest4.wrap(a, sel... | <|body_start_0|>
self.M_min = -20
self.M_max = -18
self.a_min = -20
self.a_max = 20
self.b_min = -20
self.b_max = 20
if g_lim != None:
self.g_min = g_lim[0]
self.g_max = g_lim[1]
<|end_body_0|>
<|body_start_1|>
m = rng.rand()
... | Specify the model in Python. | Model | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""Specify the model in Python."""
def __init__(self, g_lim=None):
"""Parameter values *are not* stored inside the class"""
<|body_0|>
def from_prior(self):
"""Unlike in C++, this must *return* a numpy array of parameters."""
<|body_1|>
def pe... | stack_v2_sparse_classes_36k_train_020652 | 13,227 | permissive | [
{
"docstring": "Parameter values *are not* stored inside the class",
"name": "__init__",
"signature": "def __init__(self, g_lim=None)"
},
{
"docstring": "Unlike in C++, this must *return* a numpy array of parameters.",
"name": "from_prior",
"signature": "def from_prior(self)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_009689 | Implement the Python class `Model` described below.
Class description:
Specify the model in Python.
Method signatures and docstrings:
- def __init__(self, g_lim=None): Parameter values *are not* stored inside the class
- def from_prior(self): Unlike in C++, this must *return* a numpy array of parameters.
- def pertur... | Implement the Python class `Model` described below.
Class description:
Specify the model in Python.
Method signatures and docstrings:
- def __init__(self, g_lim=None): Parameter values *are not* stored inside the class
- def from_prior(self): Unlike in C++, this must *return* a numpy array of parameters.
- def pertur... | c355d18021467cf92546cf2fc9cb1d1abe59b8d8 | <|skeleton|>
class Model:
"""Specify the model in Python."""
def __init__(self, g_lim=None):
"""Parameter values *are not* stored inside the class"""
<|body_0|>
def from_prior(self):
"""Unlike in C++, this must *return* a numpy array of parameters."""
<|body_1|>
def pe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
"""Specify the model in Python."""
def __init__(self, g_lim=None):
"""Parameter values *are not* stored inside the class"""
self.M_min = -20
self.M_max = -18
self.a_min = -20
self.a_max = 20
self.b_min = -20
self.b_max = 20
if g_lim !... | the_stack_v2_python_sparse | zprev versions/Models_py_backup/Models backup/Bfactor.py | lefthandedroo/Cosmodels | train | 1 |
ee9e8d4f83795b0bf19f75559f1cde6a102998f8 | [
"self.msg_type = msg_type\nself.result = result\nself.args = args\nself.kwargs = kwargs",
"msg = cls(CC3DPyGraphicsFrameConnectionMsgType.REQUESTING, None, *args, **kwargs)\nconn.send(msg)\nif return_result:\n msg = conn.recv()\n if not isinstance(msg, CC3DPyGraphicsFrameConnectionMsg):\n raise Runti... | <|body_start_0|>
self.msg_type = msg_type
self.result = result
self.args = args
self.kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
msg = cls(CC3DPyGraphicsFrameConnectionMsgType.REQUESTING, None, *args, **kwargs)
conn.send(msg)
if return_result:
msg... | Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, with positional and keyword arguments as specified in the call to :meth:`request`. | CC3DPyGraphicsFrameConnectionMsg | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CC3DPyGraphicsFrameConnectionMsg:
"""Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, with positional and keyword arguments a... | stack_v2_sparse_classes_36k_train_020653 | 14,357 | no_license | [
{
"docstring": ":param msg_type: message type :type msg_type: CC3DPyGraphicsFrameConnectionMsgType :param result: message result :type result: Any :param args: message arguments :param kwargs: message keyword arguments",
"name": "__init__",
"signature": "def __init__(self, msg_type: CC3DPyGraphicsFrameC... | 3 | null | Implement the Python class `CC3DPyGraphicsFrameConnectionMsg` described below.
Class description:
Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, ... | Implement the Python class `CC3DPyGraphicsFrameConnectionMsg` described below.
Class description:
Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, ... | 65a65eaa693a6d2b3aab303f9b41e71819f4eed4 | <|skeleton|>
class CC3DPyGraphicsFrameConnectionMsg:
"""Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, with positional and keyword arguments a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CC3DPyGraphicsFrameConnectionMsg:
"""Basic message container for message passing between a client processes and a rendering process running a graphics frame. The class attribute :attr:`method` is called on the object connected on the other side of the pipe, with positional and keyword arguments as specified i... | the_stack_v2_python_sparse | cc3d/core/GraphicsUtils/CC3DPyGraphicsFrameIO.py | CompuCell3D/CompuCell3D | train | 51 |
1ff9e23224657f47a46d9c937cc14f53cf30ac26 | [
"res = 0\nfor i in range(len(heights)):\n mh = heights[i]\n res = max(res, heights[i])\n for j in range(i + 1, len(heights)):\n mh = min(mh, heights[j])\n res = max(res, mh * (j - i + 1))\nreturn res",
"def dfs(l, r):\n if l > r:\n return 0\n if l == r:\n return heights[... | <|body_start_0|>
res = 0
for i in range(len(heights)):
mh = heights[i]
res = max(res, heights[i])
for j in range(i + 1, len(heights)):
mh = min(mh, heights[j])
res = max(res, mh * (j - i + 1))
return res
<|end_body_0|>
<|body_s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largest_rectangle_in_histogram(self, heights: List[int]) -> int:
"""Bruteforce T: O(N2) S: O(1)"""
<|body_0|>
def largest_rectangle_in_histogram(self, heights: List[int]) -> int:
"""Divide and conquer T: O(NlogN) average case, O(N2) worst case (sorted) ... | stack_v2_sparse_classes_36k_train_020654 | 2,351 | no_license | [
{
"docstring": "Bruteforce T: O(N2) S: O(1)",
"name": "largest_rectangle_in_histogram",
"signature": "def largest_rectangle_in_histogram(self, heights: List[int]) -> int"
},
{
"docstring": "Divide and conquer T: O(NlogN) average case, O(N2) worst case (sorted) S: O(N) stack space",
"name": "... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largest_rectangle_in_histogram(self, heights: List[int]) -> int: Bruteforce T: O(N2) S: O(1)
- def largest_rectangle_in_histogram(self, heights: List[int]) -> int: Divide and... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largest_rectangle_in_histogram(self, heights: List[int]) -> int: Bruteforce T: O(N2) S: O(1)
- def largest_rectangle_in_histogram(self, heights: List[int]) -> int: Divide and... | 9882fdc58a24d852ebf9ee85bc10883454bd76a7 | <|skeleton|>
class Solution:
def largest_rectangle_in_histogram(self, heights: List[int]) -> int:
"""Bruteforce T: O(N2) S: O(1)"""
<|body_0|>
def largest_rectangle_in_histogram(self, heights: List[int]) -> int:
"""Divide and conquer T: O(NlogN) average case, O(N2) worst case (sorted) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largest_rectangle_in_histogram(self, heights: List[int]) -> int:
"""Bruteforce T: O(N2) S: O(1)"""
res = 0
for i in range(len(heights)):
mh = heights[i]
res = max(res, heights[i])
for j in range(i + 1, len(heights)):
mh ... | the_stack_v2_python_sparse | python/dp/optimization/largest_rectangle_in_histogram.py | pondycrane/algorithms | train | 0 | |
0454283d33cae7fb384f8ea432ca3f005e621e7a | [
"if not head:\n return\nif not head.next:\n return head\ncurrent = head\nwhile current and current.next:\n next = current.next\n if current.val == next.val:\n current.next = next.next\n else:\n current = current.next\nreturn head",
"if not head:\n return\nif not head.next:\n ret... | <|body_start_0|>
if not head:
return
if not head.next:
return head
current = head
while current and current.next:
next = current.next
if current.val == next.val:
current.next = next.next
else:
cur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def deleteDuplicates1(self, head):
"""82. Remove Duplicates from Sorted List II Given a sorted linked list, delete all nodes that have duplicate numbers, leaving only d... | stack_v2_sparse_classes_36k_train_020655 | 1,622 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "deleteDuplicates",
"signature": "def deleteDuplicates(self, head)"
},
{
"docstring": "82. Remove Duplicates from Sorted List II Given a sorted linked list, delete all nodes that have duplicate numbers, leaving only distinct numbers... | 2 | stack_v2_sparse_classes_30k_train_003641 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head): :type head: ListNode :rtype: ListNode
- def deleteDuplicates1(self, head): 82. Remove Duplicates from Sorted List II Given a sorted linked list,... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head): :type head: ListNode :rtype: ListNode
- def deleteDuplicates1(self, head): 82. Remove Duplicates from Sorted List II Given a sorted linked list,... | 11ad9d3841de09c0b4dc3a667e7e63c3558656a5 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def deleteDuplicates1(self, head):
"""82. Remove Duplicates from Sorted List II Given a sorted linked list, delete all nodes that have duplicate numbers, leaving only d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
if not head:
return
if not head.next:
return head
current = head
while current and current.next:
next = current.next
if current.val ==... | the_stack_v2_python_sparse | remove_duplicate_from_linklist.py | ganlanshu/leetcode | train | 0 | |
42e73af0a8a0595994a59e3400f84348ec0959e1 | [
"try:\n medication: models.Medication = models.Medication.create_from_json(data=request.data, patient_profile=request.user.patient_profile)\nexcept custom_exceptions.DataNotProvided as e:\n return response.Response(data=e.get_response_format(), status=status.HTTP_400_BAD_REQUEST)\nserialized_medication = seri... | <|body_start_0|>
try:
medication: models.Medication = models.Medication.create_from_json(data=request.data, patient_profile=request.user.patient_profile)
except custom_exceptions.DataNotProvided as e:
return response.Response(data=e.get_response_format(), status=status.HTTP_400_B... | Endpoints for Medication objects. | MedicationsEndpoint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedicationsEndpoint:
"""Endpoints for Medication objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new medication for the user."""
<|body_0|>
def put(self, request: Request) -> response.Response:
"""Updates an existing medication."""
... | stack_v2_sparse_classes_36k_train_020656 | 14,860 | no_license | [
{
"docstring": "Adds a new medication for the user.",
"name": "post",
"signature": "def post(self, request: Request) -> response.Response"
},
{
"docstring": "Updates an existing medication.",
"name": "put",
"signature": "def put(self, request: Request) -> response.Response"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_014989 | Implement the Python class `MedicationsEndpoint` described below.
Class description:
Endpoints for Medication objects.
Method signatures and docstrings:
- def post(self, request: Request) -> response.Response: Adds a new medication for the user.
- def put(self, request: Request) -> response.Response: Updates an exist... | Implement the Python class `MedicationsEndpoint` described below.
Class description:
Endpoints for Medication objects.
Method signatures and docstrings:
- def post(self, request: Request) -> response.Response: Adds a new medication for the user.
- def put(self, request: Request) -> response.Response: Updates an exist... | b6d757895132b9b3c8c6682c11efadf993d5905b | <|skeleton|>
class MedicationsEndpoint:
"""Endpoints for Medication objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new medication for the user."""
<|body_0|>
def put(self, request: Request) -> response.Response:
"""Updates an existing medication."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedicationsEndpoint:
"""Endpoints for Medication objects."""
def post(self, request: Request) -> response.Response:
"""Adds a new medication for the user."""
try:
medication: models.Medication = models.Medication.create_from_json(data=request.data, patient_profile=request.user... | the_stack_v2_python_sparse | main/model_api.py | kalolad1/cosmos | train | 0 |
041bde86e8c4db19fffd4293b9e8132d958d7768 | [
"try:\n code, resp = get_order_detail(request, sn)\n if code == RespCode.Succeed.value:\n return Response(resp)\n else:\n return error_resp(code, resp)\nexcept Exception as e:\n print(e)\n return error_resp(RespCode.Exception.value, _('Server exception, please try again'))",
"try:\n ... | <|body_start_0|>
try:
code, resp = get_order_detail(request, sn)
if code == RespCode.Succeed.value:
return Response(resp)
else:
return error_resp(code, resp)
except Exception as e:
print(e)
return error_resp(Resp... | OrderDetailView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderDetailView:
def get(self, request, sn):
"""订单支付页面"""
<|body_0|>
def delete(self, request, sn):
"""订单删除(逻辑删除)"""
<|body_1|>
def put(self, request, sn):
"""取消订单"""
<|body_2|>
def post(self, request, sn):
"""立即支付"""
... | stack_v2_sparse_classes_36k_train_020657 | 4,027 | no_license | [
{
"docstring": "订单支付页面",
"name": "get",
"signature": "def get(self, request, sn)"
},
{
"docstring": "订单删除(逻辑删除)",
"name": "delete",
"signature": "def delete(self, request, sn)"
},
{
"docstring": "取消订单",
"name": "put",
"signature": "def put(self, request, sn)"
},
{
... | 4 | stack_v2_sparse_classes_30k_test_000180 | Implement the Python class `OrderDetailView` described below.
Class description:
Implement the OrderDetailView class.
Method signatures and docstrings:
- def get(self, request, sn): 订单支付页面
- def delete(self, request, sn): 订单删除(逻辑删除)
- def put(self, request, sn): 取消订单
- def post(self, request, sn): 立即支付 | Implement the Python class `OrderDetailView` described below.
Class description:
Implement the OrderDetailView class.
Method signatures and docstrings:
- def get(self, request, sn): 订单支付页面
- def delete(self, request, sn): 订单删除(逻辑删除)
- def put(self, request, sn): 取消订单
- def post(self, request, sn): 立即支付
<|skeleton|>
... | 14c94075094e1657b90b0bb3f94544d008255f45 | <|skeleton|>
class OrderDetailView:
def get(self, request, sn):
"""订单支付页面"""
<|body_0|>
def delete(self, request, sn):
"""订单删除(逻辑删除)"""
<|body_1|>
def put(self, request, sn):
"""取消订单"""
<|body_2|>
def post(self, request, sn):
"""立即支付"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderDetailView:
def get(self, request, sn):
"""订单支付页面"""
try:
code, resp = get_order_detail(request, sn)
if code == RespCode.Succeed.value:
return Response(resp)
else:
return error_resp(code, resp)
except Exception as... | the_stack_v2_python_sparse | order/views.py | Tsurol/trip-server | train | 1 | |
295047fc94bc33bb6ef83c5a907a8d8daefc7077 | [
"res = []\nnums1.sort()\nnums2.sort()\ni, j = (0, 0)\nwhile i < len(nums1) and j < len(nums2):\n if nums1[i] < nums2[j]:\n i += 1\n elif nums1[i] > nums2[j]:\n j += 1\n else:\n res.append(nums1[i])\n i += 1\n j += 1\nreturn res",
"s, res = (set(), [])\nfor ele in nums1:... | <|body_start_0|>
res = []
nums1.sort()
nums2.sort()
i, j = (0, 0)
while i < len(nums1) and j < len(nums2):
if nums1[i] < nums2[j]:
i += 1
elif nums1[i] > nums2[j]:
j += 1
else:
res.append(nums1[i]... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersection(self, nums1: List[int], nums2: List[int]) -> int:
"""求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集"""
<|body_0|>
def intersection2(self, nums1: List[int], nums2: List[int]) -> List[int]:
"""两个数组求交集 Args: nums1: 数组1 nums2: 数组2 Returns... | stack_v2_sparse_classes_36k_train_020658 | 2,414 | permissive | [
{
"docstring": "求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集",
"name": "intersection",
"signature": "def intersection(self, nums1: List[int], nums2: List[int]) -> int"
},
{
"docstring": "两个数组求交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组交集",
"name": "intersection2",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_003099 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersection(self, nums1: List[int], nums2: List[int]) -> int: 求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集
- def intersection2(self, nums1: List[int], nums2: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersection(self, nums1: List[int], nums2: List[int]) -> int: 求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集
- def intersection2(self, nums1: List[int], nums2: List[in... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def intersection(self, nums1: List[int], nums2: List[int]) -> int:
"""求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集"""
<|body_0|>
def intersection2(self, nums1: List[int], nums2: List[int]) -> List[int]:
"""两个数组求交集 Args: nums1: 数组1 nums2: 数组2 Returns... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intersection(self, nums1: List[int], nums2: List[int]) -> int:
"""求出两个数组的交集 Args: nums1: 数组1 nums2: 数组2 Returns: 数组的交集"""
res = []
nums1.sort()
nums2.sort()
i, j = (0, 0)
while i < len(nums1) and j < len(nums2):
if nums1[i] < nums2[j]:
... | the_stack_v2_python_sparse | src/leetcodepython/array/intersection_two_array_349.py | zhangyu345293721/leetcode | train | 101 | |
f070749868f5ba2b7c0382cc2c8c12088889f72d | [
"super().__init__(model=acq_function.model)\nself.acq_func = acq_function\nself.prior_module = prior_module\nself._log = log\nself._prior_exponent = prior_exponent\nself._is_sample_reducing_af = isinstance(acq_function, SampleReducingMCAcquisitionFunction)\nself.set_X_pending(X_pending=X_pending)",
"prior = self.... | <|body_start_0|>
super().__init__(model=acq_function.model)
self.acq_func = acq_function
self.prior_module = prior_module
self._log = log
self._prior_exponent = prior_exponent
self._is_sample_reducing_af = isinstance(acq_function, SampleReducingMCAcquisitionFunction)
... | Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details. | PriorGuidedAcquisitionFunction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PriorGuidedAcquisitionFunction:
"""Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details."""
def __init__(self, acq_function: AcquisitionFunction, prior_module: Mod... | stack_v2_sparse_classes_36k_train_020659 | 3,750 | permissive | [
{
"docstring": "Initialize the prior-guided acquisition function. Args: acq_function: The base acquisition function. prior_module: A Module that computes the probability (or log probability) for the provided inputs. `prior_module.forward` should take a `batch_shape x q`-dim tensor of inputs and return a `batch_... | 2 | stack_v2_sparse_classes_30k_train_004136 | Implement the Python class `PriorGuidedAcquisitionFunction` described below.
Class description:
Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details.
Method signatures and docstrings:
- def... | Implement the Python class `PriorGuidedAcquisitionFunction` described below.
Class description:
Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details.
Method signatures and docstrings:
- def... | 4cc5ed59b2e8a9c780f786830c548e05cc74d53c | <|skeleton|>
class PriorGuidedAcquisitionFunction:
"""Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details."""
def __init__(self, acq_function: AcquisitionFunction, prior_module: Mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PriorGuidedAcquisitionFunction:
"""Class for weighting acquisition functions by a prior distribution. Supports MC and batch acquisition functions via SampleReducingAcquisitionFunction. See [Hvarfner2022]_ for details."""
def __init__(self, acq_function: AcquisitionFunction, prior_module: Module, log: boo... | the_stack_v2_python_sparse | botorch/acquisition/prior_guided.py | pytorch/botorch | train | 2,891 |
639e2df453845137d4f08f8788514c4bbd16fe2e | [
"uri = '%s/sms/send' % self.uri_prefix\npost_body = {'phone': phone, 'sms': message}\npost_body = json.dumps(post_body)\nresp, body = self.post(uri, post_body)\nself.expected_success(201, resp.status)\nbody = json.loads(body)\nreturn service_client.ResponseBody(resp, body)",
"uri = '%s/sms/config' % self.uri_pref... | <|body_start_0|>
uri = '%s/sms/send' % self.uri_prefix
post_body = {'phone': phone, 'sms': message}
post_body = json.dumps(post_body)
resp, body = self.post(uri, post_body)
self.expected_success(201, resp.status)
body = json.loads(body)
return service_client.Respo... | SfNotifySmsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SfNotifySmsClient:
def sms_create(self, phone, message):
"""create sms :param phone(required): The phone number to send :param message(required): Content of short message"""
<|body_0|>
def sms_config_set(self, cfg, **kwargs):
"""update config ini file :param cfg: dic... | stack_v2_sparse_classes_36k_train_020660 | 2,272 | permissive | [
{
"docstring": "create sms :param phone(required): The phone number to send :param message(required): Content of short message",
"name": "sms_create",
"signature": "def sms_create(self, phone, message)"
},
{
"docstring": "update config ini file :param cfg: dict of config like this: {section:{opt... | 3 | stack_v2_sparse_classes_30k_train_017803 | Implement the Python class `SfNotifySmsClient` described below.
Class description:
Implement the SfNotifySmsClient class.
Method signatures and docstrings:
- def sms_create(self, phone, message): create sms :param phone(required): The phone number to send :param message(required): Content of short message
- def sms_c... | Implement the Python class `SfNotifySmsClient` described below.
Class description:
Implement the SfNotifySmsClient class.
Method signatures and docstrings:
- def sms_create(self, phone, message): create sms :param phone(required): The phone number to send :param message(required): Content of short message
- def sms_c... | 1ccdab06d5800572ee0fc569c87d56332efe1538 | <|skeleton|>
class SfNotifySmsClient:
def sms_create(self, phone, message):
"""create sms :param phone(required): The phone number to send :param message(required): Content of short message"""
<|body_0|>
def sms_config_set(self, cfg, **kwargs):
"""update config ini file :param cfg: dic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SfNotifySmsClient:
def sms_create(self, phone, message):
"""create sms :param phone(required): The phone number to send :param message(required): Content of short message"""
uri = '%s/sms/send' % self.uri_prefix
post_body = {'phone': phone, 'sms': message}
post_body = json.dump... | the_stack_v2_python_sparse | yibo/tempest/tempest/services/sf_notify/json/sf_notify_sms_client.py | laoyigrace/files | train | 0 | |
9003dd21cb8c403c2aa2935edf6a750781ac3ed4 | [
"first = None\nheapq.heapify(letters)\nwhile len(letters) != 0:\n source = heapq.heappop(letters)\n if source > target:\n return source\n if first is None:\n first = source\nreturn first",
"for letter in letters:\n if letter > target:\n return letter\nreturn letters[0]"
] | <|body_start_0|>
first = None
heapq.heapify(letters)
while len(letters) != 0:
source = heapq.heappop(letters)
if source > target:
return source
if first is None:
first = source
return first
<|end_body_0|>
<|body_start_1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreatestLetter(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter1(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_020661 | 3,138 | no_license | [
{
"docstring": ":type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter",
"signature": "def nextGreatestLetter(self, letters, target)"
},
{
"docstring": ":type letters: List[str] :type target: str :rtype: str",
"name": "nextGreatestLetter1",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_000832 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter(self, letters, target): :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter1(self, letters, target): :type letters: List[str] :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreatestLetter(self, letters, target): :type letters: List[str] :type target: str :rtype: str
- def nextGreatestLetter1(self, letters, target): :type letters: List[str] :... | 233d12deca34f51c3bb0406831cc07f3b72b50cf | <|skeleton|>
class Solution:
def nextGreatestLetter(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_0|>
def nextGreatestLetter1(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def nextGreatestLetter(self, letters, target):
""":type letters: List[str] :type target: str :rtype: str"""
first = None
heapq.heapify(letters)
while len(letters) != 0:
source = heapq.heappop(letters)
if source > target:
return ... | the_stack_v2_python_sparse | Python/Find Smallest Letter Greater Than Target/main.py | briansu2004/MyLeet | train | 1 | |
15a5c96388208cf62f15be574b615a6971609528 | [
"py_typecheck.check_callable(executor_stack_fn)\nself._executor_stack_fn = executor_stack_fn\nself._executors = cachetools.LRUCache(_EXECUTOR_CACHE_SIZE)\nif ensure_closed is None:\n ensure_closed = ()\nself._ensure_closed = ensure_closed",
"py_typecheck.check_type(cardinalities, dict)\nkey = _get_hashable_key... | <|body_start_0|>
py_typecheck.check_callable(executor_stack_fn)
self._executor_stack_fn = executor_stack_fn
self._executors = cachetools.LRUCache(_EXECUTOR_CACHE_SIZE)
if ensure_closed is None:
ensure_closed = ()
self._ensure_closed = ensure_closed
<|end_body_0|>
<|b... | Implementation of executor factory holding an executor per cardinality. | ResourceManagingExecutorFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceManagingExecutorFactory:
"""Implementation of executor factory holding an executor per cardinality."""
def __init__(self, executor_stack_fn: Callable[[executor_factory.CardinalitiesType], executor_base.Executor], ensure_closed: Optional[Sequence[executor_base.Executor]]=None):
... | stack_v2_sparse_classes_36k_train_020662 | 43,780 | permissive | [
{
"docstring": "Initializes `ResourceManagingExecutorFactory`. `ResourceManagingExecutorFactory` manages a mapping from `cardinalities` to `executor_base.Executors`, closing and destroying the executors in this mapping when asked. Args: executor_stack_fn: Callable taking a mapping from `placements.PlacementLite... | 3 | stack_v2_sparse_classes_30k_train_013976 | Implement the Python class `ResourceManagingExecutorFactory` described below.
Class description:
Implementation of executor factory holding an executor per cardinality.
Method signatures and docstrings:
- def __init__(self, executor_stack_fn: Callable[[executor_factory.CardinalitiesType], executor_base.Executor], ens... | Implement the Python class `ResourceManagingExecutorFactory` described below.
Class description:
Implementation of executor factory holding an executor per cardinality.
Method signatures and docstrings:
- def __init__(self, executor_stack_fn: Callable[[executor_factory.CardinalitiesType], executor_base.Executor], ens... | 9c08381a172a26957d7c50f74214c74fe9a9fb1c | <|skeleton|>
class ResourceManagingExecutorFactory:
"""Implementation of executor factory holding an executor per cardinality."""
def __init__(self, executor_stack_fn: Callable[[executor_factory.CardinalitiesType], executor_base.Executor], ensure_closed: Optional[Sequence[executor_base.Executor]]=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResourceManagingExecutorFactory:
"""Implementation of executor factory holding an executor per cardinality."""
def __init__(self, executor_stack_fn: Callable[[executor_factory.CardinalitiesType], executor_base.Executor], ensure_closed: Optional[Sequence[executor_base.Executor]]=None):
"""Initiali... | the_stack_v2_python_sparse | tensorflow_federated/python/core/impl/executors/executor_stacks.py | Saiprasad16/federated | train | 1 |
837865c2e0b9c7e69d141b4a30ee76ca7ebf023d | [
"self.total_records = total_records\nself.total_pages = total_pages\nself.page_number = page_number\nself.number_of_records_per_page = number_of_records_per_page\nself.applications = applications\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\ntotal_records = dictio... | <|body_start_0|>
self.total_records = total_records
self.total_pages = total_pages
self.page_number = page_number
self.number_of_records_per_page = number_of_records_per_page
self.applications = applications
self.additional_properties = additional_properties
<|end_body_0|... | Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attributes: total_records (long|int): Total number of applications in query total_page... | AppStatuses | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppStatuses:
"""Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attributes: total_records (long|int): Total num... | stack_v2_sparse_classes_36k_train_020663 | 3,503 | permissive | [
{
"docstring": "Constructor for the AppStatuses class",
"name": "__init__",
"signature": "def __init__(self, total_records=None, total_pages=None, page_number=None, number_of_records_per_page=None, applications=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model... | 2 | stack_v2_sparse_classes_30k_train_011974 | Implement the Python class `AppStatuses` described below.
Class description:
Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attribut... | Implement the Python class `AppStatuses` described below.
Class description:
Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attribut... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class AppStatuses:
"""Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attributes: total_records (long|int): Total num... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AppStatuses:
"""Implementation of the 'App Statuses' model. The response for the Get App Registration Status endpoint which returns an array of App Status objects to be able to determine their registration status. This is version 2 of this response. Attributes: total_records (long|int): Total number of applic... | the_stack_v2_python_sparse | finicityapi/models/app_statuses.py | monarchmoney/finicity-python | train | 0 |
59087b571033dc1da1a770c0396ae6bd5bbcb9b6 | [
"size = len(prices)\nif size <= 0:\n return 0\nmemo = [-1] * size\n\ndef dp(start):\n if start >= size:\n return 0\n if memo[start] != -1:\n return memo[start]\n minIdx = start\n maxPro = 0\n for i in range(start + 1, size):\n if prices[i] < prices[minIdx]:\n minIdx... | <|body_start_0|>
size = len(prices)
if size <= 0:
return 0
memo = [-1] * size
def dp(start):
if start >= size:
return 0
if memo[start] != -1:
return memo[start]
minIdx = start
maxPro = 0
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int], fee: int) -> int:
"""暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee"""
<|body_0|>
def maxProfit_dp(self, prices: List[int], fee: int) -> int:
"""动态规划：三个操作状态buy, sell, rest。 通用状态转移方程：s[0,1]两种(有无股票)状态的两种情况，昨天的股票持有状态和今天的操作影响今天的收益情... | stack_v2_sparse_classes_36k_train_020664 | 4,570 | permissive | [
{
"docstring": "暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: List[int], fee: int) -> int"
},
{
"docstring": "动态规划：三个操作状态buy, sell, rest。 通用状态转移方程：s[0,1]两种(有无股票)状态的两种情况，昨天的股票持有状态和今天的操作影响今天的收益情况 dp[i][k][0] = max(dp[i - 1][k][0], dp[i - 1][... | 3 | stack_v2_sparse_classes_30k_train_002068 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int], fee: int) -> int: 暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee
- def maxProfit_dp(self, prices: List[int], fee: int) -> int: 动态规划：三个操作状态buy, sell,... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int], fee: int) -> int: 暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee
- def maxProfit_dp(self, prices: List[int], fee: int) -> int: 动态规划：三个操作状态buy, sell,... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int], fee: int) -> int:
"""暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee"""
<|body_0|>
def maxProfit_dp(self, prices: List[int], fee: int) -> int:
"""动态规划：三个操作状态buy, sell, rest。 通用状态转移方程：s[0,1]两种(有无股票)状态的两种情况，昨天的股票持有状态和今天的操作影响今天的收益情... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int], fee: int) -> int:
"""暴力优化2：消除一层循环+备忘录，超时，区分题122，含手续费 - fee"""
size = len(prices)
if size <= 0:
return 0
memo = [-1] * size
def dp(start):
if start >= size:
return 0
if ... | the_stack_v2_python_sparse | 714-best-time-to-buy-and-sell-stock-with-transaction-fee.py | yuenliou/leetcode | train | 0 | |
7f633def5a460ca1040268cd047a402b363c383c | [
"super(AdamWeightDecayOptimizer, self).__init__(False, name)\nself.learning_rate = learning_rate\nself.weight_decay_rate = weight_decay_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.exclude_from_weight_decay = exclude_from_weight_decay\nself.beta_1_t = 1.0\nself.beta_2_t = 1.0",
"... | <|body_start_0|>
super(AdamWeightDecayOptimizer, self).__init__(False, name)
self.learning_rate = learning_rate
self.weight_decay_rate = weight_decay_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.exclude_from_weight_decay = exclude_fro... | 包含修正L2正则化（权重衰减）的Adam优化器 | AdamWeightDecayOptimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""包含修正L2正则化（权重衰减）的Adam优化器"""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""创建一个Adam权重衰减优化器 :param learning_rate: float，学习率 :param weight... | stack_v2_sparse_classes_36k_train_020665 | 10,671 | no_license | [
{
"docstring": "创建一个Adam权重衰减优化器 :param learning_rate: float，学习率 :param weight_decay_rate: float，权重衰减比率 :param beta_1: float， 默认0.9，梯度一阶矩估计用的参数 :param beta_2: float， 默认0.999，梯度二阶矩估计用的参数 :param epsilon: float，防止程序计算除0 :param exclude_from_weight_decay: list，不需要L2正则化（权重衰减）的参数名称 :param name: str，优化器名称",
"name": ... | 5 | stack_v2_sparse_classes_30k_train_021094 | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
包含修正L2正则化（权重衰减）的Adam优化器
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'): 创建一个... | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
包含修正L2正则化（权重衰减）的Adam优化器
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'): 创建一个... | e41b10ee42eb435e665abde4c62d13f5f3c10c5c | <|skeleton|>
class AdamWeightDecayOptimizer:
"""包含修正L2正则化（权重衰减）的Adam优化器"""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""创建一个Adam权重衰减优化器 :param learning_rate: float，学习率 :param weight... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdamWeightDecayOptimizer:
"""包含修正L2正则化（权重衰减）的Adam优化器"""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""创建一个Adam权重衰减优化器 :param learning_rate: float，学习率 :param weight_decay_rate: ... | the_stack_v2_python_sparse | read_source/bert/optimization.py | 43reyerhrstj/nlp_store | train | 0 |
de0cfb2150dc0563751f7726ed24a8eb69e804f7 | [
"self.language = language\nself.available_languages = ['akkadian', 'arabic', 'french', 'greek', 'latin', 'old_norse', 'middle_english', 'middle_high_german']\nassert self.language in self.available_languages, \"Specific tokenizer not available for '{0}'. Only available for: '{1}'.\".format(self.language, self.avail... | <|body_start_0|>
self.language = language
self.available_languages = ['akkadian', 'arabic', 'french', 'greek', 'latin', 'old_norse', 'middle_english', 'middle_high_german']
assert self.language in self.available_languages, "Specific tokenizer not available for '{0}'. Only available for: '{1}'.".... | Tokenize according to rules specific to a given language. | WordTokenizer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordTokenizer:
"""Tokenize according to rules specific to a given language."""
def __init__(self, language):
"""Take language as argument to the class. Check availability and setup class variables."""
<|body_0|>
def tokenize(self, string):
"""Tokenize incoming st... | stack_v2_sparse_classes_36k_train_020666 | 16,196 | permissive | [
{
"docstring": "Take language as argument to the class. Check availability and setup class variables.",
"name": "__init__",
"signature": "def __init__(self, language)"
},
{
"docstring": "Tokenize incoming string.",
"name": "tokenize",
"signature": "def tokenize(self, string)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_017008 | Implement the Python class `WordTokenizer` described below.
Class description:
Tokenize according to rules specific to a given language.
Method signatures and docstrings:
- def __init__(self, language): Take language as argument to the class. Check availability and setup class variables.
- def tokenize(self, string):... | Implement the Python class `WordTokenizer` described below.
Class description:
Tokenize according to rules specific to a given language.
Method signatures and docstrings:
- def __init__(self, language): Take language as argument to the class. Check availability and setup class variables.
- def tokenize(self, string):... | 085420eaed7055fbcb311714eebb67861fd1b241 | <|skeleton|>
class WordTokenizer:
"""Tokenize according to rules specific to a given language."""
def __init__(self, language):
"""Take language as argument to the class. Check availability and setup class variables."""
<|body_0|>
def tokenize(self, string):
"""Tokenize incoming st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordTokenizer:
"""Tokenize according to rules specific to a given language."""
def __init__(self, language):
"""Take language as argument to the class. Check availability and setup class variables."""
self.language = language
self.available_languages = ['akkadian', 'arabic', 'fren... | the_stack_v2_python_sparse | cltk/tokenize/word.py | jerryfrancis-97/cltk | train | 1 |
942a1b7180ca41a8a3f2996b4b7f16f2f4ff2ae7 | [
"patient_id = data['patient_id']\npatient = Patient(data['patient'])\nanamnesis = Anamnesis(data['anamnesis'])\nrecord = Record(patient_id, patient, anamnesis)\nfilename = '{}.json'.format(str(random.randint(10000, 99999)))\nfilepath = os.path.join(os.getcwd(), self.DEFAULT_PATH_TO_PENDING_BLOCK, filename)\nwith op... | <|body_start_0|>
patient_id = data['patient_id']
patient = Patient(data['patient'])
anamnesis = Anamnesis(data['anamnesis'])
record = Record(patient_id, patient, anamnesis)
filename = '{}.json'.format(str(random.randint(10000, 99999)))
filepath = os.path.join(os.getcwd(),... | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
<|body_0|>
def get(self, id):
"""Mengambil data berdasarkan ID yang ada"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_020667 | 1,571 | no_license | [
{
"docstring": "Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis",
"name": "add",
"signature": "def add(self, data)"
},
{
"docstring": "Mengambil data berdasarkan ID yang ada",
"name": "get",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_021264 | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def add(self, data): Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis
- def get(self, id): M... | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def add(self, data): Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis
- def get(self, id): M... | 8e55e77f6a89e0e4fef60da38c318fcf97b551a3 | <|skeleton|>
class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
<|body_0|>
def get(self, id):
"""Mengambil data berdasarkan ID yang ada"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
def add(self, data):
"""Data akan ditambahkan ke folder pending sebelum dibuat menjadi satu blok utuh Data terdiri dari 2 class yaitu : Patient, Anamnesis"""
patient_id = data['patient_id']
patient = Patient(data['patient'])
anamnesis = Anamnesis(data['anamnesis'])
... | the_stack_v2_python_sparse | Distributed/Puskesmas Manado/Data/components/Controller.py | chlengkey/medchain-peer | train | 0 | |
c40dcb3ebbac21ef940d239897b0c12bd2374741 | [
"self.vault_id = vault_id\nself.vault_name = vault_name\nself.vault_type = vault_type",
"if dictionary is None:\n return None\nvault_id = dictionary.get('vaultId')\nvault_name = dictionary.get('vaultName')\nvault_type = dictionary.get('vaultType')\nreturn cls(vault_id, vault_name, vault_type)"
] | <|body_start_0|>
self.vault_id = vault_id
self.vault_name = vault_name
self.vault_type = vault_type
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
vault_id = dictionary.get('vaultId')
vault_name = dictionary.get('vaultName')
vault_... | Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster. vault_name (string): Name of the Archival Vault. vault_type (VaultTypeArchivalExternalT... | ArchivalExternalTarget | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArchivalExternalTarget:
"""Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster. vault_name (string): Name of the Arch... | stack_v2_sparse_classes_36k_train_020668 | 2,202 | permissive | [
{
"docstring": "Constructor for the ArchivalExternalTarget class",
"name": "__init__",
"signature": "def __init__(self, vault_id=None, vault_name=None, vault_type=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representat... | 2 | null | Implement the Python class `ArchivalExternalTarget` described below.
Class description:
Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster... | Implement the Python class `ArchivalExternalTarget` described below.
Class description:
Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ArchivalExternalTarget:
"""Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster. vault_name (string): Name of the Arch... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArchivalExternalTarget:
"""Implementation of the 'ArchivalExternalTarget' model. Specifies settings about the Archival External Target (such as Tape or AWS). Attributes: vault_id (long|int): Specifies the id of Archival Vault assigned by the Cohesity Cluster. vault_name (string): Name of the Archival Vault. v... | the_stack_v2_python_sparse | cohesity_management_sdk/models/archival_external_target.py | cohesity/management-sdk-python | train | 24 |
b6743954953cb860b6a18ac2f42bccfa79235d5e | [
"graph = [[] for _ in range(numCourses)]\nneigh = [[] for _ in range(numCourses)]\nfor c, p in prerequisites:\n graph[c].append(p)\n neigh[p].append(c)\nstack = [i for i in range(numCourses) if not graph[i]]\nres = []\nwhile stack:\n prerequisites = stack.pop()\n res.append(prerequisites)\n for cours... | <|body_start_0|>
graph = [[] for _ in range(numCourses)]
neigh = [[] for _ in range(numCourses)]
for c, p in prerequisites:
graph[c].append(p)
neigh[p].append(c)
stack = [i for i in range(numCourses) if not graph[i]]
res = []
while stack:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findOrder_dfs(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findOrder_bfs(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int... | stack_v2_sparse_classes_36k_train_020669 | 4,347 | no_license | [
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]",
"name": "findOrder_dfs",
"signature": "def findOrder_dfs(self, numCourses, prerequisites)"
},
{
"docstring": ":type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]",
"name": ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findOrder_dfs(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]
- def findOrder_bfs(self, numCourses, prerequisit... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findOrder_dfs(self, numCourses, prerequisites): :type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]
- def findOrder_bfs(self, numCourses, prerequisit... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def findOrder_dfs(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findOrder_bfs(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findOrder_dfs(self, numCourses, prerequisites):
""":type numCourses: int :type prerequisites: List[List[int]] :rtype: List[int]"""
graph = [[] for _ in range(numCourses)]
neigh = [[] for _ in range(numCourses)]
for c, p in prerequisites:
graph[c].appen... | the_stack_v2_python_sparse | 210_CourseSchedule2.py | jennyChing/leetCode | train | 2 | |
58597a932a7e6a3d5af23dfbb1cbe3f92ba2ce26 | [
"d = {}\ndfs(tree, None, d)\nreturn Graph(list(d.values()))",
"for node in graph.nodes:\n if node.val == val:\n targetNode = node\ndist = targetNode.distance = 0\nl = [targetNode]\ns = set()\nwhile len(l) > 0:\n node = l.pop()\n if node.val in s or len(node.neighbors) == 0:\n continue\n ... | <|body_start_0|>
d = {}
dfs(tree, None, d)
return Graph(list(d.values()))
<|end_body_0|>
<|body_start_1|>
for node in graph.nodes:
if node.val == val:
targetNode = node
dist = targetNode.distance = 0
l = [targetNode]
s = set()
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fromTreeToGraph(self, tree):
""":type tree: TreeNode :rtype: Graph"""
<|body_0|>
def updateDistance(self, graph, val):
""":type graph: Graph"""
<|body_1|>
def distanceK(self, root, target, K):
""":type root: TreeNode :type target: T... | stack_v2_sparse_classes_36k_train_020670 | 2,490 | no_license | [
{
"docstring": ":type tree: TreeNode :rtype: Graph",
"name": "fromTreeToGraph",
"signature": "def fromTreeToGraph(self, tree)"
},
{
"docstring": ":type graph: Graph",
"name": "updateDistance",
"signature": "def updateDistance(self, graph, val)"
},
{
"docstring": ":type root: Tree... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fromTreeToGraph(self, tree): :type tree: TreeNode :rtype: Graph
- def updateDistance(self, graph, val): :type graph: Graph
- def distanceK(self, root, target, K): :type root:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fromTreeToGraph(self, tree): :type tree: TreeNode :rtype: Graph
- def updateDistance(self, graph, val): :type graph: Graph
- def distanceK(self, root, target, K): :type root:... | f08b8a3f7de7a456a55573f3c4d8920a80f03a1a | <|skeleton|>
class Solution:
def fromTreeToGraph(self, tree):
""":type tree: TreeNode :rtype: Graph"""
<|body_0|>
def updateDistance(self, graph, val):
""":type graph: Graph"""
<|body_1|>
def distanceK(self, root, target, K):
""":type root: TreeNode :type target: T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fromTreeToGraph(self, tree):
""":type tree: TreeNode :rtype: Graph"""
d = {}
dfs(tree, None, d)
return Graph(list(d.values()))
def updateDistance(self, graph, val):
""":type graph: Graph"""
for node in graph.nodes:
if node.val == v... | the_stack_v2_python_sparse | py/863.py | pipi32167/LeetCode | train | 1 | |
cb1ffcc43c6c875cbff0bc4c1baf50283c85937a | [
"logging.info('=============测试血糖=============')\nl = SignsDataView(self.driver)\nself.assertTrue(l.login_health())\na = random.randint(1, 3)\nif a == 1:\n b = '餐前半小时'\n c = random.uniform(2, 9)\n l.bloodGlucose('%.2f' % c, b)\n self.assertTrue(l.check_signsData())\nelif a == 2:\n b = '餐后1小时'\n c =... | <|body_start_0|>
logging.info('=============测试血糖=============')
l = SignsDataView(self.driver)
self.assertTrue(l.login_health())
a = random.randint(1, 3)
if a == 1:
b = '餐前半小时'
c = random.uniform(2, 9)
l.bloodGlucose('%.2f' % c, b)
... | TestSignsData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSignsData:
def test_bloodGlucose(self):
"""测试血糖 :return:"""
<|body_0|>
def test_bloodPressure(self):
"""测试血压 :return:"""
<|body_1|>
def test_bloodOxygen(self):
"""测试血氧 :return:"""
<|body_2|>
def test_pules(self):
"""测试脉搏 ... | stack_v2_sparse_classes_36k_train_020671 | 3,123 | no_license | [
{
"docstring": "测试血糖 :return:",
"name": "test_bloodGlucose",
"signature": "def test_bloodGlucose(self)"
},
{
"docstring": "测试血压 :return:",
"name": "test_bloodPressure",
"signature": "def test_bloodPressure(self)"
},
{
"docstring": "测试血氧 :return:",
"name": "test_bloodOxygen",
... | 6 | null | Implement the Python class `TestSignsData` described below.
Class description:
Implement the TestSignsData class.
Method signatures and docstrings:
- def test_bloodGlucose(self): 测试血糖 :return:
- def test_bloodPressure(self): 测试血压 :return:
- def test_bloodOxygen(self): 测试血氧 :return:
- def test_pules(self): 测试脉搏 :retur... | Implement the Python class `TestSignsData` described below.
Class description:
Implement the TestSignsData class.
Method signatures and docstrings:
- def test_bloodGlucose(self): 测试血糖 :return:
- def test_bloodPressure(self): 测试血压 :return:
- def test_bloodOxygen(self): 测试血氧 :return:
- def test_pules(self): 测试脉搏 :retur... | d2b7819fd3687e0a011988fefab3e6fd70bb014a | <|skeleton|>
class TestSignsData:
def test_bloodGlucose(self):
"""测试血糖 :return:"""
<|body_0|>
def test_bloodPressure(self):
"""测试血压 :return:"""
<|body_1|>
def test_bloodOxygen(self):
"""测试血氧 :return:"""
<|body_2|>
def test_pules(self):
"""测试脉搏 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSignsData:
def test_bloodGlucose(self):
"""测试血糖 :return:"""
logging.info('=============测试血糖=============')
l = SignsDataView(self.driver)
self.assertTrue(l.login_health())
a = random.randint(1, 3)
if a == 1:
b = '餐前半小时'
c = random.uni... | the_stack_v2_python_sparse | care_user/test_case/test_signsData.py | vothin/code | train | 0 | |
fefe4314a7e38bd4b026125831965d044fe2c171 | [
"self.list = nums\nself.dic = {}\nself.k = len(nums)\nfor i, n in enumerate(self.list):\n self.dic[i] = n",
"for i in range(self.k):\n self.list[i] = self.dic[i]\nreturn self.list",
"index = list(range(self.k))\nrandom.shuffle(index)\nfor i, j in enumerate(index):\n self.list[i] = self.dic[j]\nreturn s... | <|body_start_0|>
self.list = nums
self.dic = {}
self.k = len(nums)
for i, n in enumerate(self.list):
self.dic[i] = n
<|end_body_0|>
<|body_start_1|>
for i in range(self.k):
self.list[i] = self.dic[i]
return self.list
<|end_body_1|>
<|body_start_2... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def reset(self):
"""Resets the array to its original configuration and return it. :rtype: List[int]"""
<|body_1|>
def shuffle(self):
"""Returns a random shuffling of the a... | stack_v2_sparse_classes_36k_train_020672 | 954 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "Resets the array to its original configuration and return it. :rtype: List[int]",
"name": "reset",
"signature": "def reset(self)"
},
{
"docstring": "Returns a ra... | 3 | stack_v2_sparse_classes_30k_train_011173 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def reset(self): Resets the array to its original configuration and return it. :rtype: List[int]
- def shuffle(self): Returns a ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def reset(self): Resets the array to its original configuration and return it. :rtype: List[int]
- def shuffle(self): Returns a ... | 2f46f85e1e297b0a50fdb66956b1d05622a4063d | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def reset(self):
"""Resets the array to its original configuration and return it. :rtype: List[int]"""
<|body_1|>
def shuffle(self):
"""Returns a random shuffling of the a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
self.list = nums
self.dic = {}
self.k = len(nums)
for i, n in enumerate(self.list):
self.dic[i] = n
def reset(self):
"""Resets the array to its original configuration and return it.... | the_stack_v2_python_sparse | dan/Problems/Medium/Array/384. Shuffle an Array/solution.py | xudaaaaan/Leetcode | train | 0 | |
9c9a19a0824d37c16807943e2598fd544c597393 | [
"if not root:\n return None\nstack = [root]\nwhile len(stack) != 0:\n res = stack.pop()\n if node.left:\n stack.append(node.left)\n if node.right:\n stack.append(node.right)\n temp = node.left\n node.left = node.right\n node.right = temp\nreturn root",
"if not root:\n return ... | <|body_start_0|>
if not root:
return None
stack = [root]
while len(stack) != 0:
res = stack.pop()
if node.left:
stack.append(node.left)
if node.right:
stack.append(node.right)
temp = node.left
... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def mirrorTree(self, root: TreeNode) -> TreeNode:
"""辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记为node 2，添加子节点：将node左右节点入栈 3，交换：交换node的左右节点 4，返回值：返回根节点root 复杂度分析： 时间复杂度：O(n) n为二叉树的节点数量，建立二叉树镜像需要遍... | stack_v2_sparse_classes_36k_train_020673 | 4,378 | no_license | [
{
"docstring": "辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记为node 2，添加子节点：将node左右节点入栈 3，交换：交换node的左右节点 4，返回值：返回根节点root 复杂度分析： 时间复杂度：O(n) n为二叉树的节点数量，建立二叉树镜像需要遍历树的所有节点 空间复杂度：O(n) 最差情况下，栈最多同时存储n/2个结点",
"name": "mirrorTree",
"... | 2 | null | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def mirrorTree(self, root: TreeNode) -> TreeNode: 辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记... | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def mirrorTree(self, root: TreeNode) -> TreeNode: 辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution1:
def mirrorTree(self, root: TreeNode) -> TreeNode:
"""辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记为node 2，添加子节点：将node左右节点入栈 3，交换：交换node的左右节点 4，返回值：返回根节点root 复杂度分析： 时间复杂度：O(n) n为二叉树的节点数量，建立二叉树镜像需要遍... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution1:
def mirrorTree(self, root: TreeNode) -> TreeNode:
"""辅助栈，或者辅助队列 利用栈（队列）遍历树的所有节点 node，并交换每个node的左右子树节点 算法流程： 1，特例处理：当root为空时候，直接返回null 2，初始化：栈，加入根节点root 3，循环交换：当栈stack为空时跳出： 1，出栈：记为node 2，添加子节点：将node左右节点入栈 3，交换：交换node的左右节点 4，返回值：返回根节点root 复杂度分析： 时间复杂度：O(n) n为二叉树的节点数量，建立二叉树镜像需要遍历树的所有节点 空间复杂度：... | the_stack_v2_python_sparse | 剑指offer/PythonVersion/27_二叉树的镜像.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
e37bc3396897627da9d3448800fdf4878fa9ffcd | [
"from diplomacy_research.utils.tensorflow import tf\nfrom diplomacy_research.models.layers.graph_convolution import GraphConvolution, preprocess_adjacency\nhps = lambda hparam_name: self.hparams[hparam_name]\nrelu = tf.nn.relu\nnorm_adjacency = preprocess_adjacency(get_adjacency_matrix())\nnorm_adjacency = tf.tile(... | <|body_start_0|>
from diplomacy_research.utils.tensorflow import tf
from diplomacy_research.models.layers.graph_convolution import GraphConvolution, preprocess_adjacency
hps = lambda hparam_name: self.hparams[hparam_name]
relu = tf.nn.relu
norm_adjacency = preprocess_adjacency(ge... | Value Model - Evaluates the value of a state for a given power | ValueModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValueModel:
"""Value Model - Evaluates the value of a state for a given power"""
def _get_board_value(self, board_state, current_power, name='board_state_value', reuse=None):
"""Computes the estimated value of a board state :param board_state: The board state - (batch, NB_NODES, NB_F... | stack_v2_sparse_classes_36k_train_020674 | 7,397 | permissive | [
{
"docstring": "Computes the estimated value of a board state :param board_state: The board state - (batch, NB_NODES, NB_FEATURES) :param current_power: The power for which we want the board value - (batch,) :param name: The name to use for the operaton :param reuse: Whether to reuse or not the weights from ano... | 2 | stack_v2_sparse_classes_30k_train_006105 | Implement the Python class `ValueModel` described below.
Class description:
Value Model - Evaluates the value of a state for a given power
Method signatures and docstrings:
- def _get_board_value(self, board_state, current_power, name='board_state_value', reuse=None): Computes the estimated value of a board state :pa... | Implement the Python class `ValueModel` described below.
Class description:
Value Model - Evaluates the value of a state for a given power
Method signatures and docstrings:
- def _get_board_value(self, board_state, current_power, name='board_state_value', reuse=None): Computes the estimated value of a board state :pa... | e752f02f34936bbae904815708904cabda554b57 | <|skeleton|>
class ValueModel:
"""Value Model - Evaluates the value of a state for a given power"""
def _get_board_value(self, board_state, current_power, name='board_state_value', reuse=None):
"""Computes the estimated value of a board state :param board_state: The board state - (batch, NB_NODES, NB_F... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValueModel:
"""Value Model - Evaluates the value of a state for a given power"""
def _get_board_value(self, board_state, current_power, name='board_state_value', reuse=None):
"""Computes the estimated value of a board state :param board_state: The board state - (batch, NB_NODES, NB_FEATURES) :par... | the_stack_v2_python_sparse | diplomacy_research/models/value/v001_val_relu_7/model.py | JACKHAHA363/research | train | 0 |
bd0113a620af4243dc01c49558ab8b5d01229913 | [
"if nums is None or target is None:\n return []\nlength = len(nums)\nif length < 2:\n return []\nrvt = sorted(enumerate(nums), key=lambda x: x[1])\nleft = 0\nright = length - 1\nwhile left < right:\n sum = rvt[left][1] + rvt[right][1]\n if sum == target:\n return sorted([rvt[left][0], rvt[right][... | <|body_start_0|>
if nums is None or target is None:
return []
length = len(nums)
if length < 2:
return []
rvt = sorted(enumerate(nums), key=lambda x: x[1])
left = 0
right = length - 1
while left < right:
sum = rvt[left][1] + rvt... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if ... | stack_v2_sparse_classes_36k_train_020675 | 1,777 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool",
"name": "findTarget",
"signature": "def findTarget(self, root, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool
<|skele... | c1f27c0cec80585095ce98a678ab85079e1a4c46 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
if nums is None or target is None:
return []
length = len(nums)
if length < 2:
return []
rvt = sorted(enumerate(nums), key=lambda x: x[1])
... | the_stack_v2_python_sparse | Leetcode/1_TwoSum.py | wbq9224/Leetcode_Python | train | 0 | |
9144553dbf29ab5bef749d0eedf3439cbfa05ab7 | [
"self.rects = rects\nself.range = [0]\nself.summ = 0\nfor rect in rects:\n self.summ += (rect[2] - rect[0] + 1) * (rect[3] - rect[1] + 1)\n self.range.append(self.summ)",
"n = random.randint(0, self.summ - 1)\ni = bisect.bisect(self.range, n)\nrect = self.rects[i - 1]\nn -= self.range[i - 1]\nx = rect[0] + ... | <|body_start_0|>
self.rects = rects
self.range = [0]
self.summ = 0
for rect in rects:
self.summ += (rect[2] - rect[0] + 1) * (rect[3] - rect[1] + 1)
self.range.append(self.summ)
<|end_body_0|>
<|body_start_1|>
n = random.randint(0, self.summ - 1)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.rects = rects
self.range = [0]
self.summ = 0
for rec... | stack_v2_sparse_classes_36k_train_020676 | 2,975 | no_license | [
{
"docstring": ":type rects: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, rects)"
},
{
"docstring": ":rtype: List[int]",
"name": "pick",
"signature": "def pick(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int]
<|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: ... | 7a459e9742958e63be8886874904e5ab2489411a | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
self.rects = rects
self.range = [0]
self.summ = 0
for rect in rects:
self.summ += (rect[2] - rect[0] + 1) * (rect[3] - rect[1] + 1)
self.range.append(self.summ)
def pick... | the_stack_v2_python_sparse | Medium/497.py | Hellofafar/Leetcode | train | 6 | |
8fd103c2892d529f5fd66ed603ad285900c9f5c9 | [
"nbm = self.notebook_manager\nnbm.restore_checkpoint(notebook_id, checkpoint_id)\nself.set_status(204)\nself.finish()",
"nbm = self.notebook_manager\nnbm.delte_checkpoint(notebook_id, checkpoint_id)\nself.set_status(204)\nself.finish()"
] | <|body_start_0|>
nbm = self.notebook_manager
nbm.restore_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
self.finish()
<|end_body_0|>
<|body_start_1|>
nbm = self.notebook_manager
nbm.delte_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
... | ModifyNotebookCheckpointsHandler | [
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
<|body_0|>
def delete(self, notebook_id, checkpoint_id):
"""delete clears a checkpoint for a given notebook"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_020677 | 5,267 | permissive | [
{
"docstring": "post restores a notebook from a checkpoint",
"name": "post",
"signature": "def post(self, notebook_id, checkpoint_id)"
},
{
"docstring": "delete clears a checkpoint for a given notebook",
"name": "delete",
"signature": "def delete(self, notebook_id, checkpoint_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016858 | Implement the Python class `ModifyNotebookCheckpointsHandler` described below.
Class description:
Implement the ModifyNotebookCheckpointsHandler class.
Method signatures and docstrings:
- def post(self, notebook_id, checkpoint_id): post restores a notebook from a checkpoint
- def delete(self, notebook_id, checkpoint_... | Implement the Python class `ModifyNotebookCheckpointsHandler` described below.
Class description:
Implement the ModifyNotebookCheckpointsHandler class.
Method signatures and docstrings:
- def post(self, notebook_id, checkpoint_id): post restores a notebook from a checkpoint
- def delete(self, notebook_id, checkpoint_... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
<|body_0|>
def delete(self, notebook_id, checkpoint_id):
"""delete clears a checkpoint for a given notebook"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
nbm = self.notebook_manager
nbm.restore_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
self.finish()
def delete(self, noteboo... | the_stack_v2_python_sparse | pkgs/ipython-1.2.1-py27_0/lib/python2.7/site-packages/IPython/html/services/notebooks/handlers.py | wangyum/Anaconda | train | 11 | |
c2d15232d2f0fa7e58e0256d8f67549389b49b26 | [
"engine = db_connect()\ncreate_table(engine)\nself.Session = sessionmaker(bind=engine)",
"session = self.Session()\ndoc = Docs()\ndoc.authors = item['authors']\ndoc.year = item['year']\ndoc.title = item['title']\ndoc.journal = item['journal']\ndoc.bibref_details = item['bibref_details']\ndoc.volume = item['volume... | <|body_start_0|>
engine = db_connect()
create_table(engine)
self.Session = sessionmaker(bind=engine)
<|end_body_0|>
<|body_start_1|>
session = self.Session()
doc = Docs()
doc.authors = item['authors']
doc.year = item['year']
doc.title = item['title']
... | This is a custom Item Pipeline class. | ZbPipeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZbPipeline:
"""This is a custom Item Pipeline class."""
def __init__(self):
"""Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session."""
<|body_0|>
def process_item(self, item, spider):
"""Overwrited the ... | stack_v2_sparse_classes_36k_train_020678 | 2,127 | permissive | [
{
"docstring": "Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Overwrited the process_item() required method for custom Item Proces- sors. Args: item (scr... | 2 | stack_v2_sparse_classes_30k_val_000971 | Implement the Python class `ZbPipeline` described below.
Class description:
This is a custom Item Pipeline class.
Method signatures and docstrings:
- def __init__(self): Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session.
- def process_item(self, item, spi... | Implement the Python class `ZbPipeline` described below.
Class description:
This is a custom Item Pipeline class.
Method signatures and docstrings:
- def __init__(self): Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session.
- def process_item(self, item, spi... | c684be7345988ec518a406a42bd95a0778e1d4e9 | <|skeleton|>
class ZbPipeline:
"""This is a custom Item Pipeline class."""
def __init__(self):
"""Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session."""
<|body_0|>
def process_item(self, item, spider):
"""Overwrited the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZbPipeline:
"""This is a custom Item Pipeline class."""
def __init__(self):
"""Init method, that instantiates an engine and create a table by calling zb.models.py methods, and start a Session."""
engine = db_connect()
create_table(engine)
self.Session = sessionmaker(bind=e... | the_stack_v2_python_sparse | etl/extract/zb/pipelines.py | mguidoti/DSND-p6-capstone | train | 0 |
8c9c14c67e2c0dd60900ff0110504cb21224f1f2 | [
"user = create_user()\nlist_sensor = []\nsensor1 = create_sensor('test1', 'code1', user)\nlist_sensor.append(sensor1)\nsensor2 = create_sensor('test2', 'code2', user)\nlist_sensor.append(sensor2)\nself.assertEqual(len(list_sensor), 2)",
"user = create_user()\ncode_mouse_event = 'The event is attached to its targe... | <|body_start_0|>
user = create_user()
list_sensor = []
sensor1 = create_sensor('test1', 'code1', user)
list_sensor.append(sensor1)
sensor2 = create_sensor('test2', 'code2', user)
list_sensor.append(sensor2)
self.assertEqual(len(list_sensor), 2)
<|end_body_0|>
<|b... | SensorTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensorTests:
def test_list_Sensor(self):
"""Test for a list of Sensor :return:"""
<|body_0|>
def test_create_Sensor(self):
"""Test for a created Sensor :return:"""
<|body_1|>
def test_update_Sensor(self):
"""Test for a update Sensor :return:"""
... | stack_v2_sparse_classes_36k_train_020679 | 3,684 | no_license | [
{
"docstring": "Test for a list of Sensor :return:",
"name": "test_list_Sensor",
"signature": "def test_list_Sensor(self)"
},
{
"docstring": "Test for a created Sensor :return:",
"name": "test_create_Sensor",
"signature": "def test_create_Sensor(self)"
},
{
"docstring": "Test for... | 4 | stack_v2_sparse_classes_30k_train_003860 | Implement the Python class `SensorTests` described below.
Class description:
Implement the SensorTests class.
Method signatures and docstrings:
- def test_list_Sensor(self): Test for a list of Sensor :return:
- def test_create_Sensor(self): Test for a created Sensor :return:
- def test_update_Sensor(self): Test for a... | Implement the Python class `SensorTests` described below.
Class description:
Implement the SensorTests class.
Method signatures and docstrings:
- def test_list_Sensor(self): Test for a list of Sensor :return:
- def test_create_Sensor(self): Test for a created Sensor :return:
- def test_update_Sensor(self): Test for a... | 8c8f76acb85baff1cd2d8258f686515d08678350 | <|skeleton|>
class SensorTests:
def test_list_Sensor(self):
"""Test for a list of Sensor :return:"""
<|body_0|>
def test_create_Sensor(self):
"""Test for a created Sensor :return:"""
<|body_1|>
def test_update_Sensor(self):
"""Test for a update Sensor :return:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SensorTests:
def test_list_Sensor(self):
"""Test for a list of Sensor :return:"""
user = create_user()
list_sensor = []
sensor1 = create_sensor('test1', 'code1', user)
list_sensor.append(sensor1)
sensor2 = create_sensor('test2', 'code2', user)
list_senso... | the_stack_v2_python_sparse | probe_project/apps/probe_dispatcher/tests.py | liflab/cornipickle-probe | train | 0 | |
684ac5d020af54b814e062e5262026b8dfb17b83 | [
"test_user1 = self.add_user('something@email.com', 'Some', 'Thing', 'Mr')\ntest_user2 = self.add_user('something2@email.com', 'Some', 'Thing2', 'Ms')\nevent_admin = self.add_user('event_admin@ea.com', 'event_admin', is_admin=True)\nevent = self.add_event(name={'en': 'Tech Talk'}, description={'en': 'tech talking'},... | <|body_start_0|>
test_user1 = self.add_user('something@email.com', 'Some', 'Thing', 'Mr')
test_user2 = self.add_user('something2@email.com', 'Some', 'Thing2', 'Ms')
event_admin = self.add_user('event_admin@ea.com', 'event_admin', is_admin=True)
event = self.add_event(name={'en': 'Tech Ta... | OfferListAPITest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfferListAPITest:
def _seed_static_data(self):
"""Seed static data for the tests."""
<|body_0|>
def test_offer_list(self):
"""Test that an offer list is returned."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
test_user1 = self.add_user('something@... | stack_v2_sparse_classes_36k_train_020680 | 22,229 | permissive | [
{
"docstring": "Seed static data for the tests.",
"name": "_seed_static_data",
"signature": "def _seed_static_data(self)"
},
{
"docstring": "Test that an offer list is returned.",
"name": "test_offer_list",
"signature": "def test_offer_list(self)"
}
] | 2 | null | Implement the Python class `OfferListAPITest` described below.
Class description:
Implement the OfferListAPITest class.
Method signatures and docstrings:
- def _seed_static_data(self): Seed static data for the tests.
- def test_offer_list(self): Test that an offer list is returned. | Implement the Python class `OfferListAPITest` described below.
Class description:
Implement the OfferListAPITest class.
Method signatures and docstrings:
- def _seed_static_data(self): Seed static data for the tests.
- def test_offer_list(self): Test that an offer list is returned.
<|skeleton|>
class OfferListAPITes... | c0002c877ee65dbed282283614be8f3ea5ec750b | <|skeleton|>
class OfferListAPITest:
def _seed_static_data(self):
"""Seed static data for the tests."""
<|body_0|>
def test_offer_list(self):
"""Test that an offer list is returned."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfferListAPITest:
def _seed_static_data(self):
"""Seed static data for the tests."""
test_user1 = self.add_user('something@email.com', 'Some', 'Thing', 'Mr')
test_user2 = self.add_user('something2@email.com', 'Some', 'Thing2', 'Ms')
event_admin = self.add_user('event_admin@ea.c... | the_stack_v2_python_sparse | api/app/registration/tests.py | deep-learning-indaba/Baobab | train | 59 | |
35b393ed44d3d82c6785f03beb2b1ae969e9d63b | [
"currency_id = False\naccount_move = self.account_move_id\nif account_move:\n if account_move.currency_id:\n currency_id = account_move.currency_id\n elif account_move.account_id.currency_id:\n currency_id = account_move.account_id.currency_id.id\n else:\n currency_id = account_move.co... | <|body_start_0|>
currency_id = False
account_move = self.account_move_id
if account_move:
if account_move.currency_id:
currency_id = account_move.currency_id
elif account_move.account_id.currency_id:
currency_id = account_move.account_id.cu... | Credit lines to reconcile payments from an invoice | invoice_reconciliation_credit_line | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class invoice_reconciliation_credit_line:
"""Credit lines to reconcile payments from an invoice"""
def _compute_currency_id(self):
"""On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle de la société de l'écriture comptable"""
<|body_... | stack_v2_sparse_classes_36k_train_020681 | 36,478 | no_license | [
{
"docstring": "On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle de la société de l'écriture comptable",
"name": "_compute_currency_id",
"signature": "def _compute_currency_id(self)"
},
{
"docstring": "Au changement du montant à réconcilier, on ... | 2 | null | Implement the Python class `invoice_reconciliation_credit_line` described below.
Class description:
Credit lines to reconcile payments from an invoice
Method signatures and docstrings:
- def _compute_currency_id(self): On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle... | Implement the Python class `invoice_reconciliation_credit_line` described below.
Class description:
Credit lines to reconcile payments from an invoice
Method signatures and docstrings:
- def _compute_currency_id(self): On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle... | eb394e1f79ba1995da2dcd81adfdd511c22caff9 | <|skeleton|>
class invoice_reconciliation_credit_line:
"""Credit lines to reconcile payments from an invoice"""
def _compute_currency_id(self):
"""On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle de la société de l'écriture comptable"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class invoice_reconciliation_credit_line:
"""Credit lines to reconcile payments from an invoice"""
def _compute_currency_id(self):
"""On récupère la devise de l'écriture comptable, ou celle du compte de l'écriture comptable, ou celle de la société de l'écriture comptable"""
currency_id = False
... | the_stack_v2_python_sparse | OpenPROD/openprod-addons/account_openprod/wizard/invoice_reconciliation.py | kazacube-mziouadi/ceci | train | 0 |
5d23d239ab717bcc29c49d9e6d08c13efd5cd720 | [
"if not root:\n return ''\nqueue = collections.deque([root])\nres = []\nwhile queue:\n node = queue.popleft()\n res.append(str(node.val) if node else 'null')\n if node:\n queue.append(node.left)\n queue.append(node.right)\nreturn ' '.join(res)",
"if not data:\n return None\nbfs_order ... | <|body_start_0|>
if not root:
return ''
queue = collections.deque([root])
res = []
while queue:
node = queue.popleft()
res.append(str(node.val) if node else 'null')
if node:
queue.append(node.left)
queue.appe... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_020682 | 4,000 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 14193efc60bd3ec9cef48e777fdba022ce190285 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
queue = collections.deque([root])
res = []
while queue:
node = queue.popleft()
res.append(str(node.val)... | the_stack_v2_python_sparse | src/297.py | liuyaqiao/Algorithms | train | 0 | |
b47fdae17486036f89ab53ec02ffb1d4390ee209 | [
"shape_list = x.get_shape().as_list()\nassert len(shape_list) == 3\nself.x = x\nself.layer_index = layer_index\nself.d_model = d_model\nself.d_ff = d_ff\nself.initializer = tf.random_normal_initializer(stddev=0.1)",
"output = None\ninput = tf.expand_dims(self.x, axis=3)\noutput_conv1 = tf.layers.conv2d(input, fil... | <|body_start_0|>
shape_list = x.get_shape().as_list()
assert len(shape_list) == 3
self.x = x
self.layer_index = layer_index
self.d_model = d_model
self.d_ff = d_ff
self.initializer = tf.random_normal_initializer(stddev=0.1)
<|end_body_0|>
<|body_start_1|>
... | position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2 | PositionWiseFeedFoward | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionWiseFeedFoward:
"""position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2"""
def __init__(self, x, layer_index, d_model=512, d_ff=2048):
""":param x: shape should be:[batch,sequence_length,d_model] :param layer_index: index of layer :return: shape:[s... | stack_v2_sparse_classes_36k_train_020683 | 3,327 | permissive | [
{
"docstring": ":param x: shape should be:[batch,sequence_length,d_model] :param layer_index: index of layer :return: shape:[sequence_length,d_model]",
"name": "__init__",
"signature": "def __init__(self, x, layer_index, d_model=512, d_ff=2048)"
},
{
"docstring": "x: [batch,sequence_length,d_mod... | 2 | stack_v2_sparse_classes_30k_train_020359 | Implement the Python class `PositionWiseFeedFoward` described below.
Class description:
position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2
Method signatures and docstrings:
- def __init__(self, x, layer_index, d_model=512, d_ff=2048): :param x: shape should be:[batch,sequence_length,d_mo... | Implement the Python class `PositionWiseFeedFoward` described below.
Class description:
position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2
Method signatures and docstrings:
- def __init__(self, x, layer_index, d_model=512, d_ff=2048): :param x: shape should be:[batch,sequence_length,d_mo... | 091ff9910839ba5053302383af99762c0c91a992 | <|skeleton|>
class PositionWiseFeedFoward:
"""position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2"""
def __init__(self, x, layer_index, d_model=512, d_ff=2048):
""":param x: shape should be:[batch,sequence_length,d_model] :param layer_index: index of layer :return: shape:[s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositionWiseFeedFoward:
"""position-wise feed forward networks. formula as below: FFN(x)=max(0,xW1+b1)W2+b2"""
def __init__(self, x, layer_index, d_model=512, d_ff=2048):
""":param x: shape should be:[batch,sequence_length,d_model] :param layer_index: index of layer :return: shape:[sequence_lengt... | the_stack_v2_python_sparse | a07_Transformer/a2_poistion_wise_feed_forward.py | SunYanCN/text_classification | train | 2 |
639f990371bf20341eeb8b78734bac7be8cf8876 | [
"oper = {'and': 'intersection', 'or': 'union', 'not': 'complement'}\nif len(item) < 2 or len(item) > 3:\n raise TypeError('{} must be exactly 1 operator and 1-2 items'.format(item))\nself._check('operator', item[0], str, choices=oper.keys())\nself._check('operand1', item[1], (int, tuple))\nif len(item) == 3:\n ... | <|body_start_0|>
oper = {'and': 'intersection', 'or': 'union', 'not': 'complement'}
if len(item) < 2 or len(item) > 3:
raise TypeError('{} must be exactly 1 operator and 1-2 items'.format(item))
self._check('operator', item[0], str, choices=oper.keys())
self._check('operand1'... | SCEndpoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SCEndpoint:
def _combo_expansion(self, item):
"""Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`dict`: The dictionary structure of the expanded asset list combinations."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020684 | 12,037 | permissive | [
{
"docstring": "Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`dict`: The dictionary structure of the expanded asset list combinations.",
"name": "_combo_expansion",
"signature": "def _combo_expansion(self, item)... | 3 | stack_v2_sparse_classes_30k_train_014850 | Implement the Python class `SCEndpoint` described below.
Class description:
Implement the SCEndpoint class.
Method signatures and docstrings:
- def _combo_expansion(self, item): Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`d... | Implement the Python class `SCEndpoint` described below.
Class description:
Implement the SCEndpoint class.
Method signatures and docstrings:
- def _combo_expansion(self, item): Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`d... | 4e31049891f55016168b14ae30d332a965523640 | <|skeleton|>
class SCEndpoint:
def _combo_expansion(self, item):
"""Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`dict`: The dictionary structure of the expanded asset list combinations."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SCEndpoint:
def _combo_expansion(self, item):
"""Expands the asset combination expressions from nested tuples to the nested dictionary structure that's expected. Args: item Returns: :obj:`dict`: The dictionary structure of the expanded asset list combinations."""
oper = {'and': 'intersection',... | the_stack_v2_python_sparse | tenable/sc/base.py | tenable/pyTenable | train | 300 | |
3d085d472f1e2d7c8ab69f1b449bc40a005b486d | [
"if self.parent_stack:\n return self.parent_stack[-1].segments[:self.segment_idx]\nelse:\n return tuple()",
"if self.parent_stack:\n return self.parent_stack[-1].segments[self.segment_idx + 1:]\nelse:\n return tuple()"
] | <|body_start_0|>
if self.parent_stack:
return self.parent_stack[-1].segments[:self.segment_idx]
else:
return tuple()
<|end_body_0|>
<|body_start_1|>
if self.parent_stack:
return self.parent_stack[-1].segments[self.segment_idx + 1:]
else:
r... | Class for holding the context passed to rule eval functions. | RuleContext | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleContext:
"""Class for holding the context passed to rule eval functions."""
def siblings_pre(self) -> Tuple[BaseSegment, ...]:
"""Return sibling segments prior to self.segment."""
<|body_0|>
def siblings_post(self) -> Tuple[BaseSegment, ...]:
"""Return siblin... | stack_v2_sparse_classes_36k_train_020685 | 1,767 | permissive | [
{
"docstring": "Return sibling segments prior to self.segment.",
"name": "siblings_pre",
"signature": "def siblings_pre(self) -> Tuple[BaseSegment, ...]"
},
{
"docstring": "Return sibling segments after self.segment.",
"name": "siblings_post",
"signature": "def siblings_post(self) -> Tup... | 2 | null | Implement the Python class `RuleContext` described below.
Class description:
Class for holding the context passed to rule eval functions.
Method signatures and docstrings:
- def siblings_pre(self) -> Tuple[BaseSegment, ...]: Return sibling segments prior to self.segment.
- def siblings_post(self) -> Tuple[BaseSegment... | Implement the Python class `RuleContext` described below.
Class description:
Class for holding the context passed to rule eval functions.
Method signatures and docstrings:
- def siblings_pre(self) -> Tuple[BaseSegment, ...]: Return sibling segments prior to self.segment.
- def siblings_post(self) -> Tuple[BaseSegment... | a66da908907ee1eaf09d88a731025da29e7fca07 | <|skeleton|>
class RuleContext:
"""Class for holding the context passed to rule eval functions."""
def siblings_pre(self) -> Tuple[BaseSegment, ...]:
"""Return sibling segments prior to self.segment."""
<|body_0|>
def siblings_post(self) -> Tuple[BaseSegment, ...]:
"""Return siblin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RuleContext:
"""Class for holding the context passed to rule eval functions."""
def siblings_pre(self) -> Tuple[BaseSegment, ...]:
"""Return sibling segments prior to self.segment."""
if self.parent_stack:
return self.parent_stack[-1].segments[:self.segment_idx]
else:
... | the_stack_v2_python_sparse | src/sqlfluff/core/rules/context.py | sqlfluff/sqlfluff | train | 5,931 |
79eabc0e2877e04d2205ef39e5139fd615cd71b6 | [
"self.screen = screen\nself.rect = rect\nself.font_size = font_size\nself.txt_color = (255, 255, 255)\nself.images = images\nself.text = ''\nself.set_text(text)\nself.action = action\nself.is_down = False\nself.user_data = None\nself.enabled = True\nself.prev_image = None\nself.buttonClick = pygame.mixer.Sound('dat... | <|body_start_0|>
self.screen = screen
self.rect = rect
self.font_size = font_size
self.txt_color = (255, 255, 255)
self.images = images
self.text = ''
self.set_text(text)
self.action = action
self.is_down = False
self.user_data = None
... | Button | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Button:
def __init__(self, screen, rect, text='', font_size=20, action=None, images=None):
"""The button needs a rect (to set position and size), a label and (optionally) an action. (the action is a function to be called when the button is pressed). Finaly a tuple of 4 images can be pass... | stack_v2_sparse_classes_36k_train_020686 | 4,970 | no_license | [
{
"docstring": "The button needs a rect (to set position and size), a label and (optionally) an action. (the action is a function to be called when the button is pressed). Finaly a tuple of 4 images can be passed: normal, hover, down & disabled. when a button is clicked, it also creates an event of type Events.... | 5 | stack_v2_sparse_classes_30k_train_014814 | Implement the Python class `Button` described below.
Class description:
Implement the Button class.
Method signatures and docstrings:
- def __init__(self, screen, rect, text='', font_size=20, action=None, images=None): The button needs a rect (to set position and size), a label and (optionally) an action. (the action... | Implement the Python class `Button` described below.
Class description:
Implement the Button class.
Method signatures and docstrings:
- def __init__(self, screen, rect, text='', font_size=20, action=None, images=None): The button needs a rect (to set position and size), a label and (optionally) an action. (the action... | cbec4381d940a80ac4f888777ccbdee3f4fa0941 | <|skeleton|>
class Button:
def __init__(self, screen, rect, text='', font_size=20, action=None, images=None):
"""The button needs a rect (to set position and size), a label and (optionally) an action. (the action is a function to be called when the button is pressed). Finaly a tuple of 4 images can be pass... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Button:
def __init__(self, screen, rect, text='', font_size=20, action=None, images=None):
"""The button needs a rect (to set position and size), a label and (optionally) an action. (the action is a function to be called when the button is pressed). Finaly a tuple of 4 images can be passed: normal, ho... | the_stack_v2_python_sparse | project/build/exe.win-amd64-3.6/GUI/button.py | MatisseGh/RiskProject | train | 0 | |
4d1eb8d7db518a4fcaf6c84aad66d55505a3e4c8 | [
"result = 0\nwhile n != 0:\n digit = n % 10\n result += digit\n n /= 10\n if n != 0:\n result *= 10\nreturn result",
"if x < 0:\n return False\nreturn self.reverseInteger(abs(x)) == abs(x)"
] | <|body_start_0|>
result = 0
while n != 0:
digit = n % 10
result += digit
n /= 10
if n != 0:
result *= 10
return result
<|end_body_0|>
<|body_start_1|>
if x < 0:
return False
return self.reverseInteger(ab... | Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome"""
def reverseInteger(self, n):
"""Reverses a number and returns the reversed number"""
<|body_0|>
def isPalindrome(self, x):
... | stack_v2_sparse_classes_36k_train_020687 | 776 | no_license | [
{
"docstring": "Reverses a number and returns the reversed number",
"name": "reverseInteger",
"signature": "def reverseInteger(self, n)"
},
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013292 | Implement the Python class `Solution` described below.
Class description:
Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome
Method signatures and docstrings:
- def reverseInteger(self, n): Reverses a number and returns the reversed number
- d... | Implement the Python class `Solution` described below.
Class description:
Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome
Method signatures and docstrings:
- def reverseInteger(self, n): Reverses a number and returns the reversed number
- d... | f5bb79266f2bfed9fba0b92e06b93b308eb49767 | <|skeleton|>
class Solution:
"""Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome"""
def reverseInteger(self, n):
"""Reverses a number and returns the reversed number"""
<|body_0|>
def isPalindrome(self, x):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Solution reverses the integer, then checks if the reversed integer equals the original integer. If it does, it's a palindrome"""
def reverseInteger(self, n):
"""Reverses a number and returns the reversed number"""
result = 0
while n != 0:
digit = n % 10
... | the_stack_v2_python_sparse | palindrome_number.py | DarinM223/leetcode | train | 0 |
a9dda2b5872527b3da007e45701ac6982b8b5fa6 | [
"cls._insert_properties(model=model, interface=cls)\ncls._insert_methods(model=model, interface=cls)\ncls._insert_functions(model=model, interface=cls)",
"for property_name, default_value in interface._PROPERTIES.items():\n if property_name not in model.__dir__():\n setattr(model, property_name, copy.co... | <|body_start_0|>
cls._insert_properties(model=model, interface=cls)
cls._insert_methods(model=model, interface=cls)
cls._insert_functions(model=model, interface=cls)
<|end_body_0|>
<|body_start_1|>
for property_name, default_value in interface._PROPERTIES.items():
if propert... | An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attributes: '_PROPERTIES', '_METHODS' and '_FUNCTIONS'. Then it should implement 'add_in... | MLRunInterface | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLRunInterface:
"""An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attributes: '_PROPERTIES', '_METHODS' and '_FU... | stack_v2_sparse_classes_36k_train_020688 | 3,226 | permissive | [
{
"docstring": "Enrich the model object with this class properties, methods and functions so it will have MLRun specific features. :param model: The object to enrich his interface",
"name": "add_interface",
"signature": "def add_interface(cls, model: Model)"
},
{
"docstring": "Insert the propert... | 4 | null | Implement the Python class `MLRunInterface` described below.
Class description:
An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attribu... | Implement the Python class `MLRunInterface` described below.
Class description:
An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attribu... | 97209b27ccf3daf8f202a1a2bb1b01abd537ad70 | <|skeleton|>
class MLRunInterface:
"""An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attributes: '_PROPERTIES', '_METHODS' and '_FU... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLRunInterface:
"""An abstract class for enriching an object interface with the properties, methods and functions written below. A class inheriting MLRun interface should insert what ever it needs to be inserted to the object to the following private attributes: '_PROPERTIES', '_METHODS' and '_FUNCTIONS'. The... | the_stack_v2_python_sparse | mlrun/frameworks/_common/mlrun_interface.py | eran-nussbaum/mlrun | train | 0 |
e8f7cbbde808a8878f904bf9f211dad0917ca9a6 | [
"self.sensor = sensor = eyesensor\nself.sensor_view = sensor.view\nself.sensor.view = self.view\nself.age = 0\nself.samples = []\nnumber_of_samples = min(number_of_samples, sample_period)\nself.schedule = random.sample(range(sample_period), number_of_samples)\nself.schedule.sort(reverse=True)",
"retval = self.sen... | <|body_start_0|>
self.sensor = sensor = eyesensor
self.sensor_view = sensor.view
self.sensor.view = self.view
self.age = 0
self.samples = []
number_of_samples = min(number_of_samples, sample_period)
self.schedule = random.sample(range(sample_period), number_of_sam... | Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays. | EyeSensorSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EyeSensorSampler:
"""Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays."""
def __init__(self, eyesensor, sample_period, number_of_samples=30):
"""This draws its samples directly from the output of eyesensor.view() by wrapping the method."""
... | stack_v2_sparse_classes_36k_train_020689 | 38,944 | permissive | [
{
"docstring": "This draws its samples directly from the output of eyesensor.view() by wrapping the method.",
"name": "__init__",
"signature": "def __init__(self, eyesensor, sample_period, number_of_samples=30)"
},
{
"docstring": "Wrapper around eyesensor.view which takes samples",
"name": "... | 3 | stack_v2_sparse_classes_30k_train_020601 | Implement the Python class `EyeSensorSampler` described below.
Class description:
Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays.
Method signatures and docstrings:
- def __init__(self, eyesensor, sample_period, number_of_samples=30): This draws its samples directly from the outpu... | Implement the Python class `EyeSensorSampler` described below.
Class description:
Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays.
Method signatures and docstrings:
- def __init__(self, eyesensor, sample_period, number_of_samples=30): This draws its samples directly from the outpu... | 367f8701ec18226029d7ef070e70e9a8248a1374 | <|skeleton|>
class EyeSensorSampler:
"""Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays."""
def __init__(self, eyesensor, sample_period, number_of_samples=30):
"""This draws its samples directly from the output of eyesensor.view() by wrapping the method."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EyeSensorSampler:
"""Samples eyesensor.rgb, the eye's view. Attribute samples is list of RGB numpy arrays."""
def __init__(self, eyesensor, sample_period, number_of_samples=30):
"""This draws its samples directly from the output of eyesensor.view() by wrapping the method."""
self.sensor =... | the_stack_v2_python_sparse | encoders.py | ctrl-z-9000-times/HTM_experiments | train | 15 |
321badeb5eebfb5b264d02aab1da193677c8edb2 | [
"discussion = Discussion(title='Sample Discussion')\ntime = discussion.last_modified\ndiscussion.update_last_modified()\nself.assertNotEqual(time, discussion.last_modified)",
"time = timezone.now() + datetime.timedelta(days=30)\nfuture_discussion = Discussion(create_date=time)\nself.assertEqual(future_discussion.... | <|body_start_0|>
discussion = Discussion(title='Sample Discussion')
time = discussion.last_modified
discussion.update_last_modified()
self.assertNotEqual(time, discussion.last_modified)
<|end_body_0|>
<|body_start_1|>
time = timezone.now() + datetime.timedelta(days=30)
f... | DiscussionMethodTestCase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiscussionMethodTestCase:
def test_update_last_modified(self):
"""If a discussion is created it should have a default last_modified time. When calling update_last_modified() the discussion last_modified should be reset to the current time. Thus it should not equal the time of instantiati... | stack_v2_sparse_classes_36k_train_020690 | 2,139 | permissive | [
{
"docstring": "If a discussion is created it should have a default last_modified time. When calling update_last_modified() the discussion last_modified should be reset to the current time. Thus it should not equal the time of instantiation.",
"name": "test_update_last_modified",
"signature": "def test_... | 4 | stack_v2_sparse_classes_30k_train_006152 | Implement the Python class `DiscussionMethodTestCase` described below.
Class description:
Implement the DiscussionMethodTestCase class.
Method signatures and docstrings:
- def test_update_last_modified(self): If a discussion is created it should have a default last_modified time. When calling update_last_modified() t... | Implement the Python class `DiscussionMethodTestCase` described below.
Class description:
Implement the DiscussionMethodTestCase class.
Method signatures and docstrings:
- def test_update_last_modified(self): If a discussion is created it should have a default last_modified time. When calling update_last_modified() t... | 59f3f3ae727fe52c7897beaf73d157b02cdcb7a3 | <|skeleton|>
class DiscussionMethodTestCase:
def test_update_last_modified(self):
"""If a discussion is created it should have a default last_modified time. When calling update_last_modified() the discussion last_modified should be reset to the current time. Thus it should not equal the time of instantiati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiscussionMethodTestCase:
def test_update_last_modified(self):
"""If a discussion is created it should have a default last_modified time. When calling update_last_modified() the discussion last_modified should be reset to the current time. Thus it should not equal the time of instantiation."""
... | the_stack_v2_python_sparse | discussions/tests.py | pabulumm/neighbors | train | 0 | |
fb3c46559c97249ec61dc3c112ce70ada3c8b605 | [
"self.price = price\nspecial = list(filter(lambda x: x[-1] < sum((x[i] * price[i] for i in range(len(price)))), special))\nreturn self.shopping(special, needs)",
"if not needs:\n return 0\nspcial = list(filter(lambda x: all((x[i] <= needs[i] for i in range(len(needs)))), spcial))\nif not spcial:\n return su... | <|body_start_0|>
self.price = price
special = list(filter(lambda x: x[-1] < sum((x[i] * price[i] for i in range(len(price)))), special))
return self.shopping(special, needs)
<|end_body_0|>
<|body_start_1|>
if not needs:
return 0
spcial = list(filter(lambda x: all((x[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shoppingOffers(self, price, special, needs):
""":type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int"""
<|body_0|>
def shopping(self, spcial, needs):
"""从 spcial中 刚刚好购买needs所需的最低花费 :param spcial: :param needs: :return... | stack_v2_sparse_classes_36k_train_020691 | 2,735 | no_license | [
{
"docstring": ":type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int",
"name": "shoppingOffers",
"signature": "def shoppingOffers(self, price, special, needs)"
},
{
"docstring": "从 spcial中 刚刚好购买needs所需的最低花费 :param spcial: :param needs: :return:",
"name": "... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shoppingOffers(self, price, special, needs): :type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int
- def shopping(self, spcial, needs): 从 s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shoppingOffers(self, price, special, needs): :type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int
- def shopping(self, spcial, needs): 从 s... | c0807a7f31a265b3090ef3d32a0ad5a2b10579f7 | <|skeleton|>
class Solution:
def shoppingOffers(self, price, special, needs):
""":type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int"""
<|body_0|>
def shopping(self, spcial, needs):
"""从 spcial中 刚刚好购买needs所需的最低花费 :param spcial: :param needs: :return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shoppingOffers(self, price, special, needs):
""":type price: List[int] :type special: List[List[int]] :type needs: List[int] :rtype: int"""
self.price = price
special = list(filter(lambda x: x[-1] < sum((x[i] * price[i] for i in range(len(price)))), special))
retu... | the_stack_v2_python_sparse | six_hundred_thirty_eight.py | Yanl05/LeetCode | train | 0 | |
e496289bdc2f5d4e224a682c3b466c3ccb78d0ee | [
"if codecs is None:\n encoding = None\nConcurrentRotatingFileHandler.__init__(self, filename, mode, encoding, delay)\nself.suffix = '%Y-%m-%d'\nself.suffix_time = ''",
"try:\n if self.check_baseFilename(record):\n self.build_baseFilename()\n ConcurrentRotatingFileHandler.emit(self, record)\nexcept... | <|body_start_0|>
if codecs is None:
encoding = None
ConcurrentRotatingFileHandler.__init__(self, filename, mode, encoding, delay)
self.suffix = '%Y-%m-%d'
self.suffix_time = ''
<|end_body_0|>
<|body_start_1|>
try:
if self.check_baseFilename(record):
... | SafeFileHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SafeFileHandler:
def __init__(self, filename, mode, encoding=None, delay=0):
"""Use the specified filename for streamed logging"""
<|body_0|>
def emit(self, record):
"""Emit a record. Always check time"""
<|body_1|>
def check_baseFilename(self, record):
... | stack_v2_sparse_classes_36k_train_020692 | 3,518 | no_license | [
{
"docstring": "Use the specified filename for streamed logging",
"name": "__init__",
"signature": "def __init__(self, filename, mode, encoding=None, delay=0)"
},
{
"docstring": "Emit a record. Always check time",
"name": "emit",
"signature": "def emit(self, record)"
},
{
"docstr... | 4 | stack_v2_sparse_classes_30k_train_015854 | Implement the Python class `SafeFileHandler` described below.
Class description:
Implement the SafeFileHandler class.
Method signatures and docstrings:
- def __init__(self, filename, mode, encoding=None, delay=0): Use the specified filename for streamed logging
- def emit(self, record): Emit a record. Always check ti... | Implement the Python class `SafeFileHandler` described below.
Class description:
Implement the SafeFileHandler class.
Method signatures and docstrings:
- def __init__(self, filename, mode, encoding=None, delay=0): Use the specified filename for streamed logging
- def emit(self, record): Emit a record. Always check ti... | fa608a9fab7fe9293e728c8051186d95b4a15fc1 | <|skeleton|>
class SafeFileHandler:
def __init__(self, filename, mode, encoding=None, delay=0):
"""Use the specified filename for streamed logging"""
<|body_0|>
def emit(self, record):
"""Emit a record. Always check time"""
<|body_1|>
def check_baseFilename(self, record):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SafeFileHandler:
def __init__(self, filename, mode, encoding=None, delay=0):
"""Use the specified filename for streamed logging"""
if codecs is None:
encoding = None
ConcurrentRotatingFileHandler.__init__(self, filename, mode, encoding, delay)
self.suffix = '%Y-%m-%... | the_stack_v2_python_sparse | utilPackage/utilLog/classLogMgr.py | wangxindev/apiServer | train | 1 | |
0a1a023e88e4ea6742fa0ed7791e517e3065cb0e | [
"logger.debug('Visiting %s', self.novel_url)\nsoup = self.get_soup(self.novel_url)\nself.novel_title = soup.select_one('h1.bookinfo-title').text.strip()\nlogger.info('Novel title: %s', self.novel_title)\nself.novel_author = soup.select_one('span', {'itemprop': 'creator'}).text.strip()\nlogger.info('Novel author: %s... | <|body_start_0|>
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('h1.bookinfo-title').text.strip()
logger.info('Novel title: %s', self.novel_title)
self.novel_author = soup.select_one('span', {'itemprop': 'creato... | NovelCool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NovelCool:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_020693 | 2,362 | permissive | [
{
"docstring": "Get novel title, autor, cover etc",
"name": "read_novel_info",
"signature": "def read_novel_info(self)"
},
{
"docstring": "Download body of a single chapter and return as clean html format.",
"name": "download_chapter_body",
"signature": "def download_chapter_body(self, c... | 2 | stack_v2_sparse_classes_30k_train_015754 | Implement the Python class `NovelCool` described below.
Class description:
Implement the NovelCool class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean html format. | Implement the Python class `NovelCool` described below.
Class description:
Implement the NovelCool class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean html format.
<|s... | 451e816ab03c8466be90f6f0b3eaa52d799140ce | <|skeleton|>
class NovelCool:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NovelCool:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('h1.bookinfo-title').text.strip()
logger.info('Novel title: %s', self.novel_... | the_stack_v2_python_sparse | lncrawl/sources/novelcool.py | NNTin/lightnovel-crawler | train | 2 | |
d118d974bd80a86234af86120d34ef80603c890f | [
"if dialect.name == 'postgresql':\n return dialect.type_descriptor(sqlalchemy.dialects.postgresql.UUID)\nreturn dialect.type_descriptor(String)",
"if dialect.name == 'postgres':\n return value\nif value is None:\n return value\nreturn str(value)",
"if dialect.name == 'postgresql':\n return value\nif... | <|body_start_0|>
if dialect.name == 'postgresql':
return dialect.type_descriptor(sqlalchemy.dialects.postgresql.UUID)
return dialect.type_descriptor(String)
<|end_body_0|>
<|body_start_1|>
if dialect.name == 'postgres':
return value
if value is None:
... | Converts UUID to string before storing to database. Converts string to UUID when retrieving from database. | UUID | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UUID:
"""Converts UUID to string before storing to database. Converts string to UUID when retrieving from database."""
def load_dialect_impl(self, dialect):
"""When using Postgres database, use the Postgres UUID column type. Otherwise, use String column type."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_020694 | 1,449 | permissive | [
{
"docstring": "When using Postgres database, use the Postgres UUID column type. Otherwise, use String column type.",
"name": "load_dialect_impl",
"signature": "def load_dialect_impl(self, dialect)"
},
{
"docstring": "When using Postgres database, no conversion. Otherwise, convert to string befo... | 3 | stack_v2_sparse_classes_30k_train_018746 | Implement the Python class `UUID` described below.
Class description:
Converts UUID to string before storing to database. Converts string to UUID when retrieving from database.
Method signatures and docstrings:
- def load_dialect_impl(self, dialect): When using Postgres database, use the Postgres UUID column type. Ot... | Implement the Python class `UUID` described below.
Class description:
Converts UUID to string before storing to database. Converts string to UUID when retrieving from database.
Method signatures and docstrings:
- def load_dialect_impl(self, dialect): When using Postgres database, use the Postgres UUID column type. Ot... | 665d39a2bd82543d5196555f0801ef8fd4a3ee48 | <|skeleton|>
class UUID:
"""Converts UUID to string before storing to database. Converts string to UUID when retrieving from database."""
def load_dialect_impl(self, dialect):
"""When using Postgres database, use the Postgres UUID column type. Otherwise, use String column type."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UUID:
"""Converts UUID to string before storing to database. Converts string to UUID when retrieving from database."""
def load_dialect_impl(self, dialect):
"""When using Postgres database, use the Postgres UUID column type. Otherwise, use String column type."""
if dialect.name == 'postgr... | the_stack_v2_python_sparse | all-gists/9262225/snippet.py | gistable/gistable | train | 76 |
3681cb6c081bb8a31dc2cd5b762e7f4c6d8a005d | [
"Thread.__init__(self)\nself.setDaemon(True)\nself.output = output\nself.done = False",
"while not self.done:\n input_text = input()\n if input_text:\n _send(self.output, input_text + '\\r\\n')"
] | <|body_start_0|>
Thread.__init__(self)
self.setDaemon(True)
self.output = output
self.done = False
<|end_body_0|>
<|body_start_1|>
while not self.done:
input_text = input()
if input_text:
_send(self.output, input_text + '\r\n')
<|end_body_... | A class that mirrors standard input to the chat server until it's told to stop. | PropagateStandardInput | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropagateStandardInput:
"""A class that mirrors standard input to the chat server until it's told to stop."""
def __init__(self, output):
"""Make this thread a daemon thread, so that if the Python interpreter needs to quit it won't be held up waiting for this thread to die."""
... | stack_v2_sparse_classes_36k_train_020695 | 2,957 | permissive | [
{
"docstring": "Make this thread a daemon thread, so that if the Python interpreter needs to quit it won't be held up waiting for this thread to die.",
"name": "__init__",
"signature": "def __init__(self, output)"
},
{
"docstring": "Echo standard input to the chat server until told to stop.",
... | 2 | stack_v2_sparse_classes_30k_train_000383 | Implement the Python class `PropagateStandardInput` described below.
Class description:
A class that mirrors standard input to the chat server until it's told to stop.
Method signatures and docstrings:
- def __init__(self, output): Make this thread a daemon thread, so that if the Python interpreter needs to quit it w... | Implement the Python class `PropagateStandardInput` described below.
Class description:
A class that mirrors standard input to the chat server until it's told to stop.
Method signatures and docstrings:
- def __init__(self, output): Make this thread a daemon thread, so that if the Python interpreter needs to quit it w... | df7e1ff1739bf32d896faecbb2b7554dd4f9e214 | <|skeleton|>
class PropagateStandardInput:
"""A class that mirrors standard input to the chat server until it's told to stop."""
def __init__(self, output):
"""Make this thread a daemon thread, so that if the Python interpreter needs to quit it won't be held up waiting for this thread to die."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PropagateStandardInput:
"""A class that mirrors standard input to the chat server until it's told to stop."""
def __init__(self, output):
"""Make this thread a daemon thread, so that if the Python interpreter needs to quit it won't be held up waiting for this thread to die."""
Thread.__in... | the_stack_v2_python_sparse | cookbook/network/chat_client.py | fyabc/Toys | train | 1 |
a34831456df7220cf831a8265786bce62d6e91d0 | [
"default_attr = {'keep_slides': None, 'discard_slides': []}\ndefault_attr.update(kwargs)\nsuper().__init__(default_attr=default_attr)\nself.gc = gc\nself.source_folder_id = source_folder_id\nself.set_slide_ids()",
"resp = self.gc.get('item?folderId=%s&limit=1000000' % self.source_folder_id)\nself.slide_ids = {j['... | <|body_start_0|>
default_attr = {'keep_slides': None, 'discard_slides': []}
default_attr.update(kwargs)
super().__init__(default_attr=default_attr)
self.gc = gc
self.source_folder_id = source_folder_id
self.set_slide_ids()
<|end_body_0|>
<|body_start_1|>
resp = s... | Iterate through large_image items in a girder folder. | Slide_iterator | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Slide_iterator:
"""Iterate through large_image items in a girder folder."""
def __init__(self, gc, source_folder_id, **kwargs):
"""Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder_id : str girder ID of folder in which slides are located... | stack_v2_sparse_classes_36k_train_020696 | 8,437 | permissive | [
{
"docstring": "Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder_id : str girder ID of folder in which slides are located keep_slides : list List of slide names to keep. If None, all are kept. discard_slides : list List of slide names to discard. kwargs : key-valu... | 3 | stack_v2_sparse_classes_30k_train_010568 | Implement the Python class `Slide_iterator` described below.
Class description:
Iterate through large_image items in a girder folder.
Method signatures and docstrings:
- def __init__(self, gc, source_folder_id, **kwargs): Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder... | Implement the Python class `Slide_iterator` described below.
Class description:
Iterate through large_image items in a girder folder.
Method signatures and docstrings:
- def __init__(self, gc, source_folder_id, **kwargs): Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder... | c03c852e72f1497d22535c6b7d5aba25c74e620d | <|skeleton|>
class Slide_iterator:
"""Iterate through large_image items in a girder folder."""
def __init__(self, gc, source_folder_id, **kwargs):
"""Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder_id : str girder ID of folder in which slides are located... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Slide_iterator:
"""Iterate through large_image items in a girder folder."""
def __init__(self, gc, source_folder_id, **kwargs):
"""Init Slide_iterator object. Arguments ----------- gc : object girder client object source_folder_id : str girder ID of folder in which slides are located keep_slides ... | the_stack_v2_python_sparse | histomicstk/workflows/workflow_runner.py | DigitalSlideArchive/HistomicsTK | train | 351 |
572d5d12bb177bc53625d3de3b5fa50ae218e790 | [
"self.dist = dist\nself.alias_initialisation()\nself.table_prob_list = list(self.table_prob)",
"n = len(self.dist)\nself.table_prob = {}\nself.table_alias = {}\nscaled_prob = {}\nsmall = []\nlarge = []\nfor o, p in self.dist.items():\n scaled_prob[o] = Decimal(p) * n\n if scaled_prob[o] < 1:\n small.... | <|body_start_0|>
self.dist = dist
self.alias_initialisation()
self.table_prob_list = list(self.table_prob)
<|end_body_0|>
<|body_start_1|>
n = len(self.dist)
self.table_prob = {}
self.table_alias = {}
scaled_prob = {}
small = []
large = []
... | A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/). | VoseAlias | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VoseAlias:
"""A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/)."""
def __init__(self, dist):
""... | stack_v2_sparse_classes_36k_train_020697 | 9,862 | permissive | [
{
"docstring": "Given a definition try matching a word to the definition :) Parameters ---------- key : str Your dictionary.com api key wordlist : str Path to any wordlist you want by default it uses the OSX built in word list Raises ------ TypeError If the randomly generated word is not found on dictionary.com... | 4 | stack_v2_sparse_classes_30k_train_013001 | Implement the Python class `VoseAlias` described below.
Class description:
A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/).
Meth... | Implement the Python class `VoseAlias` described below.
Class description:
A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/).
Meth... | c61bbe8a41dcd76898813c846ea99a275d0af6f3 | <|skeleton|>
class VoseAlias:
"""A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/)."""
def __init__(self, dist):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VoseAlias:
"""A probability distribution for discrete weighted random variables and its probability/alias tables for efficient sampling via Vose's Alias Method (a good explanation of which can be found at http://www.keithschwarz.com/darts-dice-coins/)."""
def __init__(self, dist):
"""Given a defi... | the_stack_v2_python_sparse | src/dictogram.py | imthaghost/tweetGen | train | 1 |
b3142e8642d2a6f5aa3657bc549a46a7b6aab754 | [
"collection: Final[str] = 'profile_armor_map'\nquery = Query(collection, service_id=self._client.service_id)\nquery.add_term(field=self.id_field, value=self.id)\nquery.limit(20)\njoin = query.create_join(ArmourInfo.collection)\njoin.set_fields(ArmourInfo.id_field)\nreturn SequenceProxy(ArmourInfo, query, client=sel... | <|body_start_0|>
collection: Final[str] = 'profile_armor_map'
query = Query(collection, service_id=self._client.service_id)
query.add_term(field=self.id_field, value=self.id)
query.limit(20)
join = query.create_join(ArmourInfo.collection)
join.set_fields(ArmourInfo.id_fie... | An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium nodes or pumpkins. .. attribute:: id... | Profile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium n... | stack_v2_sparse_classes_36k_train_020698 | 5,971 | permissive | [
{
"docstring": "Return the armour info of the profile. This returns a :class:`auraxium.SequenceProxy`.",
"name": "armour_info",
"signature": "def armour_info(self) -> SequenceProxy[ArmourInfo]"
},
{
"docstring": "Return the resist info of the profile. This returns a :class:`auraxium.SequenceProx... | 2 | stack_v2_sparse_classes_30k_train_005304 | Implement the Python class `Profile` described below.
Class description:
An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as othe... | Implement the Python class `Profile` described below.
Class description:
An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as othe... | 23dcf927a199c8d7c917d89fe96b470a34cf4bba | <|skeleton|>
class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium nodes or pumpk... | the_stack_v2_python_sparse | auraxium/ps2/_profile.py | leonhard-s/auraxium | train | 29 |
ef8495f4415279d10c485d25a04cdbe32618085a | [
"if threshold is None:\n threshold = self._threshold\nif self._classifier is not None:\n top_matches = min(top_matches, self._matcher_tup.length - 1)\n dists, inds = self._classifier.search(np.array(emb).astype('float32'), k=top_matches)\n dists = np.squeeze(dists).tolist()\n inds = np.squeeze(inds).... | <|body_start_0|>
if threshold is None:
threshold = self._threshold
if self._classifier is not None:
top_matches = min(top_matches, self._matcher_tup.length - 1)
dists, inds = self._classifier.search(np.array(emb).astype('float32'), k=top_matches)
dists = n... | Classify face id using Faiss | FaissMatcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
<|body_0|>
def fit(self, embs, labels):
"""Fit current matc... | stack_v2_sparse_classes_36k_train_020699 | 16,051 | no_license | [
{
"docstring": "See superclass doc",
"name": "match",
"signature": "def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True)"
},
{
"docstring": "Fit current matcher to new embs and labels :param embs: list of embs :param lab... | 3 | stack_v2_sparse_classes_30k_train_007793 | Implement the Python class `FaissMatcher` described below.
Class description:
Classify face id using Faiss
Method signatures and docstrings:
- def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True): See superclass doc
- def fit(self, embs, labe... | Implement the Python class `FaissMatcher` described below.
Class description:
Classify face id using Faiss
Method signatures and docstrings:
- def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True): See superclass doc
- def fit(self, embs, labe... | 0f97af4e110b0e8de8d1b9f18fcd3f69c69b54cc | <|skeleton|>
class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
<|body_0|>
def fit(self, embs, labels):
"""Fit current matc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FaissMatcher:
"""Classify face id using Faiss"""
def match(self, emb, top_matches=Config.Matcher.MAX_TOP_MATCHES, threshold=None, return_dists=False, always_return_closest=True):
"""See superclass doc"""
if threshold is None:
threshold = self._threshold
if self._classi... | the_stack_v2_python_sparse | src/matcher.py | duongle98/Face-Rec | train | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.