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NeptuneDataClient#

Index > NeptuneData > NeptuneDataClient

Auto-generated documentation for NeptuneData type annotations stubs module mypy-boto3-neptunedata.

NeptuneDataClient#

Type annotations and code completion for boto3.client("neptunedata"). boto3 documentation

# NeptuneDataClient usage example

from boto3.session import Session
from mypy_boto3_neptunedata.client import NeptuneDataClient

def get_neptunedata_client() -> NeptuneDataClient:
    return Session().client("neptunedata")

Exceptions#

boto3 client exceptions are generated in runtime. This class provides code completion for boto3.client("neptunedata").exceptions structure.

# Exceptions.exceptions usage example

client = boto3.client("neptunedata")

try:
    do_something(client)
except (
    client.exceptions.AccessDeniedException,
    client.exceptions.BadRequestException,
    client.exceptions.BulkLoadIdNotFoundException,
    client.exceptions.CancelledByUserException,
    client.exceptions.ClientError,
    client.exceptions.ClientTimeoutException,
    client.exceptions.ConcurrentModificationException,
    client.exceptions.ConstraintViolationException,
    client.exceptions.ExpiredStreamException,
    client.exceptions.FailureByQueryException,
    client.exceptions.IllegalArgumentException,
    client.exceptions.InternalFailureException,
    client.exceptions.InvalidArgumentException,
    client.exceptions.InvalidNumericDataException,
    client.exceptions.InvalidParameterException,
    client.exceptions.LoadUrlAccessDeniedException,
    client.exceptions.MLResourceNotFoundException,
    client.exceptions.MalformedQueryException,
    client.exceptions.MemoryLimitExceededException,
    client.exceptions.MethodNotAllowedException,
    client.exceptions.MissingParameterException,
    client.exceptions.ParsingException,
    client.exceptions.PreconditionsFailedException,
    client.exceptions.QueryLimitExceededException,
    client.exceptions.QueryLimitException,
    client.exceptions.QueryTooLargeException,
    client.exceptions.ReadOnlyViolationException,
    client.exceptions.S3Exception,
    client.exceptions.ServerShutdownException,
    client.exceptions.StatisticsNotAvailableException,
    client.exceptions.StreamRecordsNotFoundException,
    client.exceptions.ThrottlingException,
    client.exceptions.TimeLimitExceededException,
    client.exceptions.TooManyRequestsException,
    client.exceptions.UnsupportedOperationException,
) as e:
    print(e)
# Exceptions.exceptions type checking example

from mypy_boto3_neptunedata.client import Exceptions

def handle_error(exc: Exceptions.AccessDeniedException) -> None:
    ...

Methods#

can_paginate#

Check if an operation can be paginated.

Type annotations and code completion for boto3.client("neptunedata").can_paginate method. boto3 documentation

# can_paginate method definition

def can_paginate(
    self,
    operation_name: str,
) -> bool:
    ...

cancel_gremlin_query#

Cancels a Gremlin query.

Type annotations and code completion for boto3.client("neptunedata").cancel_gremlin_query method. boto3 documentation

# cancel_gremlin_query method definition

def cancel_gremlin_query(
    self,
    *,
    queryId: str,
) -> CancelGremlinQueryOutputTypeDef:  # (1)
    ...
  1. See CancelGremlinQueryOutputTypeDef 
# cancel_gremlin_query method usage example with argument unpacking

kwargs: CancelGremlinQueryInputRequestTypeDef = {  # (1)
    "queryId": ...,
}

parent.cancel_gremlin_query(**kwargs)
  1. See CancelGremlinQueryInputRequestTypeDef

cancel_loader_job#

Cancels a specified load job.

Type annotations and code completion for boto3.client("neptunedata").cancel_loader_job method. boto3 documentation

# cancel_loader_job method definition

def cancel_loader_job(
    self,
    *,
    loadId: str,
) -> CancelLoaderJobOutputTypeDef:  # (1)
    ...
  1. See CancelLoaderJobOutputTypeDef 
# cancel_loader_job method usage example with argument unpacking

kwargs: CancelLoaderJobInputRequestTypeDef = {  # (1)
    "loadId": ...,
}

parent.cancel_loader_job(**kwargs)
  1. See CancelLoaderJobInputRequestTypeDef

cancel_ml_data_processing_job#

Cancels a Neptune ML data processing job.

Type annotations and code completion for boto3.client("neptunedata").cancel_ml_data_processing_job method. boto3 documentation

# cancel_ml_data_processing_job method definition

def cancel_ml_data_processing_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
    clean: bool = ...,
) -> CancelMLDataProcessingJobOutputTypeDef:  # (1)
    ...
  1. See CancelMLDataProcessingJobOutputTypeDef 
# cancel_ml_data_processing_job method usage example with argument unpacking

kwargs: CancelMLDataProcessingJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.cancel_ml_data_processing_job(**kwargs)
  1. See CancelMLDataProcessingJobInputRequestTypeDef

cancel_ml_model_training_job#

Cancels a Neptune ML model training job.

Type annotations and code completion for boto3.client("neptunedata").cancel_ml_model_training_job method. boto3 documentation

# cancel_ml_model_training_job method definition

def cancel_ml_model_training_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
    clean: bool = ...,
) -> CancelMLModelTrainingJobOutputTypeDef:  # (1)
    ...
  1. See CancelMLModelTrainingJobOutputTypeDef 
# cancel_ml_model_training_job method usage example with argument unpacking

kwargs: CancelMLModelTrainingJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.cancel_ml_model_training_job(**kwargs)
  1. See CancelMLModelTrainingJobInputRequestTypeDef

cancel_ml_model_transform_job#

Cancels a specified model transform job.

Type annotations and code completion for boto3.client("neptunedata").cancel_ml_model_transform_job method. boto3 documentation

# cancel_ml_model_transform_job method definition

def cancel_ml_model_transform_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
    clean: bool = ...,
) -> CancelMLModelTransformJobOutputTypeDef:  # (1)
    ...
  1. See CancelMLModelTransformJobOutputTypeDef 
# cancel_ml_model_transform_job method usage example with argument unpacking

kwargs: CancelMLModelTransformJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.cancel_ml_model_transform_job(**kwargs)
  1. See CancelMLModelTransformJobInputRequestTypeDef

cancel_open_cypher_query#

Cancels a specified openCypher query.

Type annotations and code completion for boto3.client("neptunedata").cancel_open_cypher_query method. boto3 documentation

# cancel_open_cypher_query method definition

def cancel_open_cypher_query(
    self,
    *,
    queryId: str,
    silent: bool = ...,
) -> CancelOpenCypherQueryOutputTypeDef:  # (1)
    ...
  1. See CancelOpenCypherQueryOutputTypeDef 
# cancel_open_cypher_query method usage example with argument unpacking

kwargs: CancelOpenCypherQueryInputRequestTypeDef = {  # (1)
    "queryId": ...,
}

parent.cancel_open_cypher_query(**kwargs)
  1. See CancelOpenCypherQueryInputRequestTypeDef

close#

Closes underlying endpoint connections.

Type annotations and code completion for boto3.client("neptunedata").close method. boto3 documentation

# close method definition

def close(
    self,
) -> None:
    ...

create_ml_endpoint#

Creates a new Neptune ML inference endpoint that lets you query one specific model that the model-training process constructed.

Type annotations and code completion for boto3.client("neptunedata").create_ml_endpoint method. boto3 documentation

# create_ml_endpoint method definition

def create_ml_endpoint(
    self,
    *,
    id: str = ...,
    mlModelTrainingJobId: str = ...,
    mlModelTransformJobId: str = ...,
    update: bool = ...,
    neptuneIamRoleArn: str = ...,
    modelName: str = ...,
    instanceType: str = ...,
    instanceCount: int = ...,
    volumeEncryptionKMSKey: str = ...,
) -> CreateMLEndpointOutputTypeDef:  # (1)
    ...
  1. See CreateMLEndpointOutputTypeDef 
# create_ml_endpoint method usage example with argument unpacking

kwargs: CreateMLEndpointInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.create_ml_endpoint(**kwargs)
  1. See CreateMLEndpointInputRequestTypeDef

delete_ml_endpoint#

Cancels the creation of a Neptune ML inference endpoint.

Type annotations and code completion for boto3.client("neptunedata").delete_ml_endpoint method. boto3 documentation

# delete_ml_endpoint method definition

def delete_ml_endpoint(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
    clean: bool = ...,
) -> DeleteMLEndpointOutputTypeDef:  # (1)
    ...
  1. See DeleteMLEndpointOutputTypeDef 
# delete_ml_endpoint method usage example with argument unpacking

kwargs: DeleteMLEndpointInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.delete_ml_endpoint(**kwargs)
  1. See DeleteMLEndpointInputRequestTypeDef

delete_propertygraph_statistics#

Deletes statistics for Gremlin and openCypher (property graph) data.

Type annotations and code completion for boto3.client("neptunedata").delete_propertygraph_statistics method. boto3 documentation

# delete_propertygraph_statistics method definition

def delete_propertygraph_statistics(
    self,
) -> DeletePropertygraphStatisticsOutputTypeDef:  # (1)
    ...
  1. See DeletePropertygraphStatisticsOutputTypeDef

delete_sparql_statistics#

Deletes SPARQL statistics When invoking this operation in a Neptune cluster that has IAM authentication enabled, the IAM user or role making the request must have a policy attached that allows the neptune-db:DeleteStatistics <https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actio....

Type annotations and code completion for boto3.client("neptunedata").delete_sparql_statistics method. boto3 documentation

# delete_sparql_statistics method definition

def delete_sparql_statistics(
    self,
) -> DeleteSparqlStatisticsOutputTypeDef:  # (1)
    ...
  1. See DeleteSparqlStatisticsOutputTypeDef

execute_fast_reset#

The fast reset REST API lets you reset a Neptune graph quicky and easily, removing all of its data.

Type annotations and code completion for boto3.client("neptunedata").execute_fast_reset method. boto3 documentation

# execute_fast_reset method definition

def execute_fast_reset(
    self,
    *,
    action: ActionType,  # (1)
    token: str = ...,
) -> ExecuteFastResetOutputTypeDef:  # (2)
    ...
  1. See ActionType
  2. See ExecuteFastResetOutputTypeDef 
# execute_fast_reset method usage example with argument unpacking

kwargs: ExecuteFastResetInputRequestTypeDef = {  # (1)
    "action": ...,
}

parent.execute_fast_reset(**kwargs)
  1. See ExecuteFastResetInputRequestTypeDef

execute_gremlin_explain_query#

Executes a Gremlin Explain query.

Type annotations and code completion for boto3.client("neptunedata").execute_gremlin_explain_query method. boto3 documentation

# execute_gremlin_explain_query method definition

def execute_gremlin_explain_query(
    self,
    *,
    gremlinQuery: str,
) -> ExecuteGremlinExplainQueryOutputTypeDef:  # (1)
    ...
  1. See ExecuteGremlinExplainQueryOutputTypeDef 
# execute_gremlin_explain_query method usage example with argument unpacking

kwargs: ExecuteGremlinExplainQueryInputRequestTypeDef = {  # (1)
    "gremlinQuery": ...,
}

parent.execute_gremlin_explain_query(**kwargs)
  1. See ExecuteGremlinExplainQueryInputRequestTypeDef

execute_gremlin_profile_query#

Executes a Gremlin Profile query, which runs a specified traversal, collects various metrics about the run, and produces a profile report as output.

Type annotations and code completion for boto3.client("neptunedata").execute_gremlin_profile_query method. boto3 documentation

# execute_gremlin_profile_query method definition

def execute_gremlin_profile_query(
    self,
    *,
    gremlinQuery: str,
    results: bool = ...,
    chop: int = ...,
    serializer: str = ...,
    indexOps: bool = ...,
) -> ExecuteGremlinProfileQueryOutputTypeDef:  # (1)
    ...
  1. See ExecuteGremlinProfileQueryOutputTypeDef 
# execute_gremlin_profile_query method usage example with argument unpacking

kwargs: ExecuteGremlinProfileQueryInputRequestTypeDef = {  # (1)
    "gremlinQuery": ...,
}

parent.execute_gremlin_profile_query(**kwargs)
  1. See ExecuteGremlinProfileQueryInputRequestTypeDef

execute_gremlin_query#

This commands executes a Gremlin query.

Type annotations and code completion for boto3.client("neptunedata").execute_gremlin_query method. boto3 documentation

# execute_gremlin_query method definition

def execute_gremlin_query(
    self,
    *,
    gremlinQuery: str,
    serializer: str = ...,
) -> ExecuteGremlinQueryOutputTypeDef:  # (1)
    ...
  1. See ExecuteGremlinQueryOutputTypeDef 
# execute_gremlin_query method usage example with argument unpacking

kwargs: ExecuteGremlinQueryInputRequestTypeDef = {  # (1)
    "gremlinQuery": ...,
}

parent.execute_gremlin_query(**kwargs)
  1. See ExecuteGremlinQueryInputRequestTypeDef

execute_open_cypher_explain_query#

Executes an openCypher explain request.

Type annotations and code completion for boto3.client("neptunedata").execute_open_cypher_explain_query method. boto3 documentation

# execute_open_cypher_explain_query method definition

def execute_open_cypher_explain_query(
    self,
    *,
    openCypherQuery: str,
    explainMode: OpenCypherExplainModeType,  # (1)
    parameters: str = ...,
) -> ExecuteOpenCypherExplainQueryOutputTypeDef:  # (2)
    ...
  1. See OpenCypherExplainModeType
  2. See ExecuteOpenCypherExplainQueryOutputTypeDef 
# execute_open_cypher_explain_query method usage example with argument unpacking

kwargs: ExecuteOpenCypherExplainQueryInputRequestTypeDef = {  # (1)
    "openCypherQuery": ...,
    "explainMode": ...,
}

parent.execute_open_cypher_explain_query(**kwargs)
  1. See ExecuteOpenCypherExplainQueryInputRequestTypeDef

execute_open_cypher_query#

Executes an openCypher query.

Type annotations and code completion for boto3.client("neptunedata").execute_open_cypher_query method. boto3 documentation

# execute_open_cypher_query method definition

def execute_open_cypher_query(
    self,
    *,
    openCypherQuery: str,
    parameters: str = ...,
) -> ExecuteOpenCypherQueryOutputTypeDef:  # (1)
    ...
  1. See ExecuteOpenCypherQueryOutputTypeDef 
# execute_open_cypher_query method usage example with argument unpacking

kwargs: ExecuteOpenCypherQueryInputRequestTypeDef = {  # (1)
    "openCypherQuery": ...,
}

parent.execute_open_cypher_query(**kwargs)
  1. See ExecuteOpenCypherQueryInputRequestTypeDef

generate_presigned_url#

Generate a presigned url given a client, its method, and arguments.

Type annotations and code completion for boto3.client("neptunedata").generate_presigned_url method. boto3 documentation

# generate_presigned_url method definition

def generate_presigned_url(
    self,
    ClientMethod: str,
    Params: Mapping[str, Any] = ...,
    ExpiresIn: int = 3600,
    HttpMethod: str = ...,
) -> str:
    ...

get_engine_status#

Retrieves the status of the graph database on the host.

Type annotations and code completion for boto3.client("neptunedata").get_engine_status method. boto3 documentation

# get_engine_status method definition

def get_engine_status(
    self,
) -> GetEngineStatusOutputTypeDef:  # (1)
    ...
  1. See GetEngineStatusOutputTypeDef

get_gremlin_query_status#

Gets the status of a specified Gremlin query.

Type annotations and code completion for boto3.client("neptunedata").get_gremlin_query_status method. boto3 documentation

# get_gremlin_query_status method definition

def get_gremlin_query_status(
    self,
    *,
    queryId: str,
) -> GetGremlinQueryStatusOutputTypeDef:  # (1)
    ...
  1. See GetGremlinQueryStatusOutputTypeDef 
# get_gremlin_query_status method usage example with argument unpacking

kwargs: GetGremlinQueryStatusInputRequestTypeDef = {  # (1)
    "queryId": ...,
}

parent.get_gremlin_query_status(**kwargs)
  1. See GetGremlinQueryStatusInputRequestTypeDef

get_loader_job_status#

Gets status information about a specified load job.

Type annotations and code completion for boto3.client("neptunedata").get_loader_job_status method. boto3 documentation

# get_loader_job_status method definition

def get_loader_job_status(
    self,
    *,
    loadId: str,
    details: bool = ...,
    errors: bool = ...,
    page: int = ...,
    errorsPerPage: int = ...,
) -> GetLoaderJobStatusOutputTypeDef:  # (1)
    ...
  1. See GetLoaderJobStatusOutputTypeDef 
# get_loader_job_status method usage example with argument unpacking

kwargs: GetLoaderJobStatusInputRequestTypeDef = {  # (1)
    "loadId": ...,
}

parent.get_loader_job_status(**kwargs)
  1. See GetLoaderJobStatusInputRequestTypeDef

get_ml_data_processing_job#

Retrieves information about a specified data processing job.

Type annotations and code completion for boto3.client("neptunedata").get_ml_data_processing_job method. boto3 documentation

# get_ml_data_processing_job method definition

def get_ml_data_processing_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
) -> GetMLDataProcessingJobOutputTypeDef:  # (1)
    ...
  1. See GetMLDataProcessingJobOutputTypeDef 
# get_ml_data_processing_job method usage example with argument unpacking

kwargs: GetMLDataProcessingJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.get_ml_data_processing_job(**kwargs)
  1. See GetMLDataProcessingJobInputRequestTypeDef

get_ml_endpoint#

Retrieves details about an inference endpoint.

Type annotations and code completion for boto3.client("neptunedata").get_ml_endpoint method. boto3 documentation

# get_ml_endpoint method definition

def get_ml_endpoint(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
) -> GetMLEndpointOutputTypeDef:  # (1)
    ...
  1. See GetMLEndpointOutputTypeDef 
# get_ml_endpoint method usage example with argument unpacking

kwargs: GetMLEndpointInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.get_ml_endpoint(**kwargs)
  1. See GetMLEndpointInputRequestTypeDef

get_ml_model_training_job#

Retrieves information about a Neptune ML model training job.

Type annotations and code completion for boto3.client("neptunedata").get_ml_model_training_job method. boto3 documentation

# get_ml_model_training_job method definition

def get_ml_model_training_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
) -> GetMLModelTrainingJobOutputTypeDef:  # (1)
    ...
  1. See GetMLModelTrainingJobOutputTypeDef 
# get_ml_model_training_job method usage example with argument unpacking

kwargs: GetMLModelTrainingJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.get_ml_model_training_job(**kwargs)
  1. See GetMLModelTrainingJobInputRequestTypeDef

get_ml_model_transform_job#

Gets information about a specified model transform job.

Type annotations and code completion for boto3.client("neptunedata").get_ml_model_transform_job method. boto3 documentation

# get_ml_model_transform_job method definition

def get_ml_model_transform_job(
    self,
    *,
    id: str,
    neptuneIamRoleArn: str = ...,
) -> GetMLModelTransformJobOutputTypeDef:  # (1)
    ...
  1. See GetMLModelTransformJobOutputTypeDef 
# get_ml_model_transform_job method usage example with argument unpacking

kwargs: GetMLModelTransformJobInputRequestTypeDef = {  # (1)
    "id": ...,
}

parent.get_ml_model_transform_job(**kwargs)
  1. See GetMLModelTransformJobInputRequestTypeDef

get_open_cypher_query_status#

Retrieves the status of a specified openCypher query.

Type annotations and code completion for boto3.client("neptunedata").get_open_cypher_query_status method. boto3 documentation

# get_open_cypher_query_status method definition

def get_open_cypher_query_status(
    self,
    *,
    queryId: str,
) -> GetOpenCypherQueryStatusOutputTypeDef:  # (1)
    ...
  1. See GetOpenCypherQueryStatusOutputTypeDef 
# get_open_cypher_query_status method usage example with argument unpacking

kwargs: GetOpenCypherQueryStatusInputRequestTypeDef = {  # (1)
    "queryId": ...,
}

parent.get_open_cypher_query_status(**kwargs)
  1. See GetOpenCypherQueryStatusInputRequestTypeDef

get_propertygraph_statistics#

Gets property graph statistics (Gremlin and openCypher).

Type annotations and code completion for boto3.client("neptunedata").get_propertygraph_statistics method. boto3 documentation

# get_propertygraph_statistics method definition

def get_propertygraph_statistics(
    self,
) -> GetPropertygraphStatisticsOutputTypeDef:  # (1)
    ...
  1. See GetPropertygraphStatisticsOutputTypeDef

get_propertygraph_stream#

Gets a stream for a property graph.

Type annotations and code completion for boto3.client("neptunedata").get_propertygraph_stream method. boto3 documentation

# get_propertygraph_stream method definition

def get_propertygraph_stream(
    self,
    *,
    limit: int = ...,
    iteratorType: IteratorTypeType = ...,  # (1)
    commitNum: int = ...,
    opNum: int = ...,
    encoding: EncodingType = ...,  # (2)
) -> GetPropertygraphStreamOutputTypeDef:  # (3)
    ...
  1. See IteratorTypeType
  2. See EncodingType
  3. See GetPropertygraphStreamOutputTypeDef 
# get_propertygraph_stream method usage example with argument unpacking

kwargs: GetPropertygraphStreamInputRequestTypeDef = {  # (1)
    "limit": ...,
}

parent.get_propertygraph_stream(**kwargs)
  1. See GetPropertygraphStreamInputRequestTypeDef

get_propertygraph_summary#

Gets a graph summary for a property graph.

Type annotations and code completion for boto3.client("neptunedata").get_propertygraph_summary method. boto3 documentation

# get_propertygraph_summary method definition

def get_propertygraph_summary(
    self,
    *,
    mode: GraphSummaryTypeType = ...,  # (1)
) -> GetPropertygraphSummaryOutputTypeDef:  # (2)
    ...
  1. See GraphSummaryTypeType
  2. See GetPropertygraphSummaryOutputTypeDef 
# get_propertygraph_summary method usage example with argument unpacking

kwargs: GetPropertygraphSummaryInputRequestTypeDef = {  # (1)
    "mode": ...,
}

parent.get_propertygraph_summary(**kwargs)
  1. See GetPropertygraphSummaryInputRequestTypeDef

get_rdf_graph_summary#

Gets a graph summary for an RDF graph.

Type annotations and code completion for boto3.client("neptunedata").get_rdf_graph_summary method. boto3 documentation

# get_rdf_graph_summary method definition

def get_rdf_graph_summary(
    self,
    *,
    mode: GraphSummaryTypeType = ...,  # (1)
) -> GetRDFGraphSummaryOutputTypeDef:  # (2)
    ...
  1. See GraphSummaryTypeType
  2. See GetRDFGraphSummaryOutputTypeDef 
# get_rdf_graph_summary method usage example with argument unpacking

kwargs: GetRDFGraphSummaryInputRequestTypeDef = {  # (1)
    "mode": ...,
}

parent.get_rdf_graph_summary(**kwargs)
  1. See GetRDFGraphSummaryInputRequestTypeDef

get_sparql_statistics#

Gets RDF statistics (SPARQL).

Type annotations and code completion for boto3.client("neptunedata").get_sparql_statistics method. boto3 documentation

# get_sparql_statistics method definition

def get_sparql_statistics(
    self,
) -> GetSparqlStatisticsOutputTypeDef:  # (1)
    ...
  1. See GetSparqlStatisticsOutputTypeDef

get_sparql_stream#

Gets a stream for an RDF graph.

Type annotations and code completion for boto3.client("neptunedata").get_sparql_stream method. boto3 documentation

# get_sparql_stream method definition

def get_sparql_stream(
    self,
    *,
    limit: int = ...,
    iteratorType: IteratorTypeType = ...,  # (1)
    commitNum: int = ...,
    opNum: int = ...,
    encoding: EncodingType = ...,  # (2)
) -> GetSparqlStreamOutputTypeDef:  # (3)
    ...
  1. See IteratorTypeType
  2. See EncodingType
  3. See GetSparqlStreamOutputTypeDef 
# get_sparql_stream method usage example with argument unpacking

kwargs: GetSparqlStreamInputRequestTypeDef = {  # (1)
    "limit": ...,
}

parent.get_sparql_stream(**kwargs)
  1. See GetSparqlStreamInputRequestTypeDef

list_gremlin_queries#

Lists active Gremlin queries.

Type annotations and code completion for boto3.client("neptunedata").list_gremlin_queries method. boto3 documentation

# list_gremlin_queries method definition

def list_gremlin_queries(
    self,
    *,
    includeWaiting: bool = ...,
) -> ListGremlinQueriesOutputTypeDef:  # (1)
    ...
  1. See ListGremlinQueriesOutputTypeDef 
# list_gremlin_queries method usage example with argument unpacking

kwargs: ListGremlinQueriesInputRequestTypeDef = {  # (1)
    "includeWaiting": ...,
}

parent.list_gremlin_queries(**kwargs)
  1. See ListGremlinQueriesInputRequestTypeDef

list_loader_jobs#

Retrieves a list of the loadIds for all active loader jobs.

Type annotations and code completion for boto3.client("neptunedata").list_loader_jobs method. boto3 documentation

# list_loader_jobs method definition

def list_loader_jobs(
    self,
    *,
    limit: int = ...,
    includeQueuedLoads: bool = ...,
) -> ListLoaderJobsOutputTypeDef:  # (1)
    ...
  1. See ListLoaderJobsOutputTypeDef 
# list_loader_jobs method usage example with argument unpacking

kwargs: ListLoaderJobsInputRequestTypeDef = {  # (1)
    "limit": ...,
}

parent.list_loader_jobs(**kwargs)
  1. See ListLoaderJobsInputRequestTypeDef

list_ml_data_processing_jobs#

Returns a list of Neptune ML data processing jobs.

Type annotations and code completion for boto3.client("neptunedata").list_ml_data_processing_jobs method. boto3 documentation

# list_ml_data_processing_jobs method definition

def list_ml_data_processing_jobs(
    self,
    *,
    maxItems: int = ...,
    neptuneIamRoleArn: str = ...,
) -> ListMLDataProcessingJobsOutputTypeDef:  # (1)
    ...
  1. See ListMLDataProcessingJobsOutputTypeDef 
# list_ml_data_processing_jobs method usage example with argument unpacking

kwargs: ListMLDataProcessingJobsInputRequestTypeDef = {  # (1)
    "maxItems": ...,
}

parent.list_ml_data_processing_jobs(**kwargs)
  1. See ListMLDataProcessingJobsInputRequestTypeDef

list_ml_endpoints#

Lists existing inference endpoints.

Type annotations and code completion for boto3.client("neptunedata").list_ml_endpoints method. boto3 documentation

# list_ml_endpoints method definition

def list_ml_endpoints(
    self,
    *,
    maxItems: int = ...,
    neptuneIamRoleArn: str = ...,
) -> ListMLEndpointsOutputTypeDef:  # (1)
    ...
  1. See ListMLEndpointsOutputTypeDef 
# list_ml_endpoints method usage example with argument unpacking

kwargs: ListMLEndpointsInputRequestTypeDef = {  # (1)
    "maxItems": ...,
}

parent.list_ml_endpoints(**kwargs)
  1. See ListMLEndpointsInputRequestTypeDef

list_ml_model_training_jobs#

Lists Neptune ML model-training jobs.

Type annotations and code completion for boto3.client("neptunedata").list_ml_model_training_jobs method. boto3 documentation

# list_ml_model_training_jobs method definition

def list_ml_model_training_jobs(
    self,
    *,
    maxItems: int = ...,
    neptuneIamRoleArn: str = ...,
) -> ListMLModelTrainingJobsOutputTypeDef:  # (1)
    ...
  1. See ListMLModelTrainingJobsOutputTypeDef 
# list_ml_model_training_jobs method usage example with argument unpacking

kwargs: ListMLModelTrainingJobsInputRequestTypeDef = {  # (1)
    "maxItems": ...,
}

parent.list_ml_model_training_jobs(**kwargs)
  1. See ListMLModelTrainingJobsInputRequestTypeDef

list_ml_model_transform_jobs#

Returns a list of model transform job IDs.

Type annotations and code completion for boto3.client("neptunedata").list_ml_model_transform_jobs method. boto3 documentation

# list_ml_model_transform_jobs method definition

def list_ml_model_transform_jobs(
    self,
    *,
    maxItems: int = ...,
    neptuneIamRoleArn: str = ...,
) -> ListMLModelTransformJobsOutputTypeDef:  # (1)
    ...
  1. See ListMLModelTransformJobsOutputTypeDef 
# list_ml_model_transform_jobs method usage example with argument unpacking

kwargs: ListMLModelTransformJobsInputRequestTypeDef = {  # (1)
    "maxItems": ...,
}

parent.list_ml_model_transform_jobs(**kwargs)
  1. See ListMLModelTransformJobsInputRequestTypeDef

list_open_cypher_queries#

Lists active openCypher queries.

Type annotations and code completion for boto3.client("neptunedata").list_open_cypher_queries method. boto3 documentation

# list_open_cypher_queries method definition

def list_open_cypher_queries(
    self,
    *,
    includeWaiting: bool = ...,
) -> ListOpenCypherQueriesOutputTypeDef:  # (1)
    ...
  1. See ListOpenCypherQueriesOutputTypeDef 
# list_open_cypher_queries method usage example with argument unpacking

kwargs: ListOpenCypherQueriesInputRequestTypeDef = {  # (1)
    "includeWaiting": ...,
}

parent.list_open_cypher_queries(**kwargs)
  1. See ListOpenCypherQueriesInputRequestTypeDef

manage_propertygraph_statistics#

Manages the generation and use of property graph statistics.

Type annotations and code completion for boto3.client("neptunedata").manage_propertygraph_statistics method. boto3 documentation

# manage_propertygraph_statistics method definition

def manage_propertygraph_statistics(
    self,
    *,
    mode: StatisticsAutoGenerationModeType = ...,  # (1)
) -> ManagePropertygraphStatisticsOutputTypeDef:  # (2)
    ...
  1. See StatisticsAutoGenerationModeType
  2. See ManagePropertygraphStatisticsOutputTypeDef 
# manage_propertygraph_statistics method usage example with argument unpacking

kwargs: ManagePropertygraphStatisticsInputRequestTypeDef = {  # (1)
    "mode": ...,
}

parent.manage_propertygraph_statistics(**kwargs)
  1. See ManagePropertygraphStatisticsInputRequestTypeDef

manage_sparql_statistics#

Manages the generation and use of RDF graph statistics.

Type annotations and code completion for boto3.client("neptunedata").manage_sparql_statistics method. boto3 documentation

# manage_sparql_statistics method definition

def manage_sparql_statistics(
    self,
    *,
    mode: StatisticsAutoGenerationModeType = ...,  # (1)
) -> ManageSparqlStatisticsOutputTypeDef:  # (2)
    ...
  1. See StatisticsAutoGenerationModeType
  2. See ManageSparqlStatisticsOutputTypeDef 
# manage_sparql_statistics method usage example with argument unpacking

kwargs: ManageSparqlStatisticsInputRequestTypeDef = {  # (1)
    "mode": ...,
}

parent.manage_sparql_statistics(**kwargs)
  1. See ManageSparqlStatisticsInputRequestTypeDef

start_loader_job#

Starts a Neptune bulk loader job to load data from an Amazon S3 bucket into a Neptune DB instance.

Type annotations and code completion for boto3.client("neptunedata").start_loader_job method. boto3 documentation

# start_loader_job method definition

def start_loader_job(
    self,
    *,
    source: str,
    format: FormatType,  # (1)
    s3BucketRegion: S3BucketRegionType,  # (2)
    iamRoleArn: str,
    mode: ModeType = ...,  # (3)
    failOnError: bool = ...,
    parallelism: ParallelismType = ...,  # (4)
    parserConfiguration: Mapping[str, str] = ...,
    updateSingleCardinalityProperties: bool = ...,
    queueRequest: bool = ...,
    dependencies: Sequence[str] = ...,
    userProvidedEdgeIds: bool = ...,
) -> StartLoaderJobOutputTypeDef:  # (5)
    ...
  1. See FormatType
  2. See S3BucketRegionType
  3. See ModeType
  4. See ParallelismType
  5. See StartLoaderJobOutputTypeDef 
# start_loader_job method usage example with argument unpacking

kwargs: StartLoaderJobInputRequestTypeDef = {  # (1)
    "source": ...,
    "format": ...,
    "s3BucketRegion": ...,
    "iamRoleArn": ...,
}

parent.start_loader_job(**kwargs)
  1. See StartLoaderJobInputRequestTypeDef

start_ml_data_processing_job#

Creates a new Neptune ML data processing job for processing the graph data exported from Neptune for training.

Type annotations and code completion for boto3.client("neptunedata").start_ml_data_processing_job method. boto3 documentation

# start_ml_data_processing_job method definition

def start_ml_data_processing_job(
    self,
    *,
    inputDataS3Location: str,
    processedDataS3Location: str,
    id: str = ...,
    previousDataProcessingJobId: str = ...,
    sagemakerIamRoleArn: str = ...,
    neptuneIamRoleArn: str = ...,
    processingInstanceType: str = ...,
    processingInstanceVolumeSizeInGB: int = ...,
    processingTimeOutInSeconds: int = ...,
    modelType: str = ...,
    configFileName: str = ...,
    subnets: Sequence[str] = ...,
    securityGroupIds: Sequence[str] = ...,
    volumeEncryptionKMSKey: str = ...,
    s3OutputEncryptionKMSKey: str = ...,
) -> StartMLDataProcessingJobOutputTypeDef:  # (1)
    ...
  1. See StartMLDataProcessingJobOutputTypeDef 
# start_ml_data_processing_job method usage example with argument unpacking

kwargs: StartMLDataProcessingJobInputRequestTypeDef = {  # (1)
    "inputDataS3Location": ...,
    "processedDataS3Location": ...,
}

parent.start_ml_data_processing_job(**kwargs)
  1. See StartMLDataProcessingJobInputRequestTypeDef

start_ml_model_training_job#

Creates a new Neptune ML model training job.

Type annotations and code completion for boto3.client("neptunedata").start_ml_model_training_job method. boto3 documentation

# start_ml_model_training_job method definition

def start_ml_model_training_job(
    self,
    *,
    dataProcessingJobId: str,
    trainModelS3Location: str,
    id: str = ...,
    previousModelTrainingJobId: str = ...,
    sagemakerIamRoleArn: str = ...,
    neptuneIamRoleArn: str = ...,
    baseProcessingInstanceType: str = ...,
    trainingInstanceType: str = ...,
    trainingInstanceVolumeSizeInGB: int = ...,
    trainingTimeOutInSeconds: int = ...,
    maxHPONumberOfTrainingJobs: int = ...,
    maxHPOParallelTrainingJobs: int = ...,
    subnets: Sequence[str] = ...,
    securityGroupIds: Sequence[str] = ...,
    volumeEncryptionKMSKey: str = ...,
    s3OutputEncryptionKMSKey: str = ...,
    enableManagedSpotTraining: bool = ...,
    customModelTrainingParameters: CustomModelTrainingParametersTypeDef = ...,  # (1)
) -> StartMLModelTrainingJobOutputTypeDef:  # (2)
    ...
  1. See CustomModelTrainingParametersTypeDef
  2. See StartMLModelTrainingJobOutputTypeDef 
# start_ml_model_training_job method usage example with argument unpacking

kwargs: StartMLModelTrainingJobInputRequestTypeDef = {  # (1)
    "dataProcessingJobId": ...,
    "trainModelS3Location": ...,
}

parent.start_ml_model_training_job(**kwargs)
  1. See StartMLModelTrainingJobInputRequestTypeDef

start_ml_model_transform_job#

Creates a new model transform job.

Type annotations and code completion for boto3.client("neptunedata").start_ml_model_transform_job method. boto3 documentation

# start_ml_model_transform_job method definition

def start_ml_model_transform_job(
    self,
    *,
    modelTransformOutputS3Location: str,
    id: str = ...,
    dataProcessingJobId: str = ...,
    mlModelTrainingJobId: str = ...,
    trainingJobName: str = ...,
    sagemakerIamRoleArn: str = ...,
    neptuneIamRoleArn: str = ...,
    customModelTransformParameters: CustomModelTransformParametersTypeDef = ...,  # (1)
    baseProcessingInstanceType: str = ...,
    baseProcessingInstanceVolumeSizeInGB: int = ...,
    subnets: Sequence[str] = ...,
    securityGroupIds: Sequence[str] = ...,
    volumeEncryptionKMSKey: str = ...,
    s3OutputEncryptionKMSKey: str = ...,
) -> StartMLModelTransformJobOutputTypeDef:  # (2)
    ...
  1. See CustomModelTransformParametersTypeDef
  2. See StartMLModelTransformJobOutputTypeDef 
# start_ml_model_transform_job method usage example with argument unpacking

kwargs: StartMLModelTransformJobInputRequestTypeDef = {  # (1)
    "modelTransformOutputS3Location": ...,
}

parent.start_ml_model_transform_job(**kwargs)
  1. See StartMLModelTransformJobInputRequestTypeDef