Class WarehouseClient (0.1.0)

Service that manages media content + metadata for streaming.

Return the API endpoint used by the client instance.

Returns the transport used by the client instance.

Return the universe domain used by the client instance.

Instantiates the warehouse client.

Releases underlying transport's resources.

Returns a fully-qualified annotation string.

Returns a fully-qualified asset string.

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Generates clips for downloading. The api takes in a time range, and generates a clip of the first content available after start_time and before end_time, which may overflow beyond these bounds. Returned clips are truncated if the total size of the clips are larger than 100MB.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_clip_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ClipAssetRequest(
        name="name_value",
    )

    # Make the request
    response = client.clip_asset(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Returns a fully-qualified corpus string.

Creates annotation inside asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_create_annotation():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.CreateAnnotationRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_annotation(request=request)

    # Handle the response
    print(response)

Creates an asset inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_create_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.CreateAssetRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_asset(request=request)

    # Handle the response
    print(response)

Creates a corpus inside a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_create_corpus():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    corpus = visionai_v1alpha1.Corpus()
    corpus.display_name = "display_name_value"

    request = visionai_v1alpha1.CreateCorpusRequest(
        parent="parent_value",
        corpus=corpus,
    )

    # Make the request
    operation = client.create_corpus(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

Creates data schema inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_create_data_schema():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    data_schema = visionai_v1alpha1.DataSchema()
    data_schema.key = "key_value"

    request = visionai_v1alpha1.CreateDataSchemaRequest(
        parent="parent_value",
        data_schema=data_schema,
    )

    # Make the request
    response = client.create_data_schema(request=request)

    # Handle the response
    print(response)

Creates a search configuration inside a corpus.

Please follow the rules below to create a valid CreateSearchConfigRequest. --- General Rules ---

1. Request.search_config_id must not be associated with an existing SearchConfig.
2. Request must contain at least one non-empty search_criteria_property or facet_property.
3. mapped_fields must not be empty, and must map to existing UGA keys.
4. All mapped_fields must be of the same type.
5. All mapped_fields must share the same granularity.
6. All mapped_fields must share the same semantic SearchConfig match options. For property-specific rules, please reference the comments for FacetProperty and SearchCriteriaProperty.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_create_search_config():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.CreateSearchConfigRequest(
        parent="parent_value",
        search_config_id="search_config_id_value",
    )

    # Make the request
    response = client.create_search_config(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified data_schema string.

Deletes annotation inside asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_delete_annotation():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.DeleteAnnotationRequest(
        name="name_value",
    )

    # Make the request
    client.delete_annotation(request=request)

Deletes asset inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_delete_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.DeleteAssetRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_asset(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

Deletes a corpus only if its empty. Returns empty response.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_delete_corpus():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.DeleteCorpusRequest(
        name="name_value",
    )

    # Make the request
    client.delete_corpus(request=request)

Deletes data schema inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_delete_data_schema():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.DeleteDataSchemaRequest(
        name="name_value",
    )

    # Make the request
    client.delete_data_schema(request=request)

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Deletes a search configuration inside a corpus.

For a DeleteSearchConfigRequest to be valid, Request.search_configuration.name must already exist.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_delete_search_config():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.DeleteSearchConfigRequest(
        name="name_value",
    )

    # Make the request
    client.delete_search_config(request=request)

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Generates a uri for an HLS manifest. The api takes in a collection of time ranges, and generates a URI for an HLS manifest that covers all the requested time ranges.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_generate_hls_uri():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GenerateHlsUriRequest(
        name="name_value",
    )

    # Make the request
    response = client.generate_hls_uri(request=request)

    # Handle the response
    print(response)

Reads annotation inside asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_get_annotation():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GetAnnotationRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_annotation(request=request)

    # Handle the response
    print(response)

Reads an asset inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_get_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GetAssetRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_asset(request=request)

    # Handle the response
    print(response)

Gets corpus details inside a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_get_corpus():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GetCorpusRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_corpus(request=request)

    # Handle the response
    print(response)

Gets data schema inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_get_data_schema():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GetDataSchemaRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_data_schema(request=request)

    # Handle the response
    print(response)

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Gets information about a location.

Deprecated. Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Gets the latest state of a long-running operation.

Gets a search configuration inside a corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_get_search_config():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.GetSearchConfigRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_search_config(request=request)

    # Handle the response
    print(response)

Ingests data for the asset. It is not allowed to ingest a data chunk which is already expired according to TTL. This method is only available via the gRPC API (not HTTP since bi-directional streaming is not supported via HTTP).

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_ingest_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    config = visionai_v1alpha1.Config()
    config.asset = "asset_value"

    request = visionai_v1alpha1.IngestAssetRequest(
        config=config,
    )

    # This method expects an iterator which contains
    # 'visionai_v1alpha1.IngestAssetRequest' objects
    # Here we create a generator that yields a single `request` for
    # demonstrative purposes.
    requests = [request]

    def request_generator():
        for request in requests:
            yield request

    # Make the request
    stream = client.ingest_asset(requests=request_generator())

    # Handle the response
    for response in stream:
        print(response)

Lists a list of annotations inside asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_list_annotations():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ListAnnotationsRequest(
    )

    # Make the request
    page_result = client.list_annotations(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists an list of assets inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_list_assets():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ListAssetsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_assets(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists all corpora in a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_list_corpora():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ListCorporaRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_corpora(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists a list of data schemas inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_list_data_schemas():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ListDataSchemasRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_data_schemas(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Lists information about the supported locations for this service.

Lists operations that match the specified filter in the request.

Lists all search configurations inside a corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_list_search_configs():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.ListSearchConfigsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_search_configs(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Parses a annotation path into its component segments.

Parses a asset path into its component segments.

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a corpus path into its component segments.

Parses a data_schema path into its component segments.

Parses a search_config path into its component segments.

Search media asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_search_assets():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.SearchAssetsRequest(
        corpus="corpus_value",
    )

    # Make the request
    page_result = client.search_assets(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Returns a fully-qualified search_config string.

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Tests the specified IAM permissions against the IAM access control policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Updates annotation inside asset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_update_annotation():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.UpdateAnnotationRequest(
    )

    # Make the request
    response = client.update_annotation(request=request)

    # Handle the response
    print(response)

Updates an asset inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_update_asset():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.UpdateAssetRequest(
    )

    # Make the request
    response = client.update_asset(request=request)

    # Handle the response
    print(response)

Updates a corpus in a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_update_corpus():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    corpus = visionai_v1alpha1.Corpus()
    corpus.display_name = "display_name_value"

    request = visionai_v1alpha1.UpdateCorpusRequest(
        corpus=corpus,
    )

    # Make the request
    response = client.update_corpus(request=request)

    # Handle the response
    print(response)

Updates data schema inside corpus.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_update_data_schema():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    data_schema = visionai_v1alpha1.DataSchema()
    data_schema.key = "key_value"

    request = visionai_v1alpha1.UpdateDataSchemaRequest(
        data_schema=data_schema,
    )

    # Make the request
    response = client.update_data_schema(request=request)

    # Handle the response
    print(response)

Updates a search configuration inside a corpus.

Please follow the rules below to create a valid UpdateSearchConfigRequest. --- General Rules ---

1. Request.search_configuration.name must already exist.
2. Request must contain at least one non-empty search_criteria_property or facet_property.
3. mapped_fields must not be empty, and must map to existing UGA keys.
4. All mapped_fields must be of the same type.
5. All mapped_fields must share the same granularity.
6. All mapped_fields must share the same semantic SearchConfig match options. For property-specific rules, please reference the comments for FacetProperty and SearchCriteriaProperty.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import visionai_v1alpha1

def sample_update_search_config():
    # Create a client
    client = visionai_v1alpha1.WarehouseClient()

    # Initialize request argument(s)
    request = visionai_v1alpha1.UpdateSearchConfigRequest(
    )

    # Make the request
    response = client.update_search_config(request=request)

    # Handle the response
    print(response)