Class LanguageServiceAsyncClient (2.5.2)

LanguageServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.language_v1beta2.services.language_service.transports.base.LanguageServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Provides text analysis operations such as sentiment analysis and entity recognition.

Properties

transport

Returns the transport used by the client instance.

Returns
TypeDescription
LanguageServiceTransportThe transport used by the client instance.

Methods

LanguageServiceAsyncClient

LanguageServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.language_v1beta2.services.language_service.transports.base.LanguageServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the language service client.

Parameters
NameDescription
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

transport Union[str, .LanguageServiceTransport]

The transport to use. If set to None, a transport is chosen automatically.

client_options ClientOptions

Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.

Exceptions
TypeDescription
google.auth.exceptions.MutualTlsChannelErrorIf mutual TLS transport creation failed for any reason.

analyze_entities

analyze_entities(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.AnalyzeEntitiesRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1beta2.types.language_service.EncodingType] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Finds named entities (currently proper names and common nouns) in the text along with entity types, salience, mentions for each entity, and other properties.

from google.cloud import language_v1beta2

async def sample_analyze_entities():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.AnalyzeEntitiesRequest(
        document=document,
    )

    # Make the request
    response = await client.analyze_entities(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.AnalyzeEntitiesRequest, dict]

The request object. The entity analysis request message.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

encoding_type EncodingType

The encoding type used by the API to calculate offsets. This corresponds to the encoding_type field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.AnalyzeEntitiesResponseThe entity analysis response message.

analyze_entity_sentiment

analyze_entity_sentiment(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.AnalyzeEntitySentimentRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1beta2.types.language_service.EncodingType] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Finds entities, similar to xref_AnalyzeEntities in the text and analyzes sentiment associated with each entity and its mentions.

from google.cloud import language_v1beta2

async def sample_analyze_entity_sentiment():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.AnalyzeEntitySentimentRequest(
        document=document,
    )

    # Make the request
    response = await client.analyze_entity_sentiment(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.AnalyzeEntitySentimentRequest, dict]

The request object. The entity-level sentiment analysis request message.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

encoding_type EncodingType

The encoding type used by the API to calculate offsets. This corresponds to the encoding_type field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.AnalyzeEntitySentimentResponseThe entity-level sentiment analysis response message.

analyze_sentiment

analyze_sentiment(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.AnalyzeSentimentRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1beta2.types.language_service.EncodingType] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Analyzes the sentiment of the provided text.

from google.cloud import language_v1beta2

async def sample_analyze_sentiment():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.AnalyzeSentimentRequest(
        document=document,
    )

    # Make the request
    response = await client.analyze_sentiment(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.AnalyzeSentimentRequest, dict]

The request object. The sentiment analysis request message.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

encoding_type EncodingType

The encoding type used by the API to calculate sentence offsets for the sentence sentiment. This corresponds to the encoding_type field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.AnalyzeSentimentResponseThe sentiment analysis response message.

analyze_syntax

analyze_syntax(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.AnalyzeSyntaxRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1beta2.types.language_service.EncodingType] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Analyzes the syntax of the text and provides sentence boundaries and tokenization along with part-of-speech tags, dependency trees, and other properties.

from google.cloud import language_v1beta2

async def sample_analyze_syntax():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.AnalyzeSyntaxRequest(
        document=document,
    )

    # Make the request
    response = await client.analyze_syntax(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.AnalyzeSyntaxRequest, dict]

The request object. The syntax analysis request message.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

encoding_type EncodingType

The encoding type used by the API to calculate offsets. This corresponds to the encoding_type field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.AnalyzeSyntaxResponseThe syntax analysis response message.

annotate_text

annotate_text(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.AnnotateTextRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, features: Optional[google.cloud.language_v1beta2.types.language_service.AnnotateTextRequest.Features] = None, encoding_type: Optional[google.cloud.language_v1beta2.types.language_service.EncodingType] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

A convenience method that provides all syntax, sentiment, entity, and classification features in one call.

from google.cloud import language_v1beta2

async def sample_annotate_text():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.AnnotateTextRequest(
        document=document,
    )

    # Make the request
    response = await client.annotate_text(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.AnnotateTextRequest, dict]

The request object. The request message for the text annotation API, which can perform multiple analysis types (sentiment, entities, and syntax) in one call.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

features Features

Required. The enabled features. This corresponds to the features field on the request instance; if request is provided, this should not be set.

encoding_type EncodingType

The encoding type used by the API to calculate offsets. This corresponds to the encoding_type field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.AnnotateTextResponseThe text annotations response message.

classify_text

classify_text(request: Optional[Union[google.cloud.language_v1beta2.types.language_service.ClassifyTextRequest, dict]] = None, *, document: Optional[google.cloud.language_v1beta2.types.language_service.Document] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Classifies a document into categories.

from google.cloud import language_v1beta2

async def sample_classify_text():
    # Create a client
    client = language_v1beta2.LanguageServiceAsyncClient()

    # Initialize request argument(s)
    document = language_v1beta2.Document()
    document.content = "content_value"

    request = language_v1beta2.ClassifyTextRequest(
        document=document,
    )

    # Make the request
    response = await client.classify_text(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.language_v1beta2.types.ClassifyTextRequest, dict]

The request object. The document classification request message.

document Document

Required. Input document. This corresponds to the document field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.language_v1beta2.types.ClassifyTextResponseThe document classification response message.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

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

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
LanguageServiceAsyncClientThe constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

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

Parameter
NameDescription
info dict

The service account private key info.

Returns
TypeDescription
LanguageServiceAsyncClientThe constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

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

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
LanguageServiceAsyncClientThe constructed client.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)

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 variabel 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.

Parameter
NameDescription
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf any errors happen.
Returns
TypeDescription
Tuple[str, Callable[[], Tuple[bytes, bytes]]]returns the API endpoint and the client cert source to use.

get_transport_class

get_transport_class()

Returns an appropriate transport class.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.