LanguageServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.language_v1.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.
Inheritance
builtins.object > LanguageServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
LanguageServiceTransport | The transport used by the client instance. |
Methods
LanguageServiceAsyncClient
LanguageServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.language_v1.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.
Name | Description |
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 |
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
analyze_entities
analyze_entities(request: Optional[Union[google.cloud.language_v1.types.language_service.AnalyzeEntitiesRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1.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.
# 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 language_v1
async def sample_analyze_entities():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.AnalyzeEntitiesRequest(
document=document,
)
# Make the request
response = await client.analyze_entities(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.types.AnalyzeEntitiesRequest, dict]
The request object. The entity analysis request message. |
document |
Document
Required. Input document. This corresponds to the |
encoding_type |
EncodingType
The encoding type used by the API to calculate offsets. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.AnalyzeEntitiesResponse | The entity analysis response message. |
analyze_entity_sentiment
analyze_entity_sentiment(request: Optional[Union[google.cloud.language_v1.types.language_service.AnalyzeEntitySentimentRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1.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.
# 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 language_v1
async def sample_analyze_entity_sentiment():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.AnalyzeEntitySentimentRequest(
document=document,
)
# Make the request
response = await client.analyze_entity_sentiment(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.types.AnalyzeEntitySentimentRequest, dict]
The request object. The entity-level sentiment analysis request message. |
document |
Document
Required. Input document. This corresponds to the |
encoding_type |
EncodingType
The encoding type used by the API to calculate offsets. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.AnalyzeEntitySentimentResponse | The entity-level sentiment analysis response message. |
analyze_sentiment
analyze_sentiment(request: Optional[Union[google.cloud.language_v1.types.language_service.AnalyzeSentimentRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1.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.
# 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 language_v1
async def sample_analyze_sentiment():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.AnalyzeSentimentRequest(
document=document,
)
# Make the request
response = await client.analyze_sentiment(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.types.AnalyzeSentimentRequest, dict]
The request object. The sentiment analysis request message. |
document |
Document
Required. Input document. This corresponds to the |
encoding_type |
EncodingType
The encoding type used by the API to calculate sentence offsets. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.AnalyzeSentimentResponse | The sentiment analysis response message. |
analyze_syntax
analyze_syntax(request: Optional[Union[google.cloud.language_v1.types.language_service.AnalyzeSyntaxRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.types.language_service.Document] = None, encoding_type: Optional[google.cloud.language_v1.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.
# 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 language_v1
async def sample_analyze_syntax():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.AnalyzeSyntaxRequest(
document=document,
)
# Make the request
response = await client.analyze_syntax(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.types.AnalyzeSyntaxRequest, dict]
The request object. The syntax analysis request message. |
document |
Document
Required. Input document. This corresponds to the |
encoding_type |
EncodingType
The encoding type used by the API to calculate offsets. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.AnalyzeSyntaxResponse | The syntax analysis response message. |
annotate_text
annotate_text(request: Optional[Union[google.cloud.language_v1.types.language_service.AnnotateTextRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.types.language_service.Document] = None, features: Optional[google.cloud.language_v1.types.language_service.AnnotateTextRequest.Features] = None, encoding_type: Optional[google.cloud.language_v1.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 the features that analyzeSentiment, analyzeEntities, and analyzeSyntax provide in one call.
# 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 language_v1
async def sample_annotate_text():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.AnnotateTextRequest(
document=document,
)
# Make the request
response = await client.annotate_text(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.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 |
features |
Features
Required. The enabled features. This corresponds to the |
encoding_type |
EncodingType
The encoding type used by the API to calculate offsets. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.AnnotateTextResponse | The text annotations response message. |
classify_text
classify_text(request: Optional[Union[google.cloud.language_v1.types.language_service.ClassifyTextRequest, dict]] = None, *, document: Optional[google.cloud.language_v1.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.
# 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 language_v1
async def sample_classify_text():
# Create a client
client = language_v1.LanguageServiceAsyncClient()
# Initialize request argument(s)
document = language_v1.Document()
document.content = "content_value"
request = language_v1.ClassifyTextRequest(
document=document,
)
# Make the request
response = await client.classify_text(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.language_v1.types.ClassifyTextRequest, dict]
The request object. The document classification request message. |
document |
Document
Required. Input document. This corresponds to the |
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. |
Type | Description |
google.cloud.language_v1.types.ClassifyTextResponse | The 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
LanguageServiceAsyncClient | The 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.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
LanguageServiceAsyncClient | The 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
LanguageServiceAsyncClient | The 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.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Type | Description |
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.