analyzeEntities(body, x__xgafv=None)
Finds named entities (currently finds proper names) in the text,
  analyzeSentiment(body, x__xgafv=None)
Analyzes the sentiment of the provided text.
  annotateText(body, x__xgafv=None)
A convenience method that provides all the features that analyzeSentiment,
analyzeEntities(body, x__xgafv=None)
  Finds named entities (currently finds proper names) in the text,
entity types, salience, mentions for each entity, and other properties.
Args:
  body: object, The request body. (required)
    The object takes the form of:
{ # The entity analysis request message.
    "document": { # ################################################################ # # Input document.
        #
        # Represents the input to API methods.
      "content": "A String", # The content of the input in string format.
      "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`,
          # returns an `INVALID_ARGUMENT` error.
      "language": "A String", # The language of the document (if not specified, the language is
          # automatically detected). Both ISO and BCP-47 language codes are
          # accepted.
          # **Current Language Restrictions:**
          #
          #  * Only English, Spanish, and Japanese textual content
          #    are supported, with the following additional restriction:
          #    * `analyzeSentiment` only supports English text.
          # If the language (either specified by the caller or automatically detected)
          # is not supported by the called API method, an `INVALID_ARGUMENT` error
          # is returned.
      "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located.
    },
    "encodingType": "A String", # The encoding type used by the API to calculate offsets.
  }
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
Returns:
  An object of the form:
    { # The entity analysis response message.
    "entities": [ # The recognized entities in the input document.
      { # Represents a phrase in the text that is a known entity, such as
          # a person, an organization, or location. The API associates information, such
          # as salience and mentions, with entities.
        "type": "A String", # The entity type.
        "mentions": [ # The mentions of this entity in the input document. The API currently
            # supports proper noun mentions.
          { # Represents a mention for an entity in the text. Currently, proper noun
              # mentions are supported.
            "text": { # Represents an output piece of text. # The mention text.
              "content": "A String", # The content of the output text.
              "beginOffset": 42, # The API calculates the beginning offset of the content in the original
                  # document according to the EncodingType specified in the API request.
            },
          },
        ],
        "salience": 3.14, # The salience score associated with the entity in the [0, 1.0] range.
            #
            # The salience score for an entity provides information about the
            # importance or centrality of that entity to the entire document text.
            # Scores closer to 0 are less salient, while scores closer to 1.0 are highly
            # salient.
        "name": "A String", # The representative name for the entity.
        "metadata": { # Metadata associated with the entity.
            #
            # Currently, only Wikipedia URLs are provided, if available.
            # The associated key is "wikipedia_url".
          "a_key": "A String",
        },
      },
    ],
    "language": "A String", # The language of the text, which will be the same as the language specified
        # in the request or, if not specified, the automatically-detected language.
        # See Document.language field for more details.
  }
analyzeSentiment(body, x__xgafv=None)
  Analyzes the sentiment of the provided text.
Args:
  body: object, The request body. (required)
    The object takes the form of:
{ # The sentiment analysis request message.
    "document": { # ################################################################ # # Input document. Currently, `analyzeSentiment` only supports English text
        # (Document.language="EN").
        #
        # Represents the input to API methods.
      "content": "A String", # The content of the input in string format.
      "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`,
          # returns an `INVALID_ARGUMENT` error.
      "language": "A String", # The language of the document (if not specified, the language is
          # automatically detected). Both ISO and BCP-47 language codes are
          # accepted.
          # **Current Language Restrictions:**
          #
          #  * Only English, Spanish, and Japanese textual content
          #    are supported, with the following additional restriction:
          #    * `analyzeSentiment` only supports English text.
          # If the language (either specified by the caller or automatically detected)
          # is not supported by the called API method, an `INVALID_ARGUMENT` error
          # is returned.
      "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located.
    },
  }
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
Returns:
  An object of the form:
    { # The sentiment analysis response message.
    "documentSentiment": { # Represents the feeling associated with the entire text or entities in # The overall sentiment of the input document.
        # the text.
      "polarity": 3.14, # Polarity of the sentiment in the [-1.0, 1.0] range. Larger numbers
          # represent more positive sentiments.
      "magnitude": 3.14, # A non-negative number in the [0, +inf) range, which represents
          # the absolute magnitude of sentiment regardless of polarity (positive or
          # negative).
    },
    "language": "A String", # The language of the text, which will be the same as the language specified
        # in the request or, if not specified, the automatically-detected language.
  }
annotateText(body, x__xgafv=None)
  A convenience method that provides all the features that analyzeSentiment,
analyzeEntities, and analyzeSyntax provide in one call.
Args:
  body: object, The request body. (required)
    The object takes the form of:
{ # The request message for the text annotation API, which can perform multiple
      # analysis types (sentiment, entities, and syntax) in one call.
    "document": { # ################################################################ # # Input document.
        #
        # Represents the input to API methods.
      "content": "A String", # The content of the input in string format.
      "type": "A String", # Required. If the type is not set or is `TYPE_UNSPECIFIED`,
          # returns an `INVALID_ARGUMENT` error.
      "language": "A String", # The language of the document (if not specified, the language is
          # automatically detected). Both ISO and BCP-47 language codes are
          # accepted.
          # **Current Language Restrictions:**
          #
          #  * Only English, Spanish, and Japanese textual content
          #    are supported, with the following additional restriction:
          #    * `analyzeSentiment` only supports English text.
          # If the language (either specified by the caller or automatically detected)
          # is not supported by the called API method, an `INVALID_ARGUMENT` error
          # is returned.
      "gcsContentUri": "A String", # The Google Cloud Storage URI where the file content is located.
    },
    "encodingType": "A String", # The encoding type used by the API to calculate offsets.
    "features": { # All available features for sentiment, syntax, and semantic analysis. # The enabled features.
        # Setting each one to true will enable that specific analysis for the input.
      "extractSyntax": True or False, # Extract syntax information.
      "extractEntities": True or False, # Extract entities.
      "extractDocumentSentiment": True or False, # Extract document-level sentiment.
    },
  }
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
Returns:
  An object of the form:
    { # The text annotations response message.
    "tokens": [ # Tokens, along with their syntactic information, in the input document.
        # Populated if the user enables
        # AnnotateTextRequest.Features.extract_syntax.
      { # Represents the smallest syntactic building block of the text.
        "text": { # Represents an output piece of text. # The token text.
          "content": "A String", # The content of the output text.
          "beginOffset": 42, # The API calculates the beginning offset of the content in the original
              # document according to the EncodingType specified in the API request.
        },
        "dependencyEdge": { # Represents dependency parse tree information for a token. # Dependency tree parse for this token.
          "headTokenIndex": 42, # Represents the head of this token in the dependency tree.
              # This is the index of the token which has an arc going to this token.
              # The index is the position of the token in the array of tokens returned
              # by the API method. If this token is a root token, then the
              # `head_token_index` is its own index.
          "label": "A String", # The parse label for the token.
        },
        "partOfSpeech": { # Represents part of speech information for a token. # Parts of speech tag for this token.
          "tag": "A String", # The part of speech tag.
        },
        "lemma": "A String", # [Lemma](https://en.wikipedia.org/wiki/Lemma_(morphology))
            # of the token.
      },
    ],
    "entities": [ # Entities, along with their semantic information, in the input document.
        # Populated if the user enables
        # AnnotateTextRequest.Features.extract_entities.
      { # Represents a phrase in the text that is a known entity, such as
          # a person, an organization, or location. The API associates information, such
          # as salience and mentions, with entities.
        "type": "A String", # The entity type.
        "mentions": [ # The mentions of this entity in the input document. The API currently
            # supports proper noun mentions.
          { # Represents a mention for an entity in the text. Currently, proper noun
              # mentions are supported.
            "text": { # Represents an output piece of text. # The mention text.
              "content": "A String", # The content of the output text.
              "beginOffset": 42, # The API calculates the beginning offset of the content in the original
                  # document according to the EncodingType specified in the API request.
            },
          },
        ],
        "salience": 3.14, # The salience score associated with the entity in the [0, 1.0] range.
            #
            # The salience score for an entity provides information about the
            # importance or centrality of that entity to the entire document text.
            # Scores closer to 0 are less salient, while scores closer to 1.0 are highly
            # salient.
        "name": "A String", # The representative name for the entity.
        "metadata": { # Metadata associated with the entity.
            #
            # Currently, only Wikipedia URLs are provided, if available.
            # The associated key is "wikipedia_url".
          "a_key": "A String",
        },
      },
    ],
    "documentSentiment": { # Represents the feeling associated with the entire text or entities in # The overall sentiment for the document. Populated if the user enables
        # AnnotateTextRequest.Features.extract_document_sentiment.
        # the text.
      "polarity": 3.14, # Polarity of the sentiment in the [-1.0, 1.0] range. Larger numbers
          # represent more positive sentiments.
      "magnitude": 3.14, # A non-negative number in the [0, +inf) range, which represents
          # the absolute magnitude of sentiment regardless of polarity (positive or
          # negative).
    },
    "language": "A String", # The language of the text, which will be the same as the language specified
        # in the request or, if not specified, the automatically-detected language.
        # See Document.language field for more details.
    "sentences": [ # Sentences in the input document. Populated if the user enables
        # AnnotateTextRequest.Features.extract_syntax.
      { # Represents a sentence in the input document.
        "text": { # Represents an output piece of text. # The sentence text.
          "content": "A String", # The content of the output text.
          "beginOffset": 42, # The API calculates the beginning offset of the content in the original
              # document according to the EncodingType specified in the API request.
        },
      },
    ],
  }