问用Google进行阿拉伯语情感分析

EN

    from google.cloud import language_v1
    from google.cloud.language_v1 import enums
    import os

    print(os.environ.get('GOOGLE_APPLICATION_CREDENTIALS'))
    def sample_analyze_sentiment(text_content):
        """
        Analyzing Sentiment in a String

        Args:
          text_content The text content to analyze
        """

        client = language_v1.LanguageServiceClient()

        #text_content = 'I am so happy and joyful.'

        # Available types: PLAIN_TEXT, HTML
        type_ = enums.Document.Type.PLAIN_TEXT

        # Optional. If not specified, the language is automatically detected.
        # For list of supported languages:
        # https://cloud.google.com/natural-language/docs/languages
        language = "ar"
        document = {"content": text_content, "type": type_, "language": language}

        # Available values: NONE, UTF8, UTF16, UTF32
        encoding_type = enums.EncodingType.UTF8

        response = client.analyze_sentiment(document, encoding_type=encoding_type)
        # Get overall sentiment of the input document
        print(u"Document sentiment score: {}".format(response.document_sentiment.score))
        print(
            u"Document sentiment magnitude: {}".format(
                response.document_sentiment.magnitude
            )
        )

        # Get sentiment for all sentences in the document
        for sentence in response.sentences:
            print(u"Sentence text: {}".format(sentence.text.content))
            print(u"Sentence sentiment score: {}".format(sentence.sentiment.score))
            print(u"Sentence sentiment magnitude: {}".format(sentence.sentiment.magnitude))

        # Get 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.
        print(u"Language of the text: {}".format(response.language))



    text_content = "اهلا وسهلا"

    sample_analyze_sentiment(text_content)