naturalLanguageTest.py

from google.cloud import language_v1
# Based on example from https://cloud.google.com/natural-language/docs/analyzing-sentiment?hl=en#language-sentiment-string-python

# Credentials

def sample_analyze_sentiment(client, text_content) -> list:
    """
    Analyzing Sentiment in a String

    Args:
      text_content The text content to analyze
    """

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

    # Available types: PLAIN_TEXT, HTML
    type_ = language_v1.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 = "en"
    document = {"content": text_content, "type_": type_, "language": language}

    # Available values: NONE, UTF8, UTF16, UTF32
    encoding_type = language_v1.EncodingType.UTF8

    #print("trying analysis")

    response = client.analyze_sentiment(request = {'document': 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
    #     )
    # )

    data = []

    # 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))
        data.append({'score': sentence.sentiment.score, 
            'magnitude': 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))

    return data

if __name__ == "__main__":
    sample_analyze_sentiment("hello, my name is Soup")