senti.py

import sys
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
import os
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = r"sentiment-analysis-284609-a234a6af795c.json"


def language_analysis(text):
    client = language.LanguageServiceClient()
    # The text to analyze

    document = types.Document(
        content=text,
        type=enums.Document.Type.PLAIN_TEXT)

    # Detects the sentiment of the text
    sentiment = client.analyze_sentiment(document=document).document_sentiment
    ent_analysis = client.analyze_entities(
        document=document, encoding_type='UTF32')
    dir(ent_analysis)
    entities = ent_analysis.entities

    return sentiment, entities


# text = 'Python is a great language i use everyday for my daily work and i make machine learning models and neural networks'
text = sys.argv[1]

sentiment, entities = language_analysis(text)
print('Text: {}'.format(text))
# print('Sentiment: {}, {}'.format(sentiment.score, sentiment.magnitude))
for e in entities:
    print(e.name,  e.metadata, e.salience)