def process_document()

in nlp-sentiment-analysis/code/main.py [0:0]

• 27 lines of code
• 2 McCabe index (conditional complexity)

def process_document(bucket_name, object_name):
    """Performs sentiment analysis on a text document stored in GCS."""

    print("Document processing started.")
    language_client = language_v2.LanguageServiceClient()
    storage_client = storage.Client()
    
    file_path = f"/tmp/{object_name}"

    print(f"Downloading document to: {file_path}")
    bucket = storage_client.get_bucket(bucket_name)
    blob = bucket.blob(object_name)
    blob.download_to_filename(file_path)
    with open(file_path, "r") as text_file:
        document_content = text_file.read()

    print("Performing sentiment analysis...")
    document = language_v2.Document(content=document_content, type_=language_v2.Document.Type.PLAIN_TEXT)
    response = language_client.analyze_sentiment(request={"document": document})

    # Get results
    sentiment_score = response.document_sentiment.score
    sentiment_magnitude = response.document_sentiment.magnitude
    sentences = [
        {"text": sentence.text.content, "sentiment": sentence.sentiment.score}
        for sentence in response.sentences
    ]

    process_output(
        bucket_name,
        object_name,
        sentiment_score,
        sentiment_magnitude,
        sentences,
    )