scoring reviews

score_review.py

def score_review(source=None, file_type=None):
    '''
    source: the text, as either a string or a list of strings
    file_type: (str): indicating whether we expecting a file containing the
    text data or a directory containing a list files holding the text
    options: 'file' or 'dir'
    '''
    text_list = list()
    if isinstance(source, str) and file_type is None:
        text_list.append(source)
        decoded_review, data = decode_review(text_list)
        # make prediction
        score = model.predict(data)[0][0]
        review_rating(score, decoded_review)
    
    if isinstance(source, list) and file_type is None:
        for item in source:
            text_list = list()
            text_list.append(item)
            decoded_review, data = decode_review(text_list)
            score = model.predict(data)[0][0]
            review_rating(score, decoded_review)
    
    if isinstance(source, str) and file_type == 'file':
        file_data = open(source).read()
        text_list.append(file_data)
        decoded_review, data = decode_review(text_list)
        # make prediction
        score = model.predict(data)[0][0]
        review_rating(score, decoded_review)
    
    if isinstance(source, str) and file_type == 'dir':
        file_content_holder = list()
        for fname in os.listdir(source):
            if fname[-4:] == '.txt':
                f = open(os.path.join(source, fname))
                file_content_holder.append(f.read())
                f.close()
        for item in file_content_holder:
            text_list = list()
            text_list.append(item)
            decoded_review, data = decode_review(text_list)
            score = model.predict(data)[0][0]
            review_rating(score, decoded_review)