def compare_documents(documentA, documentB):
    """
    Dsc: computes cosine text similarity from tf idf of given document.
    Inf - source: https://stackoverflow.com/questions/8897593/similarity-between-two-text-documents
    Dependencies: http://scikit-learn.org/stable/install.html
    from sklearn.feature_extraction.text import TfidfVectorizer
    pip install -U scikit-learn numpy scipy
    """
    try:
        print("compare_documents, documentA: '%s'" % documentA)
    except Exception as err:
        print("compare_documents, Could not print documentA, err: '%s'" % err)
    sys.stdout.flush()
    try:
        print("compare_documents, documentB: '%s'" % documentB)
    except Exception as err:
        print("compare_documents, Could not print documentB, err: '%s'" % err)
    sys.stdout.flush()

    input = [documentA, documentB]
    vect = TfidfVectorizer(min_df=1, decode_error='ignore')


    tfidf = vect.fit_transform(input)
    sim_matrix = (tfidf * tfidf.T).A
    return sim_matrix[0][1]