import engine.data_processing.extract_question as qe
q_extract = qe.QuestionExtraction("js_corpus.json")
training_corpus = q_extract.extract_training_corpus()
question = q_extract.extract_question(training_corpus, 0)
print(question)
import engine.data_processing.extract_data_for_classification as dfc
import engine.data_processing.extract_question as qe
if __name__ == "__main__":
index = 1 # index of the question which you want to extract
training_corpus = qe.QuestionExtraction("js_corpus.json")
training_corpus_json = training_corpus.extract_training_corpus()
# This question var contains the raw string that is pulled from corpus
question = training_corpus.extract_question(training_corpus_json, index)
# This call will automatically returns the list of processed tokens from the question
# doc_question will contain the process 'DOC' object of the question string.
list_of_processed_tokens, doc_question = dfc.DataExtract(
).extract_list_of_tokens(question)
print(list_of_processed_tokens)