text: from Compression import *
  from IndexingData import *
  import sys
  import nltk
  if __name__ == "__main__":
      
      corpus_keys = nltk.corpus.reuters.fileids()
      corpus = [nltk.corpus.reuters.raw(id) for id in corpus_keys]
  
      allData = loadIndex('Test.bin')
      index = DecompressIndex(allData['index'])
      print(index)
      """DocId.ID = allData['totalDoc']
      query = ' '.join(sys.argv[1:])
      print(query)
      processedQuery = preProcessor.process(query)
      print(processedQuery)
      queryMetrics = calculateTfIdf(processedQuery, index)
  
      docs = calculateSimilarity(queryMetrics, index)
      print(docs)
  
      for docID in docs:
          print("\n\n-------------------DOC ID : "+str(docID)+"\n"+corpus[docID-1])"""