1. Create aclass InvertedIndexto act as an abstract data type for the inverted index data structure. Itshould include the following member functions/support these operation on its data: Anormalize(term)method that takes astrobject stored intermand returns a stemmed version of thatword suitable for a key in the inverted index Anaddterm(term, docID):method that adds the unnormalizedstrobjecttermto the index if need beand records that the document with integraldocIDcontains that term Anadddocument(document, id)method that takes a document as astrobject with integralidand addsa tokenized, normalized version of the document to the inverted index. Stopwords in the document are notindexed Abuildindex(corpus)method that takes a corpus as alistof documents and usesadddocumentasnecessary to build the index. A document's ID is its index in the listcorpus, so the first document has ID 0.next 1, and so on. .An object of typeInvertedIndexshould support the operator[term]for term lookup. In other words, ifobjectiiwas constructed viaii - InvertedIndex()and a suitable index built theniil'Kimmer']wouldreturn the list of document IDs containing the search term 'Kimmer'. Hint: magic methods .By default, if a term is not in the index, it should return the empty list[].There is a pickled corpus you can use for testing. It's located in my home directory assavedtweets.p.You can login via Putty and docp cjkimmer/savedtweets.p i427to copy it to your Jupyter notebookdirectory and access it viapickle.open). If you want to show off, you can use the path to the file in mydirectory and open it withpicklewithout copying it first! 1. Create aclass InvertedIndexto act as an abstract data type for the inverted index data structure. Itshould include the following member functions/support these operation on its data: Anormalize(term)method that takes astrobject stored intermand returns a stemmed version of thatword suitable for a key in the inverted index Anaddterm(term, docID):method that adds the unnormalizedstrobjecttermto the index if need beand records that the document with integraldocIDcontains that term Anadddocument(document, id)method that takes a document as astrobject with integralidand addsa tokenized, normalized version of the document to the inverted index. Stopwords in the document are notindexed Abuildindex(corpus)method that takes a corpus as alistof documents and usesadddocumentasnecessary to build the index. A document's ID is its index in the listcorpus, so the first document has ID 0.next 1, and so on. .An object of typeInvertedIndexshould support the operator[term]for term lookup. In other words, ifobjectiiwas constructed viaii - InvertedIndex()and a suitable index built theniil'Kimmer']wouldreturn the list of document IDs containing the search term 'Kimmer'. Hint: magic methods .By default, if a term is not in the index, it should return the empty list[].There is a pickled corpus you can use for testing. It's located in my home directory assavedtweets.p.You can login via Putty and docp cjkimmer/savedtweets.p i427to copy it to your Jupyter notebookdirectory and access it viapickle.open). If you want to show off, you can use the path to the file in mydirectory and open it withpicklewithout copying it first