def params()

in msmarco-passage-ranking/track.py [0:0]

• 34 lines of code
• 6 McCabe index (conditional complexity)

    def params(self):
        query_obj = self._queries[self._iters]
        if self._query_strategy == "bm25":
            query = generate_bm25_query(text_field=self._text_field, query=query_obj["query"], boost=1)
        elif self._query_strategy == "text_expansion":
            if self._prune is False:
                query = generate_weighted_terms_query(
                    text_expansion_field=self._text_expansion_field, query_expansion=query_obj[self._text_expansion_field], boost=1
                )
            elif self._rescore is True:
                query = generate_rescored_pruned_query(
                    field=self._text_expansion_field,
                    query_expansion=query_obj[self._text_expansion_field],
                    num_candidates=self._num_candidates,
                    boost=1,
                )
            else:
                query = generate_pruned_query(
                    field=self._text_expansion_field, query_expansion=query_obj[self._text_expansion_field], boost=1
                )
        elif self._query_strategy == "hybrid":
            query = generate_combine_bm25_weighted_terms_query(
                self._text_field, self._text_expansion_field, query_obj["query"], 1, query_obj[self._text_expansion_field], 1
            )
        else:
            raise Exception(f"The query strategy \\`{self._query_strategy}]\\` is not implemented")

        self._iters = (self._iters + 1) % len(self._queries)
        query["track_total_hits"] = self._track_total_hits
        query["size"] = self._size
        return {
            "index": self._index_name,
            "cache": self._cache,
            "body": query,
        }