| """A large crowd-sourced dataset for developing natural language interfaces for relational databases""" |
|
|
|
|
| import json |
| import os |
|
|
| import datasets |
|
|
|
|
| _CITATION = """\ |
| @article{zhongSeq2SQL2017, |
| author = {Victor Zhong and |
| Caiming Xiong and |
| Richard Socher}, |
| title = {Seq2SQL: Generating Structured Queries from Natural Language using |
| Reinforcement Learning}, |
| journal = {CoRR}, |
| volume = {abs/1709.00103}, |
| year = {2017} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| A large crowd-sourced dataset for developing natural language interfaces for relational databases |
| """ |
|
|
| _DATA_URL = "https://github.com/salesforce/WikiSQL/raw/master/data.tar.bz2" |
|
|
| _AGG_OPS = ["", "MAX", "MIN", "COUNT", "SUM", "AVG"] |
| _COND_OPS = ["=", ">", "<", "OP"] |
|
|
|
|
| class WikiSQL(datasets.GeneratorBasedBuilder): |
| """WikiSQL: A large crowd-sourced dataset for developing natural language interfaces for relational databases""" |
|
|
| VERSION = datasets.Version("0.1.0") |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "phase": datasets.Value("int32"), |
| "question": datasets.Value("string"), |
| "table": { |
| "header": datasets.features.Sequence(datasets.Value("string")), |
| "page_title": datasets.Value("string"), |
| "page_id": datasets.Value("string"), |
| "types": datasets.features.Sequence(datasets.Value("string")), |
| "id": datasets.Value("string"), |
| "section_title": datasets.Value("string"), |
| "caption": datasets.Value("string"), |
| "rows": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("string"))), |
| "name": datasets.Value("string"), |
| }, |
| "sql": { |
| "human_readable": datasets.Value("string"), |
| "sel": datasets.Value("int32"), |
| "agg": datasets.Value("int32"), |
| "conds": datasets.features.Sequence( |
| { |
| "column_index": datasets.Value("int32"), |
| "operator_index": datasets.Value("int32"), |
| "condition": datasets.Value("string"), |
| } |
| ), |
| }, |
| } |
| ), |
| |
| |
| |
| supervised_keys=None, |
| |
| homepage="https://github.com/salesforce/WikiSQL", |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| dl_dir = dl_manager.download_and_extract(_DATA_URL) |
| dl_dir = os.path.join(dl_dir, "data") |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={ |
| "main_filepath": os.path.join(dl_dir, "test.jsonl"), |
| "tables_filepath": os.path.join(dl_dir, "test.tables.jsonl"), |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, |
| gen_kwargs={ |
| "main_filepath": os.path.join(dl_dir, "dev.jsonl"), |
| "tables_filepath": os.path.join(dl_dir, "dev.tables.jsonl"), |
| }, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={ |
| "main_filepath": os.path.join(dl_dir, "train.jsonl"), |
| "tables_filepath": os.path.join(dl_dir, "train.tables.jsonl"), |
| }, |
| ), |
| ] |
|
|
| def _convert_to_human_readable(self, sel, agg, columns, conditions): |
| """Make SQL query string. Based on https://github.com/salesforce/WikiSQL/blob/c2ed4f9b22db1cc2721805d53e6e76e07e2ccbdc/lib/query.py#L10""" |
|
|
| rep = f"SELECT {_AGG_OPS[agg]} {columns[sel] if columns is not None else f'col{sel}'} FROM table" |
|
|
| if conditions: |
| rep += " WHERE " + " AND ".join([f"{columns[i]} {_COND_OPS[o]} {v}" for i, o, v in conditions]) |
| return " ".join(rep.split()) |
|
|
| def _generate_examples(self, main_filepath, tables_filepath): |
| """Yields examples.""" |
|
|
| |
| with open(tables_filepath, encoding="utf-8") as f: |
| tables = [json.loads(line) for line in f] |
| id_to_tables = {x["id"]: x for x in tables} |
|
|
| with open(main_filepath, encoding="utf-8") as f: |
| for idx, line in enumerate(f): |
| row = json.loads(line) |
| row["table"] = id_to_tables[row["table_id"]] |
| del row["table_id"] |
|
|
| |
| row["table"]["page_title"] = row["table"].get("page_title", "") |
| row["table"]["section_title"] = row["table"].get("section_title", "") |
| row["table"]["caption"] = row["table"].get("caption", "") |
| row["table"]["name"] = row["table"].get("name", "") |
| row["table"]["page_id"] = str(row["table"].get("page_id", "")) |
|
|
| |
| row["table"]["rows"] = [[str(e) for e in r] for r in row["table"]["rows"]] |
|
|
| |
| row["sql"]["human_readable"] = self._convert_to_human_readable( |
| row["sql"]["sel"], |
| row["sql"]["agg"], |
| row["table"]["header"], |
| row["sql"]["conds"], |
| ) |
|
|
| |
| |
| |
| for i in range(len(row["sql"]["conds"])): |
| row["sql"]["conds"][i] = { |
| "column_index": row["sql"]["conds"][i][0], |
| "operator_index": row["sql"]["conds"][i][1], |
| "condition": str(row["sql"]["conds"][i][2]), |
| } |
| yield idx, row |
|
|
