Datasets:
wikisql

	"""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"),
	}
	),
	},
	}
	),
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	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."""

	# Build dictionary to table_ids:tables
	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"]

	# Handle missing data
	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", ""))

	# Fix row types
	row["table"]["rows"] = [[str(e) for e in r] for r in row["table"]["rows"]]

	# Get human-readable version
	row["sql"]["human_readable"] = self._convert_to_human_readable(
	row["sql"]["sel"],
	row["sql"]["agg"],
	row["table"]["header"],
	row["sql"]["conds"],
	)

	# Restructure sql->conds
	# - wikiSQL provides a tuple [column_index, operator_index, condition]
	# as 'condition' can have 2 types (float or str) we convert to dict
	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