css.py

# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset"""


import json
import os

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
"""

_DESCRIPTION = "CSS is a large-scale cross-schema Chinese text-to-SQL dataset"

_LICENSE = "CC BY-SA 4.0"

_URL = "https://huggingface.co/datasets/zhanghanchong/css/resolve/main/css.zip"


class CSS(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="css",
            version=VERSION,
            description="CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset",
        ),
    ]

    def _info(self):
        features = datasets.Features(
            {
                "query": datasets.Value("string"),
                "db_id": datasets.Value("string"),
                "question": datasets.Value("string"),
                "question_id": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_filepath = dl_manager.download_and_extract(_URL)

        return [
            datasets.SplitGenerator(
                name=datasets.NamedSplit("example.train"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/example/train.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("example.dev"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/example/dev.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("example.test"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/example/test.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("template.train"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/template/train.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("template.dev"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/template/dev.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("template.test"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/template/test.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("schema.train"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/schema/train.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("schema.dev"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/schema/dev.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.NamedSplit("schema.test"),
                gen_kwargs={
                    "data_filepath": os.path.join(downloaded_filepath, "css/schema/test.json"),
                },
            ),
        ]

    def _generate_examples(self, data_filepath):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", data_filepath)
        with open(data_filepath, encoding="utf-8") as f:
            css = json.load(f)
            for idx, sample in enumerate(css):
                yield idx, {
                    "query": sample["query"],
                    "db_id": sample["db_id"],
                    "question": sample["question"],
                    "question_id": sample["question_id"],
                }