medical_qa_ru_data.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.
"""Russian Q&A posts from a medical related forum"""


import csv
import datasets

_DESCRIPTION = """\
This dataset contains 190,335 Russian Q&A posts from a medical related forum.
"""

class MedicalQARuData(datasets.GeneratorBasedBuilder):
    def _info(self):
        features = datasets.Features(
            {
                "date": datasets.Value("string"),
                "categ": datasets.Value("string"),
                "theme": datasets.Value("string"),
                "desc": datasets.Value("string"),
                "ans": datasets.Value("string"),
                "spec10": datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
        )

    def _split_generators(self, dl_manager):
        urls_to_download = {
            "train": "medical_qa_ru_data.csv"
        }
        downloaded_files = dl_manager.download_and_extract(urls_to_download)
        
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]})
        ]
        
        #data_file = dl_manager.download_and_extract(_URL)
        #return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file})]

    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath, encoding="utf-8") as f:
            data = csv.reader(f)
            for id_, row in enumerate(data):
                if id_>0:
                    yield id_, {
                        "date": row[0],
                        "categ": row[1],
                        "theme": row[2],
                        "desc": row[3],
                        "ans": row[4],
                        "spec10": row[5],
                    }