habr_qna.py

# coding=utf-8
# Copyright 2023 The HuggingFace Datasets Authors and Ilya Gusev
# Modified by its5Q
#
# 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.

# Lint as: python3
import os
import io

import zstandard
import jsonlines
import datasets

try:
    import simdjson
    parser = simdjson.Parser()
    def parse_json(x):
        try:
            return parser.parse(x).as_dict()
        except ValueError:
            return
except ImportError:
    import json
    def parse_json(x):
        return json.loads(x)


_DESCRIPTION = "Habr QnA Dataset"
_URL = "questions.jsonl.zst"


class YandexQFullDataset(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("0.0.1")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="default", version=VERSION, description=""),
    ]

    DEFAULT_CONFIG_NAME = "default"

    def _info(self):
        features = datasets.Features(
            {
                "id": datasets.Value("int32"),
                "author": datasets.Value("string"),
                "title": datasets.Value("string"),
                "description": datasets.Value("string"),
                "tags": datasets.Sequence(feature=datasets.Value("string")),
                "posted_at": datasets.Value("string"),
                "view_count": datasets.Value("int32"),
                "subscribers_count": datasets.Value("int32"),
                "complexity": datasets.Value("string"),
                "complexity_votes": datasets.Value("int32"),
                "comments": datasets.Sequence(feature={
                    "author": datasets.Value("string"),
                    "posted_at": datasets.Value("string"),
                    "body": datasets.Value("string")
                }),
                "answers": datasets.Sequence(feature={
                    "id": datasets.Value("int32"),
                    "author": datasets.Value("string"),
                    "posted_at": datasets.Value("string"),
                    "body": datasets.Value("string"),
                    "accepted": datasets.Value("bool"),
                    "upvote_count": datasets.Value("int32"),
                    "comments": datasets.Sequence(feature={
                        "author": datasets.Value("string"),
                        "posted_at": datasets.Value("string"),
                        "body": datasets.Value("string")
                    })
                })
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features
        )

    def _split_generators(self, dl_manager):
        downloaded_file = dl_manager.download(_URL)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"path": downloaded_file}),
        ]

    def _generate_examples(self, path):
        with open(path, "rb") as f:
            cctx = zstandard.ZstdDecompressor()
            reader_stream = io.BufferedReader(cctx.stream_reader(f))
            reader = jsonlines.Reader(reader_stream, loads=parse_json)
            for id_, item in enumerate(reader):
                yield id_, item