# coding=utf-8
# Copyright 2023 The HuggingFace Datasets Authors and Ilya Gusev
#
# 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
"""Habrahabr dataset"""

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 = "Habrahabr dataset"
_URL = "habr.jsonl.zst"


class HabrDataset(datasets.GeneratorBasedBuilder):
    """Habrahabr dataset"""

    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("uint32"),
                "language": datasets.Value("string"),
                "url": datasets.Value("string"),
                "title": datasets.Value("string"),
                "text_markdown": datasets.Value("string"),
                "text_html": datasets.Value("string"),
                "author": datasets.Value("string"),
                "original_author": datasets.Value("string"),
                "original_url": datasets.Value("string"),
                "lead_html": datasets.Value("string"),
                "lead_markdown": datasets.Value("string"),
                "type": datasets.Value("string"),
                "time_published": datasets.Value("uint64"),
                "statistics": {
                    "commentsCount": datasets.Value("uint32"),
                    "favoritesCount": datasets.Value("uint32"),
                    "readingCount": datasets.Value("uint32"),
                    "score": datasets.Value("int32"),
                    "votesCount": datasets.Value("int32"),
                    "votesCountPlus": datasets.Value("int32"),
                    "votesCountMinus": datasets.Value("int32")
                },
                "labels": datasets.Sequence(datasets.Value("string")),
                "hubs": datasets.Sequence(datasets.Value("string")),
                "flows": datasets.Sequence(datasets.Value("string")),
                "tags": datasets.Sequence(datasets.Value("string")),
                "reading_time": datasets.Value("uint32"),
                "format": datasets.Value("string"),
                "complexity": datasets.Value("string"),
                "comments": datasets.Sequence(feature={
                    "id": datasets.Value("uint64"),
                    "parent_id": datasets.Value("uint64"),
                    "level": datasets.Value("uint32"),
                    "time_published": datasets.Value("uint64"),
                    "score": datasets.Value("int32"),
                    "votes": datasets.Value("uint32"),
                    "message_html": datasets.Value("string"),
                    "message_markdown": datasets.Value("string"),
                    "author": datasets.Value("string"),
                    "children": datasets.Sequence(datasets.Value("uint64"))
                })
            }
        )
        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