# 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.
"""Cleaned Indonesian split of the KoPI corpus."""
import json
import glob
import gzip
import textwrap
import datasets
import zstandard as zstd
logger = datasets.logging.get_logger(__name__)

_CITATION = """
"""
_DESCRIPTION = """\
"""
_HOMEPAGE = "https://huggingface.co/datasets/duckaiml/Polylingual_Id"
_LICENSE = "CC0"
_BASE_URL = {
    "train":"https://huggingface.co/datasets/duckaiml/Polylingual_Id/resolve/main/{folder}/part-{index:012d}.json.zst",
}
_CONFIGS = {
    "hplt": {"part": 10, "url": "https://huggingface.co/datasets/duckaiml/Polylingual_Id/resolve/main/hplt/part_{index:d}.jsonl.zst"},
    "mc4_und": {"part": 24, "url": "https://huggingface.co/datasets/duckaiml/Polylingual_Id/resolve/main/mc4_und/part_{index:d}.jsonl.zst"},
    "indonesia_crawl": {"part": 10, "url": "https://huggingface.co/datasets/duckaiml/Polylingual_Id/resolve/main/indonesia_crawl/part_{index:d}.jsonl.zst"},
}
class Polylingual_IdConfig(datasets.BuilderConfig):
    """BuilderConfig for the Clean Polylingual_Id corpus."""
    def __init__(self, **kwargs):
        """BuilderConfig for Clean Polylingual_Id corpus.
        Args:
            **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(**kwargs)
class Polylingual_Id(datasets.GeneratorBasedBuilder):
    """KoPI corpus."""
    BUILDER_CONFIGS = [
        Polylingual_IdConfig(
            name="hplt",
            version=datasets.Version("1.0.0"),
            description=textwrap.dedent(
                f"""\
                hplt
                """
            )
        ),
        Polylingual_IdConfig(
            name="mc4_und",
            version=datasets.Version("1.0.0"),
            description=textwrap.dedent(
                f"""\
                mc4_und
                """
            )
        ),
        Polylingual_IdConfig(
            name="indonesia_crawl",
            version=datasets.Version("1.0.0"),
            description=textwrap.dedent(
                f"""\
                indonesia_crawl
                """
            )
        ),
        Polylingual_IdConfig(
            name="full",
            version=datasets.Version("1.0.0"),
            description=textwrap.dedent(
                f"""\
                indonesia-crawl
                """
            )
        )
    ]
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "url": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )
    def _split_generators(self, dl_manager):
        if self.config.name == "full":
            data = ['hplt','mc4_und','indonesia_crawl']
            train = []
            for d in data:
                url = [_CONFIGS[d]['url'].format(index=k + 1) for k in range(_CONFIGS[d]['part'])]
                train.extend(url)
            train_downloaded_files = dl_manager.download(train)
        else:
            train = [_CONFIGS[self.config.name]['url'].format(index=k + 1) for k in range(_CONFIGS[self.config.name]['part'])]
            #train = [_BASE_URL["train"].format(index=k + 1) for k in range(107)][0:_CONFIGS[self.config.name]['train']]
            train_downloaded_files = dl_manager.download(train)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
        ]
    def _generate_examples(self, filepaths):
        """This function returns the examples in the raw (text) form by iterating on all the files."""
        id_ = 0
        for filepath in filepaths:
            logger.info(f"Generating examples from {filepath}")
            with zstd.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
                for line in f:
                    if line:
                        example = json.loads(line)
                        if example.get('url') is not None:
                            yield id_, {'text':example['text'],'url':example['url']}
                            id_ += 1
                        elif example.get('metadata') is not None:
                            yield id_, {'text':example['text'],'url':example['metadata']['url']}
                            id_ += 1
                        else:
                            yield id_, {'text':example['text'],'url':None}
                            id_ += 1