import json

import datasets


_VERSION = "1.0.0"

_DESCRIPTION = "Deepset's germanDPR dataset made compatible with BEIR benchmark framework. One version contains " \
               "the original dataset 1:1 and the other dataset is preprocessed. See official dataset card for " \
               "usage of dataset with BEIR."

_SUBSETS = ["queries-original", "corpus-original", "queries-processed", "corpus-processed", "qrels"]


class GermanDPRBeir(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = (
        [
            datasets.BuilderConfig(
                name="queries-original",
                description=f"BEIR queries created 1:1 from deepset/germanDPR.",
                version=_VERSION,
            ),
            datasets.BuilderConfig(
                name="corpus-original",
                description=f"BEIR corpus created 1:1 from deepset/germanDPR.",
                version=_VERSION,
            ),
            datasets.BuilderConfig(
                name="queries-processed",
                description=f"BEIR queries created and further text-processed from deepset/germanDPR.",
                version=_VERSION,
            ),
            datasets.BuilderConfig(
                name="corpus-processed",
                description=f"BEIR corpus created and further text-processed from deepset/germanDPR.",
                version=_VERSION,
            ),
            datasets.BuilderConfig(
                name="qrels",
                description=f"BEIR qrels created from deepset/germanDPR for train and test split.",
                version=_VERSION,
            )
        ]
    )

    DEFAULT_CONFIG_NAME = "qrels"

    def _info(self):
        name = self.config.name
        _SPLITS = ["queries-original", "corpus-original", "queries-processed", "corpus-processed", "qrels"]

        if name.startswith("queries"):
            features = {
                "_id": datasets.Value("string"),
                "text": datasets.Value("string")
            }
        elif name.startswith("corpus"):
            features = {
                "_id": datasets.Value("string"),
                "title": datasets.Value("string"),
                "text": datasets.Value("string"),
            }
        else:
            # name == qrels
            features = {
                "query-id": datasets.Value("string"),
                "corpus-id": datasets.Value("string"),
                "score": datasets.Value("int32")
            }

        return datasets.DatasetInfo(
            description=f"{_DESCRIPTION}\n{self.config.description}",
            features=datasets.Features(features),
            supervised_keys=None,
            homepage="https://huggingface.co/datasets/PM-AI/germandpr-beir",
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        _SPLITS = ["queries-original", "corpus-original", "queries-processed", "corpus-processed", "qrels"]

        name = self.config.name
        if name == "qrels":
            dl_path = dl_manager.download([
                "https://huggingface.co/datasets/PM-AI/germandpr-beir/resolve/main/data/qrels/train.tsv",
                "https://huggingface.co/datasets/PM-AI/germandpr-beir/resolve/main/data/qrels/test.tsv"
            ])
            return [
                datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_path[0]}),
                datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": dl_path[1]})
            ]
        else:
            dl_path = dl_manager.download(f"https://huggingface.co/datasets/PM-AI/germandpr-beir/resolve/main/data/{name}.jsonl")
            return [
                datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_path}),
                datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": dl_path})
            ]

    def _generate_queries_data(self, filepath):
        with open(filepath, "r", encoding="utf-8") as in_file:
            for idx, line in enumerate(in_file):
                data = json.loads(line)
                yield idx, data

    def _generate_corpus_data(self, filepath):
        with open(filepath, "r", encoding="utf-8") as in_file:
            for idx, line in enumerate(in_file):
                data = json.loads(line)
                if "metadata" in data:
                    del data["metadata"]
                yield idx, data

    def _generate_qrel_data(self, filepath):
        with open(filepath, "r", encoding="utf-8") as in_file:
            in_file.readline() # first line is header
            for idx, line in enumerate(in_file):
                qid, cid, score = line.rstrip().split("\t")
                yield idx, {"query-id": qid, "corpus-id": cid, "score": score}

    def _generate_examples(self, filepath):
        """Yields examples."""
        name = self.config.name
        if name.startswith("queries"):
            return self._generate_queries_data(filepath)
        elif name.startswith("corpus"):
            return self._generate_corpus_data(filepath)
        else:
            # name == qrels
            return self._generate_qrel_data(filepath)