import json
from dataclasses import dataclass
from string import Template

import datasets
from datasets.download.download_manager import DownloadManager

_CITATION = ""
_DESCRIPTION = \
    """
    Wura is large-scale pretraining data for 20 languages popularly spoken in Africa.
    """
_HOMEPAGE = "https://github.com/castorini/AfriTeVa-keji"
_LICENSE = "Apache License 2.0"
_DOCUMENT_DATASET_VERSION = "1.0.0"
_PASSAGE_DATASET_VERSION = "1.0.0"
_LANGUAGES = {
    "Afrikaans": "afr",
    "Amharic": "amh",
    "Egyptian Arabic": "arz",
    "English": "eng",
    "French": "fra",
    "Hausa": "hau",
    "Igbo": "ibo",
    "Gahuza": "kin",
    "Malagasy": "mlg",
    "Chichewa": "nya",
    "Afaan Oromoo": "orm",
    # "Nigerian Pidgin": "pcm",
    "Portuguese": "por",
    "Shona": "sna",
    "Somali": "som",
    "Sesotho": "sot",
    "Swahili": "swa",
    "Tigrinya": "tir",
    "Xhosa": "xho",
    "Yoruba": "yor",
    "Zulu": "zul"
}
_DOCUMENT_DATASET_URL = Template("./documents-v1.0/${split}/${language}.jsonl")
_PASSAGE_DATASET_URL = Template("./passages-v1.0/${split}/${language}.txt")

INVALID_WINDOWS_CHARACTERS_IN_PATH = r"<>:/\|?*"


@dataclass
class WuraConfig(datasets.BuilderConfig):
    level: str = "document"


class WuraDataset(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        WuraConfig(
            name=language,
            version=datasets.Version(_DOCUMENT_DATASET_VERSION),
            description=f"Wura dataset for language: {language}\n{_DESCRIPTION}",
        ) for language in _LANGUAGES.values()
    ]

    DEFAULT_CONFIG_NAME = "afr"
    
    def _info(self):
        if self.config.level == "document":
            features = ["id", "headline", "content", "category", "url"]
        elif self.config.level == "passage":
            features = ["id", "text"]
        else:
            raise ValueError("level can only be one of `document` or `passage`")
        
        features = {feature: datasets.Value("string") for feature in features}

        return datasets.DatasetInfo(
            description=self.config.description,
            features=datasets.Features(features),
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license=_LICENSE
        )
    
    def _split_generators(self, dl_manager: DownloadManager):
        if self.config.level == "document":
            data_files = {
                split: _DOCUMENT_DATASET_URL.substitute(
                    split=split,
                    language=self.config.name,
                ) for split in ["train", "eval"]
            }
        elif self.config.level == "passage":
            data_files = {
                split: _PASSAGE_DATASET_URL.substitute(
                    split=split,
                    language=self.config.name,
                ) for split in ["train", "eval"]
            }
        else:
            raise ValueError("level can only be one of `document` or `passage`")
        
        language_files = dl_manager.download_and_extract(data_files)
        
        splits = [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": language_files["train"]}
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={"filepath": language_files["eval"]}
            )
        ]
        return splits
    
    def _generate_examples(self, filepath: str):
        with open(filepath, encoding="utf-8") as f:
            for idx, line in enumerate(f):
                if self.config.level == "document":
                    data = json.loads(line)
                    data["id"] = idx
                else:
                    data = {"id": idx, "text": line.strip()}

                yield idx, data