# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "datasets",
#     "dynaword",
# ]
#
# [tool.uv.sources]
# dynaword = { git = "https://huggingface.co/datasets/danish-foundation-models/danish-dynaword" }
# ///

"""
Script for downloading and processing the dataset

Note: To run this script, you need to set `GIT_LFS_SKIP_SMUDGE=1` to be able to install dynaword:

```bash
GIT_LFS_SKIP_SMUDGE=1 uv run data/enevaeldens_nyheder/create.py
```
"""

import logging
from datetime import date
from pathlib import Path
from typing import Any, cast

from datasets import Dataset, load_dataset

from dynaword.process_dataset import (
    add_token_count,
    ensure_column_order,
    remove_duplicate_text,
    remove_empty_texts,
)

logger = logging.getLogger(__name__)

SOURCE = "enevaeldens_nyheder"


def reformat_samples(example: dict[str, Any]) -> dict[str, Any]:
    creation_date = example["date"]
    # Reformatting the date to YYYY-MM-DD format
    start = creation_date
    end = creation_date
    return {
        "id": f"{SOURCE}_{example['id']}",
        "text": example["text"],
        "source": SOURCE,
        "added": date.today().strftime("%Y-%m-%d"),
        "created": f"{start}, {end}",
    }


def main():
    dataset = load_dataset(
        "JohanHeinsen/ENO",
        split="train",
        revision="009f45ef63a1a41705781840807eb620f380d17d",
    )
    dataset = cast(Dataset, dataset)

    logger.info("Removing 1 word texts")
    len_ds = len(dataset)
    dataset = dataset.filter(
        lambda x: len(x["text"].split()) >= 2
    )  # require at least 2 word in the text
    logger.info(f"Filtered {len_ds - len(dataset)} 1 word examples")

    logger.info("Filtering out texts with predicted word acuracy < 0.7")
    dataset = dataset.filter(lambda x: x["pwa"] >= 0.7)
    logger.info(f"Filtered {len_ds - len(dataset)} low accuracy examples")

    dataset = dataset.map(reformat_samples)

    dataset = remove_empty_texts(dataset)  # remove rows with empty text
    dataset = remove_duplicate_text(dataset)  # remove rows with duplicate text
    dataset = add_token_count(dataset)
    dataset = ensure_column_order(dataset)

    dataset.to_parquet(
        Path(__file__).parent / f"{SOURCE}.parquet",
    )


if __name__ == "__main__":
    log_path = Path(__file__).parent / f"{SOURCE}.log"
    logging.basicConfig(
        level=logging.INFO,
        format="%(asctime)s - %(levelname)s - %(message)s",
        handlers=[
            logging.StreamHandler(),
            logging.FileHandler(log_path),
        ],
    )
    main()