# coding=utf-8
# CodeGauntlt dataset loading script for Hugging Face Datasets
# path: codegauntlt.py

import json
import datasets

_DESCRIPTION = """\
CodeGauntlt is a multi-source dataset designed for evaluating and enhancing the robustness of AI code repair and generation agents. It introduces adversarially-constructed, obfuscated, or deceptive bugs across several programming languages, based on real-world and synthetic sources.
"""

_HOMEPAGE = "https://huggingface.co/datasets/HackerHardware/CodeGauntlt"

_CITATION = """\
@misc{codegauntlt2025,
  title={CodeGauntlt: A Dataset for Adversarial Evaluation of Code Repair Models},
  author={Esteban and Collaborators},
  year={2025},
  howpublished={\\url{https://huggingface.co/datasets/HackerHardware/CodeGauntlt}},
}
"""

class CodeGauntlt(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    def _info(self):
        features = datasets.Features(
            {
                "id": datasets.Value("string"),
                "source": datasets.Value("string"),
                "description": datasets.Value("string"),
                "code_buggy": datasets.Value("string"),
                "code_fixed": datasets.Value("string"),
                "bug_type": datasets.Value("string"),
                "tags": datasets.Value("string"),
                "metadata": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license="apache-2.0"
        )

    def _split_generators(self, dl_manager):
        data_dir = dl_manager.download_and_extract("./data")
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": f"{data_dir}/train.jsonl"}
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={"filepath": f"{data_dir}/validation.jsonl"}
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"filepath": f"{data_dir}/test.jsonl"}
            ),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            for i, line in enumerate(f):
                record = json.loads(line)
                yield i, record