from huggingface_hub import HfApi, snapshot_download
from loguru import logger

api = HfApi()


def download_dataset_snapshot(repo_id, local_dir):
    try:
        logger.info(f"Downloading dataset snapshot from {repo_id} to {local_dir}")
        snapshot_download(
            repo_id=repo_id,
            local_dir=local_dir,
            repo_type="dataset",
            tqdm_class=None,
        )
    except Exception as e:
        logger.error(f"Error downloading dataset snapshot from {repo_id} to {local_dir}: {e}. Restarting space.")
        api.restart_space(repo_id=repo_id)


def remove_files_from_dataset_repo(repo_id: str, path_patterns: list[str], commit_message: str = "Remove files"):
    """
    Remove files or directories matching specified patterns from a Hugging Face dataset repository.

    Args:
        repo_id: The ID of the dataset repository (e.g., "username/dataset-name")
        path_patterns: List of file or directory path patterns to remove
        commit_message: Message for the commit that removes the files
    """
    import fnmatch
    import os

    # Get all files in the repository
    repo_files = api.list_repo_files(repo_id=repo_id, repo_type="dataset")

    # Find files matching the patterns
    files_to_remove = []
    for pattern in path_patterns:
        matching_files = fnmatch.filter(repo_files, pattern)
        files_to_remove.extend(matching_files)

    # Delete each matching file
    for path in files_to_remove:
        try:
            api.delete_file(
                path_in_repo=path, repo_id=repo_id, repo_type="dataset", commit_message=f"{commit_message}: {path}"
            )
            print(f"Successfully removed {path} from {repo_id}")
        except Exception as e:
            print(f"Error removing {path}: {e}")


def update_dataset_info_readme(
    repo_id: str,
    dataset_info: dict,
    license_id: str = None,
    commit_message: str = "Update dataset_info in README.md",
):
    """
    Update the dataset_info section in the README.md file of a Hugging Face dataset repository.

    Args:
        repo_id: The ID of the dataset repository (e.g., "username/dataset-name")
        dataset_info: Dictionary containing dataset information to include in the README
        license_id: Optional license identifier (e.g., "mit", "cc-by-4.0")
        commit_message: Message for the commit

    Example dataset_info structure:
    {
        "features": [
            {"name": "text", "dtype": "string"},
            {"name": "label", "dtype": "int64"}
        ],
        "splits": [
            {"name": "train", "num_examples": 10000, "num_bytes": 1000000},
            {"name": "test", "num_examples": 1000, "num_bytes": 100000}
        ],
        "download_size": 1200000,
        "dataset_size": 1100000,
        "configs": [
            {
                "config_name": "default",
                "data_files": [
                    {"split": "train", "path": "data/train.csv"},
                    {"split": "test", "path": "data/test.csv"}
                ]
            }
        ]
    }
    """
    import re

    import yaml
    from huggingface_hub import HfApi

    api = HfApi()

    # Check if README.md exists
    try:
        readme_content = api.hf_hub_download(repo_id=repo_id, repo_type="dataset", filename="README.md", token=None)
        with open(readme_content, "r", encoding="utf-8") as f:
            content = f.read()
    except Exception:
        # Create a new README.md if it doesn't exist
        content = ""

    # Parse existing YAML front matter if it exists
    yaml_block = None
    yaml_match = re.search(r"---\s*\n(.*?)\n\s*---", content, re.DOTALL)

    if yaml_match:
        yaml_text = yaml_match.group(1)
        try:
            yaml_block = yaml.safe_load(yaml_text)
        except Exception as e:
            print(f"Error parsing existing YAML front matter: {e}")
            yaml_block = {}
    else:
        yaml_block = {}

    # Update or add dataset_info and license
    if dataset_info:
        yaml_block["dataset_info"] = dataset_info

    if license_id:
        yaml_block["license"] = license_id

    # Generate new YAML front matter
    new_yaml = yaml.dump(yaml_block, sort_keys=False, default_flow_style=False)
    new_yaml_block = f"---\n{new_yaml}---\n"

    # Replace existing YAML front matter or add it at the beginning
    if yaml_match:
        new_content = content[: yaml_match.start()] + new_yaml_block + content[yaml_match.end() :]
    else:
        new_content = new_yaml_block + content

    # Create a temporary file with the new content
    import tempfile

    with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".md") as temp_file:
        temp_file.write(new_content)
        temp_path = temp_file.name

    # Upload the updated README.md
    try:
        api.upload_file(
            path_or_fileobj=temp_path,
            path_in_repo="README.md",
            repo_id=repo_id,
            repo_type="dataset",
            commit_message=commit_message,
        )
        print(f"Successfully updated README.md in {repo_id}")
    except Exception as e:
        print(f"Error updating README.md: {e}")

    # Clean up temporary file
    import os

    os.unlink(temp_path)