import json
from pathlib import Path
from typing import List, Optional, Union

import numpy as np
import yaml


class NumpyJsonEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, np.integer):
            return int(obj)
        if isinstance(obj, np.floating):
            return float(obj)
        if isinstance(obj, np.ndarray):
            return obj.tolist()
        return super(NumpyJsonEncoder, self).default(obj)


def list_files_with_extensions(
    directory: Union[str, Path], extensions: Optional[List[str]] = None
) -> List[Path]:
    """
    List files in a directory with specified extensions or
        all files if no extensions are provided.

    Args:
        directory (Union[str, Path]): The directory path as a string or Path object.
        extensions (Optional[List[str]]): A list of file extensions to filter.
            Default is None, which lists all files.

    Returns:
        (List[Path]): A list of Path objects for the matching files.

    Examples:
        ```python
        >>> import supervision as sv

        >>> # List all files in the directory
        >>> files = sv.list_files_with_extensions(directory='my_directory')

        >>> # List only files with '.txt' and '.md' extensions
        >>> files = sv.list_files_with_extensions(
        ...     directory='my_directory', extensions=['txt', 'md'])
        ```
    """

    directory = Path(directory)
    files_with_extensions = []

    if extensions is not None:
        for ext in extensions:
            files_with_extensions.extend(directory.glob(f"*.{ext}"))
    else:
        files_with_extensions.extend(directory.glob("*"))

    return files_with_extensions


def read_txt_file(file_path: str, skip_empty: bool = False) -> List[str]:
    """
    Read a text file and return a list of strings without newline characters.
    Optionally skip empty lines.

    Args:
        file_path (str): The path to the text file.
        skip_empty (bool): If True, skip lines that are empty or contain only
            whitespace. Default is False.

    Returns:
        List[str]: A list of strings representing the lines in the text file.
    """
    with open(file_path, "r") as file:
        if skip_empty:
            lines = [line.rstrip("\n") for line in file if line.strip()]
        else:
            lines = [line.rstrip("\n") for line in file]

    return lines


def save_text_file(lines: List[str], file_path: str):
    """
    Write a list of strings to a text file, each string on a new line.

    Args:
        lines (List[str]): The list of strings to be written to the file.
        file_path (str): The path to the text file.
    """
    with open(file_path, "w") as file:
        for line in lines:
            file.write(line + "\n")


def read_json_file(file_path: str) -> dict:
    """
    Read a json file and return a dict.

    Args:
        file_path (str): The path to the json file.

    Returns:
        dict: A dict of annotations information
    """
    with open(file_path, "r") as file:
        data = json.load(file)
    return data


def save_json_file(data: dict, file_path: str, indent: int = 3) -> None:
    """
    Write a dict to a json file.

    Args:
        indent:
        data (dict): dict with unique keys and value as pair.
        file_path (str): The path to the json file.
    """
    with open(file_path, "w") as fp:
        json.dump(data, fp, cls=NumpyJsonEncoder, indent=indent)


def read_yaml_file(file_path: str) -> dict:
    """
    Read a yaml file and return a dict.

    Args:
        file_path (str): The path to the yaml file.

    Returns:
        dict: A dict of content information
    """
    with open(file_path, "r") as file:
        data = yaml.safe_load(file)
    return data


def save_yaml_file(data: dict, file_path: str) -> None:
    """
    Save a dict to a json file.

    Args:
        indent:
        data (dict): dict with unique keys and value as pair.
        file_path (str): The path to the json file.
    """

    with open(file_path, "w") as outfile:
        yaml.dump(data, outfile, sort_keys=False, default_flow_style=None)