import aioboto3
import pandas as pd
from io import StringIO
from typing import Optional, Union
import os

AWS_ACCESS_KEY_ID = os.getenv('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.getenv('AWS_SECRET_ACCESS_KEY')
S3_BUCKET = os.getenv('S3_BUCKET')
S3_VIDEO_PATH = 'sample videos'
S3_MODEL_PATH = 'models'
S3_DATA_PATH = '3d_animation_arena/results'

async def download_from_s3(file_key : str, target_dir: str, bucket : str = S3_BUCKET) -> Optional[str]:
    """
    Downloads a file from an S3 bucket.

    Args:
        file_key (str): The key of the file in the S3 bucket, including extension.
        target_dir (str): The path to the directory to save the downloaded file.
        bucket (str, optional): The name of the S3 bucket.

    Returns:
        Optional[str]: The path to the file or None if the download fails.
    """
    session = aioboto3.Session()
    target_path = os.path.join(target_dir, file_key)

    async with session.client(
        's3',
        aws_access_key_id=AWS_ACCESS_KEY_ID,
        aws_secret_access_key=AWS_SECRET_ACCESS_KEY
    ) as s3_client:
        try:
            os.makedirs(target_dir, exist_ok=True)
            if os.path.exists(target_path):
                print(f'{file_key} already exists in {target_dir}')
                return target_path
            with open(target_path, 'wb') as f:
                match file_key.split('.')[-1]:
                    case 'mp4':
                        await s3_client.download_fileobj(bucket, os.path.join(S3_VIDEO_PATH, file_key), f)
                    case 'glb'|'obj'|'stl'|'gltf'|'splat'|'ply':
                        await s3_client.download_fileobj(bucket, os.path.join(S3_MODEL_PATH, file_key), f)
                    case _:
                        print(f"Unsupported file type: {file_key}")
                        raise ValueError(f"Unsupported file type: {file_key}")
            return target_path
        except Exception as e:
            print(f'Error downloading {file_key} from bucket {bucket}: {e}')
            raise e
            

async def read_from_s3(file_key : str, bucket : str = S3_BUCKET) -> Optional[Union[pd.DataFrame, str]]:
    """
    Reads a file from an S3 bucket based on its file extension and returns the appropriate data type.

    Args:
        file_key (str): The key of the file in the S3 bucket.
        bucket (str, optional): The name of the S3 bucket.

    Returns:
        Optional[Union[pd.DataFrame, str]]: 
            - A pandas DataFrame if the file is a CSV.
            - A temporary file path (str) if the file is a GLB.
            - A presigned URL (str) if the file is an MP4.
            - None if the file type is unsupported.
    """
    session = aioboto3.Session()
    async with session.client(
        's3',
        aws_access_key_id=AWS_ACCESS_KEY_ID,
        aws_secret_access_key=AWS_SECRET_ACCESS_KEY
    ) as s3_client:
        try:
            match file_key.split('.')[-1]:
                case 'csv':
                    response = await s3_client.get_object(Bucket=bucket, Key=os.path.join(S3_DATA_PATH, file_key))
                    content = await response['Body'].read()
                    result = pd.read_csv(StringIO(content.decode("utf-8")))
                    return result
                case _:
                    print(f"Unsupported file type for reading: {file_key}")
                    raise ValueError(f"Unsupported file type for reading: {file_key}")
        except Exception as e:
            print(f'Error reading {file_key} from bucket {bucket}: {e}')
            raise e


async def write_to_s3(file_key : str, dataframe: pd.DataFrame, bucket : str = S3_BUCKET) -> None:
    """
    Writes a pandas DataFrame to an S3 bucket as a CSV file.

    Args:
        file_key (str): The key (file name) under which the file will be stored in the S3 bucket.
        dataframe (pd.DataFrame): The pandas DataFrame to write to the S3 bucket.
        bucket (str, optional): The name of the S3 bucket.

    Raises:
        Exception: Reraises any exception encountered during the write process.
    """
    session = aioboto3.Session()
    async with session.client(
        's3',
        aws_access_key_id=AWS_ACCESS_KEY_ID,
        aws_secret_access_key=AWS_SECRET_ACCESS_KEY
    ) as s3_client:
        try:
            match file_key.split('.')[-1]:
                case 'csv':
                    csv_buffer = StringIO()
                    dataframe.to_csv(csv_buffer, index=False)
                    await s3_client.put_object(
                        Bucket=bucket, 
                        Key=os.path.join(S3_DATA_PATH, file_key), 
                        Body=csv_buffer.getvalue()
                    )
                case _:
                    print(f"Unsupported file type for writing: {file_key}")
                    raise ValueError(f"Unsupported file type for writing: {file_key}")
        except Exception as e:
            print(f'Error writing {file_key} to bucket {bucket}: {e}')
            raise e