import os
from typing import Any, cast

import boto3
import requests
from boto3.resources.base import ServiceResource
from botocore.client import BaseClient
from botocore.exceptions import ClientError
from mypy_boto3_bedrock_runtime import BedrockRuntimeClient
from mypy_boto3_dynamodb.service_resource import DynamoDBServiceResource
from mypy_boto3_s3 import Client as S3Client
from mypy_boto3_ssm import Client as SSMClient

from vsp.shared import config, logger_factory
import os

logger = logger_factory.get_logger(__name__)

USE_ENV_VAR_INSTEAD = True
def path_to_env_var(path: str):
    # Remove leading slash and replace other slashes with underscores
    env_var = path.lstrip('/').replace('/', '_').upper()
    return env_var


def _get_session() -> boto3.Session:
    """
    Creates and returns a boto3 session based on the execution environment.

    If running in ECS (determined by the presence of AWS_CONTAINER_CREDENTIALS_RELATIVE_URI
    environment variable), it returns a default boto3 session which will use the ECS task's
    IAM role. Otherwise, it returns a session using the "Geometric-PowerUserAccess" profile
    for local execution.

    Returns:
        boto3.Session: A boto3 session configured for the current execution environment.
    """
    if "AWS_CONTAINER_CREDENTIALS_RELATIVE_URI" in os.environ:
        return boto3.Session()
    else:
        return boto3.Session(profile_name="Geometric-PowerUserAccess")


class ECSCredentialsError(Exception):
    """Raised when there's an error retrieving ECS task credentials."""


class RoleAssumptionError(Exception):
    """Raised when there's an error assuming an IAM role."""


def get_credentials() -> dict[str, str]:
    """
    Retrieves AWS credentials based on the execution environment.

    If running in ECS, it retrieves credentials from the ECS task's metadata.
    If running locally, it assumes the role specified in the configuration.

    Returns:
        dict[str, str]: A dictionary containing AccessKeyId, SecretAccessKey, and SessionToken.

    Raises:
        ECSCredentialsError: If there's an error retrieving ECS task credentials.
        RoleAssumptionError: If there's an error assuming the specified IAM role.
        ValueError: If the execution environment is not recognized.
    """
    session = _get_session()
    if "AWS_CONTAINER_CREDENTIALS_RELATIVE_URI" in os.environ:
        logger.info("Using ECS task's IAM role for credentials")
        return _get_ecs_credentials()
    else:
        logger.info("Assuming role", role_arn=config.get_role_arn())
        return _assume_role(session)


def _get_ecs_credentials() -> dict[str, str]:
    ecs_creds_url = f"http://169.254.170.2{os.environ.get('AWS_CONTAINER_CREDENTIALS_RELATIVE_URI')}"
    response = requests.get(ecs_creds_url, timeout=5)
    if response.status_code == 200:
        creds = response.json()
        return {
            "AccessKeyId": creds["AccessKeyId"],
            "SecretAccessKey": creds["SecretAccessKey"],
            "SessionToken": creds["Token"],
        }
    else:
        raise ECSCredentialsError(f"Failed to retrieve ECS task credentials. Status code: {response.status_code}")


def _assume_role(session: boto3.Session) -> dict[str, str]:
    try:
        sts_client = session.client("sts")
        assumed_role = sts_client.assume_role(RoleArn=config.get_role_arn(), RoleSessionName="AssumeRoleSession")[
            "Credentials"
        ]
        logger.info("Role assumed successfully")
        return {
            "AccessKeyId": assumed_role["AccessKeyId"],
            "SecretAccessKey": assumed_role["SecretAccessKey"],
            "SessionToken": assumed_role["SessionToken"],
        }
    except ClientError as e:
        raise RoleAssumptionError(f"Failed to assume role: {e}") from e


def _get_boto3_client(service_name: str) -> BaseClient:
    """
    Creates and returns a boto3 client for the specified AWS service.

    This function uses the session and credentials appropriate for the current
    execution environment (ECS or local).

    Args:
        service_name (str): The name of the AWS service for which to create a client.

    Returns:
        BaseClient: A boto3 client for the specified service.
    """
    logger.info("Creating boto3 client", service=service_name)
    session = _get_session()
    credentials = get_credentials()
    kwargs: dict[str, Any] = {"region_name": config.get_aws_region(), "use_ssl": True}
    if credentials:
        kwargs.update(
            {
                "aws_access_key_id": credentials["AccessKeyId"],
                "aws_secret_access_key": credentials["SecretAccessKey"],
                "aws_session_token": credentials["SessionToken"],
            }
        )
    return session.client(service_name, **kwargs)


def _get_boto3_resource(service_name: str) -> ServiceResource:
    """
    Creates and returns a boto3 resource for the specified AWS service.

    This function uses the session and credentials appropriate for the current
    execution environment (ECS or local).

    Args:
        service_name (str): The name of the AWS service for which to create a resource.

    Returns:
        ServiceResource: A boto3 resource for the specified service.
    """
    logger.info("Creating boto3 resource", service=service_name)
    session = _get_session()
    credentials = get_credentials()
    kwargs: dict[str, Any] = {"region_name": config.get_aws_region(), "use_ssl": True}
    if credentials:
        kwargs.update(
            {
                "aws_access_key_id": credentials["AccessKeyId"],
                "aws_secret_access_key": credentials["SecretAccessKey"],
                "aws_session_token": credentials["SessionToken"],
            }
        )
    return session.resource(service_name, **kwargs)


def get_ssm_client() -> SSMClient:
    """
    Returns an instance of the AWS Systems Manager (SSM) client.

    This client can be used to interact with the AWS Systems Manager service,
    such as retrieving parameters from the Parameter Store.

    Returns:
        SSMClient: An SSM client configured for the current execution environment.
    """
    return cast(SSMClient, _get_boto3_client("ssm"))


def get_s3_client() -> S3Client:
    """
    Returns an instance of the AWS S3 client.
    This client can be used to interact with Amazon S3 buckets and objects.

    Returns:
        S3Client: An S3 client configured for the current execution environment.
    """
    return cast(S3Client, _get_boto3_client("s3"))


def get_dynamodb_resource() -> DynamoDBServiceResource:
    """
    Returns an instance of the AWS DynamoDB resource.

    This resource can be used to interact with DynamoDB tables and items.

    Returns:
        DynamoDBServiceResource: A DynamoDB resource configured for the current execution environment.
    """
    return cast(DynamoDBServiceResource, _get_boto3_resource("dynamodb"))


def _assume_intermediate_role(role_arn: str, session_name: str) -> dict[str, str]:
    """
    Assumes an IAM role and returns the temporary credentials.

    Args:
        role_arn (str): The ARN of the role to assume.
        session_name (str): An identifier for the assumed role session.

    Returns:
        dict[str, str]: The temporary credentials for the assumed role.

    Raises:
        ClientError: If there's an error assuming the role.
    """
    logger.info("Attempting to assume role", role_arn=role_arn)
    try:
        sts_client = _get_boto3_client("sts")
        assumed_role = sts_client.assume_role(RoleArn=role_arn, RoleSessionName=session_name)["Credentials"]
        logger.info("Role assumed successfully")
        return {
            "AccessKeyId": assumed_role["AccessKeyId"],
            "SecretAccessKey": assumed_role["SecretAccessKey"],
            "SessionToken": assumed_role["SessionToken"],
        }
    except ClientError as e:
        logger.error("Error assuming role", error=str(e))
        raise


def get_bedrock_client() -> BedrockRuntimeClient:
    """
    Returns a Bedrock client with a specific assumed role session.

    Returns:
        BedrockRuntimeClient: A Bedrock client with the assumed role session.
    """
    role_arn = f"arn:aws:iam::{config.get_bedrock_account()}:role/BedrockAccess"
    assumed_role = _assume_intermediate_role(role_arn, "BedrockAssumeRoleSession")
    return cast(
        BedrockRuntimeClient,
        boto3.client(
            "bedrock-runtime",
            aws_access_key_id=assumed_role["AccessKeyId"],
            aws_secret_access_key=assumed_role["SecretAccessKey"],
            aws_session_token=assumed_role["SessionToken"],
            region_name=config.get_aws_region(),
        ),
    )


class ParameterNotFoundError(Exception):
    """Raised when a parameter is not found in the Parameter Store."""

    pass


class ParameterStoreAccessError(Exception):
    """Raised when there's an error accessing the Parameter Store."""

    pass


def fetch_from_parameter_store(parameter_name: str, is_secret: bool = False) -> str:
    """
    Fetches the value of a parameter from AWS Systems Manager Parameter Store.

    This function retrieves a parameter value, handling various potential errors.
    The 'is_secret' parameter is included for backwards compatibility but does not
    affect the function's behavior, as all parameters are retrieved with decryption.

    Args:
        parameter_name (str): The name of the parameter to fetch.
        is_secret (bool): Whether the parameter is a secret. Defaults to False.

    Returns:
        str: The value of the parameter

    Raises:
        ParameterNotFoundError: If the parameter is not found.
        ParameterStoreAccessError: If there's an error accessing the Parameter Store.
    """
    if USE_ENV_VAR_INSTEAD:
        env_var_name = path_to_env_var(parameter_name)
        logger.info("Fetching parameter from environment variable", parameter=env_var_name)
        value = os.environ.get(env_var_name)
        if value is None:
            raise ParameterNotFoundError(f"Environment variable '{env_var_name}' not found")
        return value


    logger.info("Fetching parameter from Parameter Store", parameter=parameter_name)
    ssm_client = get_ssm_client()
    try:
        response = ssm_client.get_parameter(Name=parameter_name, WithDecryption=is_secret)
    except ssm_client.exceptions.ParameterNotFound:
        raise ParameterNotFoundError(f"Parameter '{parameter_name}' not found")
    except ClientError as e:
        raise ParameterStoreAccessError(f"Error accessing Parameter Store: {str(e)}")

    logger.info("Successfully fetched parameter", parameter=parameter_name)
    return str(response["Parameter"].get("Value", ""))