# Auto-generated transaction service
"""Cross-table transaction service for atomic operations.

This service provides methods for executing atomic transactions across multiple
DynamoDB tables using TransactWriteItems and TransactGetItems APIs.

Currently supports:
- TransactWrite: Atomic write operations (Put, Update, Delete, ConditionCheck)
- TransactGet: Atomic read operations (Get)

Future versions may support additional cross-table patterns.
"""

from __future__ import annotations

import boto3
from entities import EmailLookup, User
from typing import Any


class TransactionService:
    """Service for cross-table transactional operations.

    This service handles atomic operations that span multiple DynamoDB tables.
    All operations are atomic - either all succeed or all fail together.

    Attributes:
        dynamodb: Boto3 DynamoDB resource for multi-table access
        client: Boto3 DynamoDB client for transaction operations
    """

    def __init__(self, dynamodb_resource: boto3.resource):
        """Initialize transaction service.

        Args:
            dynamodb_resource: Boto3 DynamoDB resource configured for your region
                              Example: boto3.resource('dynamodb', region_name='us-west-2')
        """
        self.dynamodb = dynamodb_resource
        self.client = dynamodb_resource.meta.client

    def register_user(self, user: User, email_lookup: EmailLookup) -> bool:
        """Create user and email lookup atomically

        Args:
            user: User entity to process
            email_lookup: EmailLookup entity to process

        Returns:
            bool: True if transaction succeeded, False otherwise

        Raises:
            ValueError: If entity validation fails or relationships are invalid
            ClientError: If transaction fails (e.g., condition check failure, item already exists)
        """
        # TODO: Implement Access Pattern #100
        # Operation: TransactWrite | Tables: Users, EmailLookup
        #
        # Cross-Table Transaction Example:
        # Step 1: Validate entity relationships (if needed)
        # Example: Ensure email_lookup.user_id matches user.user_id
        #
        # Step 2: Build keys for all entities
        # User.build_pk_for_lookup(...)
        # Condition: attribute_not_exists(pk)
        # EmailLookup.build_pk_for_lookup(...)
        # Condition: attribute_not_exists(pk)
        #
        # Step 3: Convert entities to DynamoDB items and add keys
        # user_item = user.model_dump(exclude_none=True)
        # user_item['pk'] = user.pk()
        # email_lookup_item = email_lookup.model_dump(exclude_none=True)
        # email_lookup_item['pk'] = email_lookup.pk()
        #
        # Step 4: Execute transaction
        # response = self.client.transact_write_items(
        #     TransactItems=[
        #         {
        #             'Put': {
        #                 'TableName': 'Users',
        #                 'Item': <entity>_item,  # Item includes partition key from Step 3
        #                 'ConditionExpression': 'attribute_not_exists(pk)'
        #             }
        #         },
        #         {
        #             'Put': {
        #                 'TableName': 'EmailLookup',
        #                 'Item': <entity>_item,  # Item includes partition key from Step 3
        #                 'ConditionExpression': 'attribute_not_exists(pk)'
        #             }
        #         },
        #     ]
        # )
        #
        # Step 5: Handle errors
        # try:
        #     response = self.client.transact_write_items(...)
        #     return True  # or appropriate return value
        # except ClientError as e:
        #     if e.response['Error']['Code'] == 'TransactionCanceledException':
        #         # Handle condition check failures
        #         reasons = e.response['Error'].get('CancellationReasons', [])
        #         # Parse reasons to determine which condition failed
        #         raise ValueError(f"Transaction failed: {reasons}")
        #     raise
        pass

    def delete_user_with_email(self, user_id: str, email: str) -> bool:
        """Delete user and email lookup atomically

        Args:
            user_id: str value
            email: str value

        Returns:
            bool: True if transaction succeeded, False otherwise

        Raises:
            ValueError: If entity validation fails or relationships are invalid
            ClientError: If transaction fails (e.g., condition check failure, item already exists)
        """
        # TODO: Implement Access Pattern #101
        # Operation: TransactWrite | Tables: Users, EmailLookup
        #
        # Cross-Table Transaction Example:
        # Step 1: Validate entity relationships (if needed)
        # Example: Ensure email_lookup.user_id matches user.user_id
        #
        # Step 2: Build keys for all entities
        # User.build_pk_for_lookup(...)
        # Condition: attribute_exists(pk)
        # EmailLookup.build_pk_for_lookup(...)
        # Condition: attribute_exists(pk)
        #
        # Step 3: Convert entities to DynamoDB items and add keys
        #
        # Step 4: Execute transaction
        # response = self.client.transact_write_items(
        #     TransactItems=[
        #         {
        #             'Delete': {
        #                 'TableName': 'Users',
        #                 'Key': {'pk': <pk_value>},
        #                 'ConditionExpression': 'attribute_exists(pk)'
        #             }
        #         },
        #         {
        #             'Delete': {
        #                 'TableName': 'EmailLookup',
        #                 'Key': {'pk': <pk_value>},
        #                 'ConditionExpression': 'attribute_exists(pk)'
        #             }
        #         },
        #     ]
        # )
        #
        # Step 5: Handle errors
        # try:
        #     response = self.client.transact_write_items(...)
        #     return True  # or appropriate return value
        # except ClientError as e:
        #     if e.response['Error']['Code'] == 'TransactionCanceledException':
        #         # Handle condition check failures
        #         reasons = e.response['Error'].get('CancellationReasons', [])
        #         # Parse reasons to determine which condition failed
        #         raise ValueError(f"Transaction failed: {reasons}")
        #     raise
        pass

    def get_user_and_email(self, user_id: str, email: str) -> dict[str, Any]:
        """Get user and email lookup atomically

        Args:
            user_id: str value
            email: str value

        Returns:
            dict[str, Any]: Dictionary containing retrieved entities

        Raises:
            ValueError: If entity validation fails or relationships are invalid
            ClientError: If transaction fails (e.g., condition check failure, item already exists)
        """
        # TODO: Implement Access Pattern #102
        # Operation: TransactGet | Tables: Users, EmailLookup
        #
        # Cross-Table Transaction Example:
        # Step 1: Build keys for all entities
        # User.build_pk_for_lookup(...)
        # EmailLookup.build_pk_for_lookup(...)
        #
        # Step 2: Execute transaction
        # response = self.client.transact_get_items(
        #     TransactItems=[
        #         {
        #             'Get': {
        #                 'TableName': 'Users',
        #                 'Key': {'pk': <pk_value>}
        #             }
        #         },
        #         {
        #             'Get': {
        #                 'TableName': 'EmailLookup',
        #                 'Key': {'pk': <pk_value>}
        #             }
        #         },
        #     ]
        # )
        #
        # Step 3: Parse and return results
        # items = response.get('Responses', [])
        # result = {}
        # if items[0].get('Item'):
        #     result['user'] = User(**items[0]['Item'])
        # if items[1].get('Item'):
        #     result['emaillookup'] = EmailLookup(**items[1]['Item'])
        # return result
        pass
