Issue number: closes #7763

Summary

Changes

This PR adds support for AWS Durable Execution SDK's DurableContext in Logger and Metrics decorators, addressing compatibility issues when using Powertools with durable Lambda functions.

Core Implementation:

• Added _unwrap_durable_context() helper function to detect and unwrap DurableContext via duck typing (checking for lambda_context and state attributes)
• Updated build_lambda_context_model() in logger to automatically unwrap DurableContext before accessing Lambda context properties
• Updated _add_cold_start_metric() in metrics base provider to unwrap DurableContext before passing to add_cold_start_metric()
• Enhanced docstrings for both inject_lambda_context and log_metrics decorators to document DurableContext support

Testing:

• Added 4 comprehensive tests for Logger's inject_lambda_context decorator with DurableContext
• Added 5 comprehensive tests for Metrics' log_metrics decorator with DurableContext
• All tests verify backward compatibility with standard LambdaContext
• Tests cover: basic functionality, log_event=True, clear_state=True, capture_cold_start_metric=True, and explicit function names

Quality:

• All existing tests pass (no regressions)
• Code formatting with ruff
• Linting with ruff check
• Type checking with mypy

User experience

Before:
Users using AWS Durable Execution SDK would encounter errors when using Logger or Metrics decorators because the decorators expected a standard LambdaContext but received a DurableContext wrapper instead.

from aws_durable_execution_sdk_python import DurableContext, durable_execution
from aws_lambda_powertools import Logger, Metrics

logger = Logger(service="durable")
metrics = Metrics(service="durable")

@durable_execution
@logger.inject_lambda_context(log_event=True)  # Raises AttributeError
@metrics.log_metrics(capture_cold_start_metric=True)  # Raises AttributeError
def lambda_handler(event: dict, context: DurableContext) -> str:
    logger.info("Processing")
    metrics.add_metric("ProcessedItems", 1, "Count")
    return "success"

After:
The decorators now seamlessly work with both standard LambdaContext and DurableContext. The unwrapping happens automatically and transparently to the user.

from aws_durable_execution_sdk_python import DurableContext, durable_execution
from aws_lambda_powertools import Logger, Metrics

logger = Logger(service="durable")
metrics = Metrics(service="durable")

@durable_execution
@logger.inject_lambda_context(log_event=True)  # Works seamlessly
@metrics.log_metrics(capture_cold_start_metric=True)  # Works seamlessly
def lambda_handler(event: dict, context: DurableContext) -> str:
    logger.info("Processing")
    metrics.add_metric("ProcessedItems", 1, "Count")
    return "success"

The implementation uses duck typing to detect DurableContext checking for lambda_context and state, automatically extracts the underlying LambdaContextand processes it normally.

This approach:
Requires no code changes from users
Maintains full backward compatibility
Follows the same pattern used in Idempotency utility
Is fully tested with both context types

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