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Middleware factory

Utility


Middleware factory provides a decorator factory to create your own middleware to run logic before, and after each Lambda invocation synchronously.

Key features

  • Run logic before, after, and handle exceptions
  • Trace each middleware when requested

Middleware with no params

You can create your own middleware using lambda_handler_decorator. The decorator factory expects 3 arguments in your function signature:

  • handler - Lambda function handler
  • event - Lambda function invocation event
  • context - Lambda function context object
app.py
from aws_lambda_powertools.middleware_factory import lambda_handler_decorator

@lambda_handler_decoratordef middleware_before_after(handler, event, context):    # logic_before_handler_execution()
    response = handler(event, context)
    # logic_after_handler_execution()
    return response

@middleware_before_afterdef lambda_handler(event, context):
    ...

Middleware with params

You can also have your own keyword arguments after the mandatory arguments.

app.py
@lambda_handler_decorator
def obfuscate_sensitive_data(handler, event, context, fields: List = None):    # Obfuscate email before calling Lambda handler
    if fields:
        for field in fields:
            field = event.get(field, "")
            if field in event:
                event[field] = obfuscate(field)

    return handler(event, context)

@obfuscate_sensitive_data(fields=["email"])def lambda_handler(event, context):
    ...

Tracing middleware execution

If you are making use of Tracer, you can trace the execution of your middleware to ease operations.

This makes use of an existing Tracer instance that you may have initialized anywhere in your code.

trace_middleware_execution.py
from aws_lambda_powertools.middleware_factory import lambda_handler_decorator

@lambda_handler_decorator(trace_execution=True)def my_middleware(handler, event, context):
    return handler(event, context)

@my_middleware
def lambda_handler(event, context):
    ...

When executed, your middleware name will appear in AWS X-Ray Trace details as ## middleware_name.

For advanced use cases, you can instantiate Tracer inside your middleware, and add annotations as well as metadata for additional operational insights.

app.py
from aws_lambda_powertools.middleware_factory import lambda_handler_decorator
from aws_lambda_powertools import Tracer

@lambda_handler_decorator(trace_execution=True)
def middleware_name(handler, event, context):
    tracer = Tracer() # Takes a copy of an existing tracer instance    tracer.add_annotation...    tracer.add_metadata...    return handler(event, context)

Tips

  • Use trace_execution to quickly understand the performance impact of your middlewares, and reduce or merge tasks when necessary
  • When nesting multiple middlewares, always return the handler with event and context, or response
  • Keep in mind Python decorators execution order. Lambda handler is actually called once (top-down)
  • Async middlewares are not supported

Testing your code

When unit testing middlewares with trace_execution option enabled, use POWERTOOLS_TRACE_DISABLED env var to safely disable Tracer.

pytest_disable_tracing.sh
POWERTOOLS_TRACE_DISABLED=1 python -m pytest
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