aws-lambda-decorators

A set of Python decorators to ease the development of AWS lambda functions.

Installation

The easiest way to use these AWS Lambda Decorators is to install them through Pip:

pip install aws-lambda-decorators

Package Contents

Decorators

The current list of AWS Lambda Python Decorators includes:

• extract: a decorator to extract and validate specific keys of a dictionary parameter passed to a AWS Lambda function.
• extract_from_event: a facade of extract to extract and validate keys from an AWS API Gateway lambda function event parameter.
• extract_from_context: a facade of extract to extract and validate keys from an AWS API Gateway lambda function context parameter.
• extract_from_ssm: a decorator to extract from AWS SSM the values of a set of parameter keys.
• validate: a decorator to validate a list of function parameters.
• log: a decorator to log the parameters passed to the lambda function and/or the response of the lambda function.
• handle_exceptions: a decorator to handle any type of declared exception generated by the lambda function.
• response_body_as_json: a decorator to transform a response dictionary body to a json string.

Validators

Currently, the package offers 2 validators:

• Mandatory: Checks if a parameter has a value.
• RegexValidator: Checks a parameter against a regular expression.

Decoders

The package offers functions to decode from JSON and JWT.

• decode_json: decodes/converts a json string to a python dictionary
• decode_jwt: decodes/converts a JWT string to a python dictionary

Examples

extract

This decorator extracts and validates values from dictionary parameters passed to a Lambda Function.

• The decorator takes a list of Parameter objects.
• Each Parameter object requires a non-empty path to the parameter in the dictionary, and the name of the dictionary (func_param_name)
• The parameter value is extracted and added as a kwarg to the lambda handler (or any other decorated function/method).
• You can add the parameter to the handler signature, or access it in the handler through kwargs.
• The name of the extracted parameter is defaulted to the last element of the path name, but can be changed by passing a (valid pythonic variable name) var_name
• You can define a default value for the parameter in the Parameter or in the lambda handler itself.
• A 400 exception is raised when the parameter cannot be extracted or when it does not validate.
• A variable path (e.g. '/headers/Authorization[jwt]/sub') can be annotated to specify a decoding. In the example, Authorization might contain a JWT, which needs to be decoded before accessing the "sub" element.

Example: code | test

@extract(parameters=[
    Parameter(path='/parent/my_param', func_param_name='a_dictionary'),  # extracts a non mandatory my_param from a_dictionary
    Parameter(path='/parent/missing_non_mandatory', func_param_name='a_dictionary', default='I am missing'),  # extracts a non mandatory missing_non_mandatory from a_dictionary
    Parameter(path='/parent/missing_mandatory', func_param_name='a_dictionary'),  # does not fail as the parameter is not validated as mandatory
    Parameter(path='/parent/child/id', validators=[Mandatory], var_name='user_id', func_param_name='another_dictionary')  # extracts a mandatory id as "user_id" from another_dictionary
])
def extract_example(a_dictionary, another_dictionary, my_param='aDefaultValue', missing_non_mandatory='I am missing', missing_mandatory=None, user_id=None):
    """
        Given these two dictionaries:

        a_dictionary = { 
            'parent': { 
                'my_param': 'Hello!' 
            }, 
            'other': 'other value' 
        }

        another_dictionary = { 
            'parent': { 
                'child': { 
                    'id': '123' 
                } 
            } 
        }

        you can now access the extracted parameters directly: 
    """
    return my_param, missing_non_mandatory, missing_mandatory, user_id

Or you can use kwargs instead of specific parameter names:

Example: code | test

@extract(parameters=[
    Parameter(path='/parent/my_param', func_param_name='a_dictionary')  # extracts a non mandatory my_param from a_dictionary
])
def extract_to_kwargs_example(a_dictionary, **kwargs):
    """
        a_dictionary = { 
            'parent': { 
                'my_param': 'Hello!' 
            }, 
            'other': 'other value' 
        }
    """
    return kwargs['my_param']  # returns 'Hello!'

A missing mandatory parameter, or a parameter that fails validation, will raise an exception:

Example: code | test 1 | test 2

@extract(parameters=[
    Parameter(path='/parent/mandatory_param', func_param_name='a_dictionary', validators=[Mandatory])  # extracts a mandatory mandatory_param from a_dictionary
])
def extract_mandatory_param_example(a_dictionary, mandatory_param=None):
    return 'Here!'  # this part will never be reached, if the mandatory_param is missing

response = extract_mandatory_param_example({'parent': {'my_param': 'Hello!'}, 'other': 'other value'} )

print(response)  # prints { 'statusCode': 400, 'body': 'Error extracting parameters' } and logs a more detailed error

You can decode any part of the parameter path from json or any other existing annotation.

Example: code | test

@extract(parameters=[
    Parameter(path='/parent[json]/my_param', func_param_name='a_dictionary')  # extracts a non mandatory my_param from a_dictionary
])
def extract_from_json_example(a_dictionary, my_param=None):
    """
        a_dictionary = { 
            'parent': '{"my_param": "Hello!" }', 
            'other': 'other value' 
        }
    """
    return my_param  # returns 'Hello!'

extract_from_event

This decorator is just a facade to the extract method to be used in AWS Api Gateway Lambdas. It automatically extracts from the event lambda parameter.

Example: code | test

@extract_from_event(parameters=[
    Parameter(path='/body[json]/my_param', validators=[Mandatory]),  # extracts a mandatory my_param from the json body of the event
    Parameter(path='/headers/Authorization[jwt]/sub', validators=[Mandatory], var_name='user_id')  # extract the mandatory sub value as user_id from the authorization JWT
])
def extract_from_event_example(event, context, my_param=None, user_id=None):
    """
        event = { 
            'body': '{"my_param": "Hello!"}', 
            'headers': { 
                'Authorization': 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c' 
            } 
        }
    """
    return my_param, user_id  # returns ('Hello!', '1234567890')

extract_from_context

This decorator is just a facade to the extract method to be used in AWS Api Gateway Lambdas. It automatically extracts from the context lambda parameter.

Example: code | test

@extract_from_context(parameters=[
    Parameter(path='/parent/my_param', validators=[Mandatory])  # extracts a mandatory my_param from the parent element in context
])
def extract_from_context_example(event, context, my_param=None):
    """
        context = {
            'parent': {
                'my_param': 'Hello!'
            }
        }
    """    
    return my_param  # returns 'Hello!'

extract_from_ssm

This decorator extracts a parameter from AWS SSM and passes the parameter down to your function as a kwarg.

• The decorator takes a list of SSMParameter objects.
• Each SSMParameter object requires the name of the SSM parameter (ssm_name)
• If no var_name is passed in, the extracted value is passed to the function with the ssm_name name

Example: code | test

@extract_from_ssm(ssm_parameters=[
    SSMParameter(ssm_name='one_key'),  # extracts the value of one_key from SSM as a kwarg named "one_key"
    SSMParameter(ssm_name='another_key', var_name="another")  # extracts another_key as a kwarg named "another"
])
def extract_from_ssm_example(your_func_params, one_key=None, another=None):
    return your_func_params, one_key, another

validate

This decorator validates a list of non dictionary parameters from your lambda function.

• The decorator takes a list of ValidatedParameter objects.
• Each parameter object needs the name of the lambda function parameter that it is going to be validated, and the list of rules to validate.
• A 400 exception is raised when the parameter does not validate.

Example: code | test

@validate(parameters=[
    ValidatedParameter(func_param_name='a_param', validators=[Mandatory]),  # validates a_param as mandatory
    ValidatedParameter(func_param_name='another_param', validators=[Mandatory, RegexValidator(r'\d+')])  # validates another_param as mandatory and containing only digits
])
def validate_example(a_param, another_param):
    return a_param, another_param  # returns 'Hello!', '123456

validate_example('Hello!', '123456')

Given the same function validate_example, a 400 exception is returned if at least one parameter does not validate:

validate_example('Hello!', 'ABCD')  # returns a 400 status code and an error message

log

This decorator allows for logging the function arguments and/or the response.

Example: code | test

@log(parameters=True, response=True)
def log_example(parameters): 
    return 'Done!'

log_example('Hello!')  # logs 'Hello!' and 'Done!'

handle_exceptions

This decorator handles a list of exceptions, returning a 400 response containing the specified friendly message to the caller.

• The decorator takes a list of ExceptionHandler objects.
• Each ExceptionHandler requires the type of exception to check, and the friendly message to return to the caller.

Example: code | test

@handle_exceptions(handlers=[
    ExceptionHandler(ClientError, "Your message when a client error happens.")
])
def handle_exceptions_example():
    dynamodb = boto3.resource('dynamodb')
    table = dynamodb.Table('non_existing_table')
    table.query(KeyConditionExpression=Key('user_id').eq(user_id))
    # ...

handle_exceptions_example()  # returns {'body': 'Your message when a client error happens.', 'statusCode': 400}

response_body_as_json

This decorator ensures that, if the response contains a body, the body is dumped as json.

• Returns a 500 error if the response body cannot be dumped as json.

Example: code | test

@response_body_as_json
def response_body_as_json_example():
    return {'statusCode': 400, 'body': {'param': 'hello!'}}

response_body_as_json_example()  # returns { 'statusCode': 400, 'body': "{ 'param': 'hello!' }" }

Documentation

You can get the docstring help by running:

>>> from aws_lambda_decorators.decorators import extract
>>> help(extract)

Links

• PyPi
• Test PyPi
• Github