againit is important to emphasize that python does not attach any significance to annotations the intended use is in third-party libraries and frameworks that may want to use them for various applications involving metaprogramming examples includebut are not limited tostatic analysis toolsdocumentationtestingfunction overloadingmarshallingremote procedure callidescontractsetc here is an example of decorator function that enforces assertions on function arguments and return valuesdef ensure(func)extract annotation data return_check func _annotations_ get('return',nonearg_checks [(name,func _annotations_ get(name)for name in func _code_ co_varnamescreate wrapper that checks argument values and the return result using the functions specified in annotations def assert_call(*args,**kwargs)for (name,check),value in zip(arg_checks,args)if checkassert check(value)"% % (namecheck _doc_ _for name,check in arg_checks[len(args):]if checkassert check(kwargs[name])"% % (namecheck _doc_ _result func(*args,**kwargsassert return_check(result)"return %sreturn_check _doc_ return result return assert_call here is an example of code that uses the previous decoratordef positive( )"must be positivereturn def negative( )"must be negativereturn @ensure def foo( :positiveb:negative-positivereturn following is some sample output of using the functionfoo( ,- foo(- , traceback (most recent call last)file ""line in file "meta py"line in call def assert_call(*args,**kwargs)assertionerrora must be positive keyword-only arguments functions can specify keyword-only arguments this is indicated by defining extra parameters after the first starred parameter for exampledef foo( *argsstrict=false)statements lib fl ff