Package: typecheck-decorator
A decorator for functions,@tc.typecheck, to be used together with
Python3 annotations on function parameters and function results.
The decorator will perform dynamic argument type checking for every call to the function.@tc.typecheck
def foo1(a:int, b=None, c:str="mydefault") -> bool :
    print(a, b, c)
    return b is not None and a != bThe parts:int,:str, and->boolare annotations.
This is a syntactic feature introduced in Python 3 where:(for parameters)
and->(for results) are delimiters and the rest can be
an arbitrary expression.
It is important to understand that, as such,annotations do not have any semantics whatsoever.
There must be explicit Python code somewhere
that looks at them and does something in order to give them a meaning.The@tc.typecheckdecorator gives the above annotations the following meaning:foo1’s argumentamust have typeint,bhas no annotation and can have any type whatsoever, it will not be checked,cmust have type string,
and the function’s result must be eitherTrue(not17or"yes"or[3,7,44]or some such) orFalse(not0orNoneor[]or some such).If any argument has the wrong type, aTypeCheckErrorexception will be raised
at run time.
Class types, collection types, fixed-length collections and
type predicates can be annotated as well.As of Python 3.5, PEP 484 specifies that annotations should be types and
their normal use will be type checking.
Many advanced types (such asSequence[int]) can now be defined via thetypingmodule, which is also available at PyPI for earlier versions of
Python 3.The present module supports thesetypingannotations, but it predates
Python 3.5 and therefore has other forms of type specification (via type
predicates) as well.
Many of these are equivalent, but some are more powerful.Here is a more complex example:import typecheck as tc

@tc.typecheck
def foo2(record:(int,int,bool), rgb:tc.re("^[rgb]$")) -> tc.any(int,float) :
    # don't expect the following to make much sense:
    a = record[0]; b = record[1]
    return a/b if (a/b == float(a)/b) else float(a)/b

foo2((4,10,True), "r")   # OK
foo2([4,10,True], "g")   # OK: list is acceptable in place of tuple
foo2((4,10,1), "rg")     # Wrong: 1 is not a bool, string is too long
foo2(None,     "R")      # Wrong: None is no tuple, string has illegal characterThese annotations mean thatrecordis a 3-tuple of two ints and
an actual bool andrgbis a one-character string that is
either “r” or “g” or “b” by virtue of a regular expression test.
The result will be a number that can be either int or float.The first and third of these are expressible withtypingannotations as
well, the second is not. The closest approximation would look like this:import typing as tg
import typecheck as tc

@tc.typecheck
def foo2(record:tg.Tuple[int,int,bool], rgb:str) -> tg.Union[int,float] :
    """rgb must be one of "r","g","b"."""
    a = record[0]; b = record[1]
    return a/b if (a/b == float(a)/b) else float(a)/b

foo2((4,10,True), "r")   # OK
foo2([4,10,True], "g")   # OK: list is acceptable in place of tuple
foo2((4,10,1), "rg")     # Wrong: 1 is not a bool (but meant-to-be-too-long string is not detected)
foo2(None,     "R")      # Wrong: None is no tuple (but meant-to-be-illegal character is not detected)Other kinds of annotations:tc.optional(int)ortg.Optional[int]will allow int and None,tc.enum(1, 2.0, "three")allows to define ad-hoc enumeration types,tc.map_of(str, tc.list_of(Person))ortg.Mapping[str, tg.MutableSequence[Person]]describe dictionaries or other mappings where all
keys are strings and all values are homogeneous lists of Persons,and so on.Tox-tested on CPython 3.3, 3.4, 3.5.Find the documentation athttps://github.com/prechelt/typecheck-decorator