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Project Description

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 != b

The parts :int, :str, and -> bool are 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.typecheck decorator gives the above annotations the following meaning: foo1’s argument a must have type int, b has no annotation and can have any type whatsoever, it will not be checked, c must have type string, and the function’s result must be either True (not 17 or "yes" or [3,7,44] or some such) or False (not 0 or None or [] or some such).

If any argument has the wrong type, a TypeCheckError exception 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 as Sequence[int]) can now be defined via the typing module, which is also available at PyPI for earlier versions of Python 3.

The present module supports these typing annotations, 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 character

These annotations mean that record is a 3-tuple of two ints and an actual bool and rgb is 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 with typing annotations 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) or tg.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)) or tg.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 at https://github.com/prechelt/typecheck-decorator

Release History

Release History

1.3

This version

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1.2

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1.0

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0.3b

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0.2a

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
typecheck-decorator-1.3.zip (32.9 kB) Copy SHA256 Checksum SHA256 Source Jan 25, 2016

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