PyContracts is a Python package that allows to declare constraints on function parameters and return values. Contracts can be specified using Python3 annotations, in a decorator, or inside a docstring :type: and :rtype: tags. PyContracts supports a basic type system, variables binding, arithmetic constraints, and has several specialized contracts (notably for Numpy arrays), as well as an extension API.
PyContracts is a Python package that allows to declare constraints on function parameters and return values. It supports a basic type system, variables binding, arithmetic constraints, and has several specialized contracts (notably for Numpy arrays).
A brief summary follows. See the full documentation at: <http://andreacensi.github.com/contracts/>
Why: The purpose of PyContracts is not to turn Python into a statically-typed language (albeit you can be as strict as you wish), but, rather, to avoid the time-consuming and obfuscating checking of various preconditions. In fact, more than the type constraints, I found useful the ability to impose value and size constraints. For example, “I need a list of at least 3 positive numbers” can be expressed as list[>=3](number, >0)). If you find that PyContracts is overkill for you, you might want to try a simpler alternative, such as typecheck. If you find that PyContracts is not enough for you, you probably want to be using Haskell instead of Python.
Contracts can be specified in three ways:
Using annotations (for Python 3) —this is perhaps the most intuitive way:
@contract def my_function(a : 'int,>0', b : 'list[N],N>0') -> 'list[N]': # Requires b to be a nonempty list, and the return # value to have the same length. ...
Using :type: and :rtype: tags in docstrings. In this way, they will be included in your Sphinx documentation:
@contract def my_function(a, b): """ Function description. :type a: int,>0 :type b: list[N],N>0 :rtype: list[N] """ ...
Using arguments to the decorators; the least intrusive way:
@contract(a='int,>0', b='list[N],N>0', returns='list[N]') def my_function(a, b): ...
Moreover, there are utility functions for manual checking of values:
as well as hooks to extend PyContracts with new contracts types:
new_contract('valid_name', lambda s: isinstance(s, str) and len(s)>0) check('dict(int: (valid_name, int))', employees)
Status: PyContracts is very well tested and documented. The syntax is stable and it won’t be changed.