contracts: A Python repository from ChrisBeaumont

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).

As a quick intro, please see this presentation about PyContracts.

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.

Specifying contracts: Contracts can be specified in three ways:

Using the ``@contract`` decorator:

@contract(a='int,>0', b='list[N],N>0', returns='list[N]')
def my_function(a, b):
    ...

Using annotations (for Python 3):

@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 docstrings, with the :type: and :rtype: tags:

@contract
def my_function(a, b):
    """ Function description.
        :type a: int,>0
        :type b: list[N],N>0
        :rtype: list[N]
    """
    ...

Deployment: In production, all checks can be disabled using the function contracts.disable_all(), so the performance hit is 0.

Extensions: You can extend PyContracts with new contracts types:

new_contract('valid_name', lambda s: isinstance(s, str) and len(s)>0)
@contract(names='dict(int: (valid_name, int))')
def process_accounting(records):
    ...

Any Python type is a contract:

@contract(a=int, # simple contract
          b='int,>0' # more complicated
          )
def f(a, b):
    ...

Enforcing interfaces: ContractsMeta (available for Python 2.x) is a metaclass like ABCMeta that propagates contracts to the subclasses:

from contracts import contract, ContractsMeta

class Base(object):
    __metaclass__ = ContractsMeta

    @abstractmethod
    @contract(probability='float,>=0,<=1')
    def sample(self, probability):
        pass

class Derived(Base):
    # The contract above is automatically enforced,
    # without this class having to know about PyContracts at all!
    def sample(self, probability):
        ....

Numpy: There is special support for Numpy:

@contract(image='array[HxWx3](uint8),H>10,W>10')
def recolor(image):
    ...

Status: The syntax is stable and it won't be changed. PyContracts is very well tested on Python 2.x.

Status on Python 3.x:

The basics work, but probably haven't been stress-tested enough.
ContractsMeta does not work.
Arithmetics construct do not work. This is because of PyParsing 2.x not being backwards compatible with PyParsing 1.6.

Any help is welcome! (I don't use Python 3 myself.) Start by running nosetests contracts.

ChrisBeaumont/contracts