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.

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:

1. Using the ``@contract`` decorator: :

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

2. 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.
        ...

3. 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.