PyContracts 1.6.0

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):

  @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:

  @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 @contract decorator:

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

In any case, PyContracts will include the spec in the __doc__ attribute.

Extensions: You can 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)

Any Python type is a contract:

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

Enforcing interfaces: The metaclass 'ContractsMeta' is like ABCMeta, but it propagates contracts to the subclasses:

from contracts import contract, ContractsMeta

class Base(object):
    __metaclass__ = ContractsMeta

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

class Derived(Base):
    # The contract is automatically enforced for all children!
    def sample(probability):
        ....

Numpy: There is special support for Numpy:

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

Status: PyContracts is very well tested and documented. The syntax is stable and it won't be changed.