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