props 0.0.2

for_all

for_all takes a list of generators (see below) and a property. It then tests the property for arbitrary values of the generators.

Here’s an example testing the commutative and associative properties of ints:

for_all(int, int)(lambda a, b: a + b == b + a)
for_all(int, int)(lambda a, b: a * b == b * a)
for_all(int, int, int)(lambda a, b, c: c * (a + b) == a * c + b * c)

Generators

Note: These are not the same as Python generators. We should rename them. Generaters? Blech.

A generator is a specification of a set of possible Python objects. A generator is either:

• One of the following built-in types:

  • None, bool, int, float, long, complex, str, tuple, set, list, or dict

• A class that implements the ArbitraryInterface

• Or constructed using the generator combinators.

arbitrary

arbitrary takes a generator and returns a single instance of the generator.

ArbitraryInterface

We provide a mixin with one classmethod, arbitrary, which raises NotImplementedError. To implement generators for your own classes, please inherit from ArbitraryInterface and provide an implementation for arbitrary.

Here’s an example implementation of a Binary Tree class:

class BinaryTree(ArbitraryInterface):
    ...
    @classmethod
    def arbitrary(cls):
        return arbitrary(one_of(Leaf, Node))

class Leaf(BinaryTree):
    ...
    @classmethod
    def arbitrary(cls):
        return cls(...)  # an instance of Leaf.

class Node(BinaryTree):
    ...
    @classmethod
    def arbitrary(cls):
        return cls(
            ...
            # This is equivalent:
            arbitrary(BinaryTree),
            # to this:
            BinaryTree.arbitrary()
        )  # an instance of Node with two subtrees.

class TestBinaryTree(AbstractTestArbitraryInterface,
                     TestCase):
    def setUp(self):
        self.obj = BinaryTree