def instance_of(s):
"""Constructs a new data structure instance conforming
to given schema. This function proceeds recursively.
"""
if isinstance(s, Mapping):
res = (OrderedDict()
if isinstance(s, OrderedDict)
else dict())
items = s.iteritems()
else:
res = [None] * len(s)
items = enumerate(s)
for key, value in items:
if is_arbitrary(value):
value = to_arbitrary(value)
res[key] = next(value)
elif isinstance(value, Iterable):
res[key] = instance_of(value)
else:
res[key] = value
if isinstance(s, tuple):
res = tuple(res)
return res
def __init__(self, func, data, tests_count=None):
"""Constructor. Callers should specify the function
which encodes the testing property, and arbitrary values'
generator for test data (function arguments).
"""
self.func = self.__coerce_to_generator_func(func)
self.data = dict((k, to_arbitrary(v) if is_arbitrary(v) else v)
for k, v in data.iteritems())
if tests_count is not None:
self.tests_count = tests_count
def __init__(self, func, data, tests_count=None):
"""Constructor. Callers should specify the function
which encodes the testing property, and arbitrary values'
generator for test data (function arguments).
"""
self.func = self.__coerce_to_generator_func(func)
self.data = dict((k, to_arbitrary(v) if is_arbitrary(v) else v)
for k, v in data.iteritems())
if tests_count is not None:
self.tests_count = tests_count
def set_(of, min_length=0, max_length=1024):
"""Generator for arbitrary sets.
Parameters for this generator allow for adjusting the size
of resulting set and elements they contain.
:param of: Generator for set elements
:param min_length: A minimum size of set to generate
:param max_length: A maximum size of set to generate
"""
size = random.randint(min_length, max_length)
if is_arbitrary(of):
return set(next(of) for _ in xrange(size))
return set(random.choice(of) for _ in xrange(size))
def wrapped(*args, **kwargs):
if not args:
return func(**kwargs)
new_args = []
for arg in args:
arg_collection = (isinstance(arg, Iterable)
and not is_arbitrary(arg))
if arg_collection:
arg = map(_2arbitrary, arg)
new_args.extend(arg)
else:
arg = _2arbitrary(arg)
new_args.append(arg)
return func(*new_args, **kwargs)
def unicode_(of=int_(min=0, max=65535), min_length=1, max_length=64):
"""Generator for arbitrary Unicode strings.
Parameters for this generator allow for adjusting the length
of resulting strings and the set of characters they are composed of.
:param of: Characters used to construct the strings.
This can be either an iterable of characters
(e.g. a string) or a generator that produces them.
:param min_length: A minimum length of string to generate
:param max_length: A maximum length of string to generate
"""
length = random.randint(min_length, max_length)
char = lambda ch: ch if isinstance(ch, basestring) else unichr(ch)
if is_arbitrary(of):
return u''.join(char(next(of)) for _ in xrange(length))
return u''.join(char(random.choice(of)) for _ in xrange(length))
def unicode_(of=int_(min=0, max=65535), min_length=1, max_length=64):
"""Generator for arbitrary Unicode strings.
Parameters for this generator allow for adjusting the length
of resulting strings and the set of characters they are composed of.
:param of: Characters used to construct the strings.
This can be either an iterable of characters
(e.g. a string) or a generator that produces them.
:param min_length: A minimum length of string to generate
:param max_length: A maximum length of string to generate
"""
length = random.randint(min_length, max_length)
char = lambda ch: ch if isinstance(ch, basestring) else unichr(ch)
if is_arbitrary(of):
return u''.join(char(next(of)) for _ in xrange(length))
return u''.join(char(random.choice(of)) for _ in xrange(length))
def elements(*args, **kwargs):
"""Generator that returns random elements from given set.
Elements can be passed either directly as arguments::
elements(1, 2, 3)
or as a list::
elements([1, 2, 3])
Every element has equal probability of being chosen.
:param count: Optional number of elements in every returned subset.
If omitted, a single element will be yield every time.
If provided, it should always be passed as keyword argument,
e.g. ``elements(range(10), count=3)``.
This can be also a generator - such as :func:`int_` -
if there's a need to randomize the subset size, too.
.. note::
There is difference between ``elements(foo)``
and ``elements(foo, count=1)``. The first form returns
random element from the set ``foo``, while the second returns random
*1-element subset* of ``foo`` - ``x`` vs ``[x]``, essentially.
"""
if not args:
raise ValueError("cannot pick random elements from empty sequence")
count = kwargs.get('count', None)
if count is None:
return random.choice(args)
if is_arbitrary(count):
count = next(to_arbitrary(count))
count = min(count, len(args))
return random.sample(args, count)
def combinator(func):
"""Decorator for arbitrary combinator functions which take
a collection of arguments as either an actual list/sequence,
or as positional arguments.
In other words, it makes it possible to use
the following two forms of invocation::
func([1, 2, 3])
func(1, 2, 3)
In both cases ``func`` receives 1, 2 and 3 as
positional arguments (``*args``).
"""
_2arbitrary = recursive(
lambda obj: to_arbitrary(obj) if is_arbitrary(obj) else obj)
@arbitrary
@functools.wraps(func)
def wrapped(*args, **kwargs):
if not args:
return func(**kwargs)
new_args = []
for arg in args:
arg_collection = (isinstance(arg, Iterable)
and not is_arbitrary(arg))
if arg_collection:
arg = map(_2arbitrary, arg)
new_args.extend(arg)
else:
arg = _2arbitrary(arg)
new_args.append(arg)
return func(*new_args, **kwargs)
return wrapped
def list_(of, min_length=0, max_length=1024):
"""Generator for arbitrary lists.
Parameters for this generator allow for adjusting the length
of resulting list and elements they contain.
:param of: Generator for list elements
:param min_length: A minimum length of list to generate
:param max_length: A maximum length of list to generate
Example of test property that uses :func:`list_`::
@qc
def calculating_average(
l=list_(of=int_(min=0, max=1024),
min_length=16, max_length=2048)
):
average = sum(l) / len(l)
assert min(l) <= average <= max(l)
"""
length = random.randint(min_length, max_length)
if is_arbitrary(of):
return [next(of) for _ in xrange(length)]
return [random.choice(of) for _ in xrange(length)]
def __generate_data(self):
"""Returns a dictionary of test data
to be passed as keyword arguments to property function.
"""
return dict((k, next(v) if is_arbitrary(v) else v)
for k, v in self.data.iteritems())
def __generate_data(self):
"""Returns a dictionary of test data
to be passed as keyword arguments to property function.
"""
return dict((k, next(v) if is_arbitrary(v) else v)
for k, v in self.data.iteritems())