# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""``utils.py``
"""
import collections
import functools
import inspect
import time
import types
[docs]def def_method(f, *args, **kwargs):
@functools.wraps(f)
def new_method(self):
return f(self, *args, **kwargs)
return new_method
[docs]def parameterized_class(cls):
"""A class decorator for running parameterized test cases.
Mark your class with @parameterized_class.
Mark your test cases with @parameterized.
"""
test_functions = inspect.getmembers(cls, predicate=inspect.ismethod)
for (name, f) in test_functions:
if name.startswith('test_') and not hasattr(f, '_test_data'):
continue
# remove the original test function from the class
delattr(cls, name)
# add a new test function to the class for each entry in f._test_data
for tag, args in f._test_data.items(): # pylint: disable=protected-access
new_name = "{0}_{1}".format(f.__name__, tag)
if hasattr(cls, new_name):
raise Exception(
"Parameterized test case '{0}.{1}' created from '{0}.{2}' "
"already exists".format(cls.__name__, new_name, name))
# Using `def new_method(self): f(self, **args)` is not sufficient
# (all new_methods use the same args value due to late binding).
# Instead, use this factory function.
new_method = def_method(f, **args)
# To add a method to a class, available for all instances:
# MyClass.method = types.MethodType(f, None, MyClass)
setattr(cls, new_name, types.MethodType(new_method, None, cls))
return cls
[docs]def parameterized(data):
"""A function decorator for parameterized test cases.
Example::
@parameterized({
'zero': dict(val=0),
'one': dict(val=1),
})
def test_val(self, val):
self.assertEqual(val, self.get_val())
The above will generate two test cases::
`test_val_zero` which runs with val=0
`test_val_one` which runs with val=1
Args:
data(dict): A dictionary that looks like {tag: {arg1: val1, ...}}
"""
def wrapped(f):
f._test_data = data # pylint: disable=protected-access
return f
return wrapped
[docs]def wait_for_condition(condition, interval=1, timeout=40):
start_time = time.time()
end_time = time.time() + timeout
while time.time() < end_time:
result = condition()
if result:
return result
time.sleep(interval)
raise Exception(("Timed out after %s seconds. Started " +
"on %s and ended on %s") % (timeout, start_time, end_time))
[docs]def memoized(func):
"""A decorator to cache function's return value
"""
cache = {}
@functools.wraps(func)
def wrapper(*args):
if not isinstance(args, collections.Hashable):
# args is not cacheable. just call the function.
return func(*args)
if args in cache:
return cache[args]
else:
value = func(*args)
cache[args] = value
return value
return wrapper