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