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Mocking framework for Python
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Chai - Python Mocking Made Easy

Version: 0.1.2
Keywords:python, mocking, testing, unittest, unittest2


Chai provides a very easy to use api for mocking/stubbing your python objects, patterned after the Mocha library for Ruby.


The following is an example of a simple test case which is mocking out a get method on the CustomObject. The Chai api allows use of call chains to make the code short, clean, and very readable. It also does away with the standard setup-and-replay work flow, giving you more flexibility in how you write your cases.

from chai import Chai

class CustomObject (object):
    def get(self, arg):

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        self.expect(obj.get).args('name').returns('My Name')
        self.assert_equals(obj.get('name'), 'My Name')
        self.expect(obj.get).args('name').returns('Your Name')
        self.assert_equals(obj.get('name'), 'Your Name')

    def test_mock_get_with_at_most(self):
        obj = CustomObject()
        self.expect(obj.get).args('name').returns('My Name').at_most(2)
        self.assert_equals(obj.get('name'), 'My Name')
        self.assert_equals(obj.get('name'), 'My Name')
        self.assert_equals(obj.get('name'), 'My Name') # this one will fail

if __name__ == '__main__':
    import unittest2


All of the features are available by extending the Chai class, itself a subclass of unittest.TestCase. If unittest2 is available Chai will use that, else it will fall back to unittest. Chai also aliases all of the assert* methods to lower-case with undersores. For example, assertNotEquals can also be referenced as assert_not_equals.

Additionally, Chai loads in all assertions, comparators and mocking methods into the module in which a Chai subclass is declared. This is done to cut down on the verbosity of typing self. everywhere that you want to run a test. The references are loaded into the subclass' module during setUp, so you're sure any method you call will be a reference to the class and module in which a particular test method is currently being executed. Methods and comparators you define locally in a test case will be globally available when you're running that particular case as well.

class ProtocolInterface(object):
    def _private_call(self, arg):
    def get_result(self, arg):
        return 'ok'

class TestCase(Chai):
    def assert_complicated_state(self, obj):
        return True  # ..or.. raise AssertionError()

    def test_mock_get(self):
        obj = ProtocolInterface()
        data = object()
        assert_equals('ok', obj.get_result(data))


The simplest mock is to stub a method. This replaces the original method with a subclass of chai.Stub, the main instrumentation class. All additional stub and expect calls will re-use this stub, and the stub is responsible for re-installing the original reference when Chai.tearDown is run.

Stubbing is used for situations when you want to assert that a method is never called.

class CustomObject (object):
    def get(self, arg):

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        assert_raises( UnexpectedCall, obj.get )

In this example, we can reference obj.get directly because get is a bound method and provides all of the context we need to refer back to obj and stub the method accordingly. There are cases where this is insufficient, such as module imports and special Python types such as object().__init__. If the object can't be stubbed with a reference, UnsupportedStub will be raised and you can use the verbose reference instead.

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        stub(obj, 'get')
        assert_raises( UnexpectedCall, obj.get )

Stubbing an unbound method will apply that stub to all future instances of that class.

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        assert_raises( UnexpectedCall, obj.get )

Finally, some methods cannot be stubbed because it is impossible to call setattr on the object. A good example of this is the datetime.datetime class.


Expectations are individual test cases that can be applied to a stub. They are expected to be run in order (unless otherwise noted). They are greedy, in that so long as an expectation has not been met and the arguments match, the arguments will be processed by that expectation. This mostly applies to the "at_least" and "any_order" expectations, which (may) stay open throughout the test and will handle any matching call.

Expectations will automatically create a stub if it's not already applied, so no separate call to stub is necessary. The arguments and edge cases regarding what can and cannot have expectations applied are identical to stubs. The expect call will return a new chai.Expectation object which can then be used to modify the expectation. Without any modifiers, an expectation will expect a single call without arguments and return None.

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        assert_equals( None, obj.get() )
        assert_raises( UnexpectedCall, obj.get )

Modifiers can be applied to the expectation. Each modifier will return a reference to the expectation for easy chaining. In this example, we're going to match a parameter and change the behavior depending on the argument. This also shows the ability to incrementally add expectations throughout the test.

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        assert_equals( 'hello', obj.get('foo') )
        assert_equals( 'hello', obj.get('foo') )
        expect(obj.get).args('bar').raises( ValueError )
        assert_raises( ValueError, obj.get, 'bar' )

Lastly, the arguments modifier supports several matching functions. For simplicity in covering the common cases, the arg expectation assumes an equals test for instances and an instanceof test for types. All rules that apply to positional arguments also apply to keyword arguments.

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject()
        assert_raises( UnexpectedCall, obj.get, 3 )
        assert_equals( 42, obj.get(3.14) )

        assert_equals( 'yes', obj.get('no') )

        assert_raises( UnexpectedCall, obj.get, [] )
        assert_equals( 'yes', obj.get(list) )


Expectations expose the following public methods for changing their behavior.

args(*args, **kwargs)
Add a test to the expectation for matching arguments.
Add a return value to the expectation when it is matched and executed.
When the expectation is run it will raise this exception. Accepts type or instance.
An integer that defines a hard limit on the minimum and maximum number of times the expectation should be executed.
Sets a minimum number of times the expectation should run and removes any maximum.
Equivalent to at_least(1).
Sets a maximum number of times the expectation should run. Does not affect the minimum.
Equivalent to at_most(1).
Equivalent to times(1), also the default for any expectation.
The expectation can be called at any time, independent of when it was defined. Can be combined with at_least_once to force it to respond to all matching calls throughout the test.

Argument Matchers

Expectation modifiers are defined as classes in chai.comparators, but loaded into the Chai class for convenience. From a Chai subclass, they are all accessible through self.

The default comparator, uses standard Python equals operator
almost_equals(float, places)
Identical to assertAlmostEquals, will match an argument to the comparator value to a most places digits beyond the decimal point.
Match an argument of a given type. Supports same arguments as builtin function isinstance.
Alias of instance_of.
Matches an argument using the Python is comparator.
Matches an argument if any of the comparators in the argument list are met. Uses automatic comparator generation for instances and types in the list.
Matches an argument if all of the comparators in the argument list are met. Uses automatic comparator generation for instances and types in the list.
Matches an argument if the supplied comparator does not match.
Matches an argument using a regular expression. Standard re rules apply.
Matches an argument if the callable returns True. The callable must take one argument, the parameter being checked.
Matches any argument.
Matches if the argument is in the in_list.
Matches if the argument contains the object using the Python in function.


Sometimes you need a mock object which can be used to stub and expect anything. Chai exposes this through the mock method which can be called in one of two ways.

Without any arguments, Chai.mock() will return a chai.Mock object that can be used for any purpose. If called with arguments, it behaves like stub and expect, creating a Mock object and setting it as the attribute on another object.

Any request for an attribute from a Mock will return a callable function, but setattr behaves as expected so it can store state as well. The dynamic function will act like a stub, raising UnexpectedCall if no expectation is defined.

class CustomObject(object):
    def __init__(self, handle):
        _handle = handle
    def do(self, arg):

class TestCase(Chai):
    def test_mock_get(self):
        obj = CustomObject( mock() )
        expect( ).args('it').returns('ok')
        assert_raises( UnexpectedCall, obj._handle.do_it_again )

The stub and expect methods handle Mock objects as arguments by mocking the __call__ method, which can also act in place of __init__.

# module
from collections import deque

class CustomObject(object):
    def __init__(self):
        self._stack = deque()

# module
import custom
from custom import CustomObject

class TestCase(Chai):
    def test_mock_get(self):
        mock( custom, 'deque' )
        expect( custom.deque ).returns( 'stack' )

        obj = CustomObject()
        assert_equals('stack', obj._stack)


You can install Chai either via the Python Package Index (PyPI) or from source.

To install using pip,:

$ pip install chai

Downloading and installing from source

Download the latest version of Chai from

You can install it by doing the following,:

$ tar xvfz chai-*.*.*.tar.gz
$ cd celery-*.*.*
$ python build
# python install # as root

Using the development version

You can clone the repository by doing the following:

$ git clone git://

Bug tracker

If you have any suggestions, bug reports or annoyances please report them to our issue tracker at


This software is licensed under the New BSD License. See the LICENSE file in the top distribution directory for the full license text.

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