How to mock a Python class for unit testing?
Jul 11, 2025 am 02:01 AMWhen writing unit tests for Python classes, mock technology can bypass external dependencies and is mainly implemented using the unittest.mock module or manual pile driving. 1. Use unittest.mock.patch to replace specific method behavior, such as the return value of the mock class method and verify the call; 2. Create a Mock class to replace the real class and simulate the overall behavior; 3. Use MagicMock to quickly generate fake data and use it in combination with patch. The core is to isolate the external environment through "stand-alone" and "preset results", so that the test focuses on the logic itself.
When you need to write unit tests for a Python class, you often encounter situations where you rely on external systems (such as databases, network requests). At this time, using mock technology can help you bypass these actual calls and make the test focus more on the logic itself. There are two main ways to implement it: use the unittest.mock
module or manually drive piles.

1. Use unittest.mock.patch
to replace the class method
The most common way is to replace the behavior of a certain class or method by patch
. For example, you have a class that depends on an external API:
class MyService: def fetch_data(self): # The HTTP request will actually be initiated to return requests.get("https://api.example.com/data")
In the test you can mock its return value like this:

from unittest.mock import patch @patch('my_module.MyService.fetch_data') def test_fetch_data(mock_fetch): mock_fetch.return_value.status_code = 200 mock_fetch.return_value.json.return_value = {'key': 'value'} service = MyService() result = service.fetch_data().json() assert result['key'] == 'value'
This way works for you want to control the output of a specific method without actually executing it.
Tips:
- If you want to verify that the method is called, you can use
assert_called_once_with()
. -
patch
can decorate functions and classes, or use a context manager insetUp
method. - Note that the module path must be written correctly, for example,
my_module.MyService.fetch_data
must be consistent with the import path.
2. Create a Mock class to simulate object behavior
If you don't just want to mock a method, but want to simulate the behavior of the entire class, you can directly create a mock class to replace the real class:

class MockDB: def connect(self): return True def query(self, sql): return [{"id": 1, "name": "test"}]
Then replace the original class in the test:
@patch('my_module.Database', new=MockDB) def test_db_query(): db = Database() result = db.query("SELECT * FROM table") assert len(result) == 1
This method is suitable for you to want the entire class to follow the mock process, rather than just modifying one or two methods.
3. Use MagicMock
to quickly generate fake data
If you just need to quickly generate some return values ??and don't want to define the complete mock class yourself, you can use MagicMock
:
from unittest.mock import MagicMock mock_obj = MagicMock() mock_obj.method.return_value = 42 assert mock_obj.method() == 42
You can use it in combination with patch
, such as replacing the constructor of a certain class:
@patch('my_module.MyClass', autospec=True) def test_init(MockClass): instance = MockClass.return_value instance.calculate.return_value = 100 obj = MyClass() result = obj.calculate() assert result == 100
Basically that's it. The core of mock is "stand-in" and "preset results", so that your tests can run without relying on the external environment.
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