假设我有一些课程：
class Worker:
_processor: Processor
def set_processor(self, processor: Processor):
self._processor = processor
def start_work(self, data: bytes):
self._processor.parse(data)
测试set_processor方法非常简单，就像这样：
def test_set_processor():
mock_processor = Mock()
worker = Worker()
worker.set_processor(mock_processor)
assert worker._processor == mock_processor
我们只是将模拟传递给set_processor方法并检查self._processor现在是否等于模拟。
但是我如何测试start_work方法？我想确定self._processor会用data? 如果我尝试修补_processor属性，则会出现错误。
这是单元测试解决方案：
worker.py：
from typing import Any
Processor = Any
class Worker:
_processor: Processor
def set_processor(self, processor: Processor):
self._processor = processor
def start_work(self, data: bytes):
self._processor.parse(data)
test_worker.py：
import unittest
from worker import Worker
from unittest.mock import Mock
class TestWorker(unittest.TestCase):
def test_set_processor(self):
mock_processor = Mock()
worker = Worker()
worker.set_processor(mock_processor)
assert worker._processor == mock_processor
worker.start_work(b'')
mock_processor.parse.assert_called_once_with(b'')
if __name__ == '__main__':
unittest.main()
100% 覆盖率的单元测试结果：
.
----------------------------------------------------------------------
Ran 1 test in 0.001s
OK
(venv) ☁ python-codelab [master] ⚡ coverage report -m
Name Stmts Miss Cover Missing
-------------------------------------------------------------------------
src/stackoverflow/59202648/test_worker.py 13 0 100%
src/stackoverflow/59202648/worker.py 8 0 100%
-------------------------------------------------------------------------
TOTAL 21 0 100%
源代码：https : //github.com/mrdulin/python-codelab/tree/master/src/stackoverflow/59202648
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我来说两句