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concurrent.futures.ProcessPoolExecutor is not a test runner but rather a Python module for concurrent execution.
Performance Improvement: You can use it in your test suite to parallelize specific tasks or functions, which can lead to faster test execution when appropriate.
| # tests/test_parallel_execution.py | |
| # In this code, we have a unittest test case class TestParallelExecution with a single test method test_parallel_execution. Within the test method, we parallelize specific tasks represented by the task_1, task_2, and task_3 functions using concurrent.futures.ProcessPoolExecutor. | |
| import concurrent.futures | |
| import unittest | |
| def task_1(): | |
| """Simulate task 1.""" | |
| return "Task 1 completed successfully." | |
| def task_2(): | |
| """Simulate task 2.""" | |
| return "Task 2 completed successfully." | |
| def task_3(): | |
| """Simulate task 3.""" | |
| return "Task 3 completed successfully." | |
| class TestParallelExecution(unittest.TestCase): | |
| def test_parallel_execution(self): | |
| """Parallelize specific tasks using ProcessPoolExecutor.""" | |
| # List of tasks to parallelize | |
| tasks = [task_1, task_2, task_3] | |
| # Create a ProcessPoolExecutor with 2 worker processes | |
| with concurrent.futures.ProcessPoolExecutor(max_workers=2) as executor: | |
| # Submit the tasks for parallel execution | |
| results = list(executor.map(lambda task: task(), tasks)) | |
| # Check that all tasks completed successfully | |
| self.assertEqual(len(results), len(tasks)) | |
| for result in results: | |
| self.assertTrue(result.endswith("completed successfully.")) | |
| # python -m unittest discover -s tests -p 'test_parallel_execution.py' | |
| # The test suite will execute, and the test_parallel_execution test method will parallelize the specified tasks using ProcessPoolExecutor. |
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