Testing in Python
Everyone will agree that testing is an important part of the development process. But it is something that many people struggle with still. When it comes down to writing out your test cases, it can seem tedious or hard to wrap your head around this different way of looking at your code. However, with a little practice, this will become as second nature as coding the actual solution.
There are four different types of tests, each depending on the granularity of code being tested, as well as the goal of the test.
This tests specific methods and logic in the code. This is the most granular type of test. The goal is to verify the internal flow of the method, as well as to make sure edge cases are being handled.
def func(): return 1 def test_func(): assert func() == 1
This tests the functionality of the component. A collection of unit tests may or may not represent a Feature test. The goal is to verify the component meets the requirements given for it. If you're thinking in terms of a work item, this would be testing a ticket as a whole.
class NewEndpoint: def on_get(req, resp): resp.body = "Hello World" def test_new_endpoint(): result = simulate_get("/newendpoint") assert result.body = "Hello World"
This tests the entire application, end to end. The goal is to guarantee the stability of the application. When new code is added, integration tests should still pass with minimal effort.
class MySystem: external_system = ExternalSystemConnector() def handle_message(message): try: external_system.send_message(message) return True catch Exception as err: return False def test_MySystem(): system = MySystem() assert system.handle_message(good_message) assert not system.handle_message(bad_message)
This tests the efficiency of a piece of code. The size of the code being tested can range from a method to the whole application.
import timeit def func(i): return i * 2 def test_performance(): assert 1 > timeit.timeit("[func(x) for x in range(20)]", number=5, setup="from __main__ import func")