In the book Working Effectively with Legacy Code, Michael Feathers defines legacy code as, simply, code without tests. He elaborates that with tests one can easily modify the behavior of the code quickly and verifiably. In the absence of tests, it is impossible to gauge if the change made the code better or worse.
Often, we do not know enough about legacy code to confidently write a test. Michael recommends writing tests that preserve and document the existing behavior, which are called characterization tests.
Unlike the usual approach of writing tests, while writing a characterization test, you will first write a failing test with a dummy output, say X, because you don't know what to expect. When the test harness fails with an error, such as "Expected output X but got Y", then you will change your test to expect Y. So, now the test will pass, and it becomes a record of the code's existing behavior.
Note that we might record buggy behavior as well. After all, this is unfamiliar code. Nevertheless, writing such tests are necessary before we start changing the code. Later, when we know the specifications and code better, we can fix these bugs and update our tests (not necessarily in that order).
Writing tests before changing the code is similar to erecting scaffoldings before the restoration of an old building. It provides a structural framework that helps you confidently undertake repairs.
You might want to approach this process in a stepwise manner as follows:
- Identify the area you need to make changes to. Write characterization tests focusing on this area until you have satisfactorily captured its behavior.
- Look at the changes you need to make and write specific test cases for those. Prefer smaller unit tests to larger and slower integration tests.
- Introduce incremental changes and test in lockstep. If tests break, then try to analyze whether it was expected. Don't be afraid to break even the characterization tests if that behavior is something that was intended to change.
If you have a good set of tests around your code, then you can quickly find the effect of changing your code.
On the other hand, if you decide to rewrite by discarding your code but not your data, then Django can help you considerably.