|category:||Unit Testing in Python|
I do a fair amount of manual refactoring. I’ve used WebSphere Studio (Eclipse) to do some automated refactoring, so I have some experience in using IDE’s which exploit Java’s static type-checking.
However, the question of type checking in a dynamic language is interesting. I don’t use a sophisticated IDE for Python development. So, I have limited experience using an IDE to do refactoring in a dynamic language.
However, JB notes “I’m having some heartburn about hierarchical type
systems as a way of determining 1) conformability and 2) managing commitments of
semantically equivalent behavior. ... Seems a constraining way
to do it, to me, not that I have a better alternative at the moment.”
Since Python relies on Duck Typing , refactoring takes on an interesting new dimension. We aren’t constrained to simply shuffle methods up and down the class hierarchy. We are now able to – well – put a method just about anywhere.
Further, since Python doesn’t have a simple, single-inheritance model, the “hierarchical” type system doesn’t completely apply.
For these reasons, refactoring in Python is one potentially complex problem.
From what I understand of Ruby, you can override a class method without creating a subclass, essentially redefining a base class in some obscure way. This gives me the willies because it makes refactoring a problem without any sensible boundaries. Maybe I’m misunderstanding Ruby, and have this wrong.
Essential Use Cases.
The principal refactoring use case involves moving a common method up the inheritance hierarchy. As a practical matter, this does happen once in a while.
An additional text-book refactoring use case arises when we’re adding or removing whole methods in the subclass hierarchy.
The fringe use case is a variation on the theme of SubClass1.methodA looking a lot like Subclass2.methodA, but they’re not the same. There are two interesting cases.
SC1.mA() is a superset of SC2.mA(). All of SC2.mA() gets refactored up, and SC1.mA() overrides it to add features.
SC1.mA() overlaps with SC2.mA(). Some common functionality has to get extracted, moved up the hierarchy; SC1.mA() and SC2.mA() are rebuilt around this common kernel.
SC1.mA() has no usable relationship with SC2.mA(). What now? In some cases, a complete change in design may be called for. The mere presence of this situation is diagnostic of the designer having missed something.
Beyond the Fringe.
Outside the fringe of ordinary refactoring are the New Design Pattern ™ situations. Mostly, these are Strategy situations, where what looks – initially – like a variant method grows into a different approach as we learn more about the solution.
Consider a pair of ordinary Entity classes that look like different entities because of different behavior. However, they have the same attributes, and almost identical methods. The only difference is one algorithm. This can be done through inheritance, but sometimes that variant algorithm is only the tip of the iceberg, and there is more variability just below the surface.
At this point, we realize we need a Strategy hierarchy to contain the variant algorithms, not a hierarchy of ordinary Entities. How does refactoring work here, where we’re moving the functionality out of a class hierarchy into a different class hierarchy? Is this even refactoring, or is it the more general case of redesign?
It doesn’t feel like refactoring because we aren’t shuffling methods up and down the class hierarchy. In Python, the Duck Typing means we don’t actually need a proper hierarchy for the Strategy class definitions. Consequently, we’re free to make significant structural changes that I don’t think an IDE can ever help with.
Across the Spectrum.
One potential problem with this is captured in the comment that “[the compiler] can’t help but see your code as a pile of text”. By extension, then, the IDE can’t do anything more than treat source as text, losing precious semantic information.
However, when doing a fundamental restructuring (from class methods to Strategy hierarchy), the source code information available to the compiler (or the IDE) isn’t of much value until you’ve finished. Nothing helps you when you’re in the middle of this. Until the semantic information exists, no IDE can help you manage and maintain the semantic information.
There are parts of design (and redesign) that are hard. I think anyone would agree that the earliest phases of noodling around about a problem are done without benefit of an IDE or formal semantics. When the design is merely conceptual, tools can’t help.
I think refactoring includes a very broad spectrum. At one end, things are essentially mechanical; at the other end things, are completely conceptual. This isn’t really a problem that needs a solution; it doesn’t need tools. It’s part of the game of moving from a good idea to software. Some parts of the good idea don’t have formal semantics. Eventually, when formal semantics exist, tools can be applied.
In the case of Python, I suspect that IDE support for refactoring could only be feeble at best. The mechanical end of the spectrum is so easy that tools aren’t required. At the conceptual end of the spectrum, tools don’t help in the first place.
The Middle Ground.
One might argue that simple, mechanical refactoring can be aided by the presence of static type declarations. However, my experience is that this covers only the most mundane of the refactoring use cases. In Python, we just move the method around.
In Python, there’s a double whammy: checking types can’t be done because the language traditionally lacked type declarations. Further – and more important – type checking doesn’t need to be done because the language is dynamic. It can’t be done, and even if it could, it didn’t matter anyway.
This is overly simplistic, however. There is some type checking which can be done in Python. The epydoc package does considerable analysis of source as part of writing documentation. It spots unused arguments, and can spot certain kinds of obvious mismatches in number of arguments vs. parameters.
When we look at JB’s point on committing to specific semantics, we see something even more profound. It goes way beyond what even Java is capable of checking or automating.
The Formal Specification.
JB is asking for a level beyond syntax, beyond type matching and off into “intent”. JB appears to be looking for formal assertions of preconditions and postconditions that he can use to determine how to redesign methods to make them refactorable, and then how to refactor the changed design.
JB’s formality would be a nice thing to capture. If every statement had a proper precondition and postcondition, then we could prove almost anything about our software except whether or not the loops actually terminated. (That can’t be formally proven in a system with the same expressive power as software, it requires more sophisticated logical tools.)
Since Java and Python have added additional markers (annotations and decorators) JB’s assertions could be captured, to an extent. You’d have to implement a simple “for all” and “there exists” predicate, but Python has a nice reduce that can be paired with a lambda that allows you to write a “for all”; from this you can built a “there exists”.
I’m not sure how helpful formal assertions would be.
When working in the center of the refactoring use cases, IDE aids are helpful. When working at the fringe, they’re just visual noise. Indeed, when redesigning something, I have to be sure not to look at any of the “helpful” messages from Eclipse because it’s checking for errors using obsolete type information. When I’ve broken the whole thing down into a workbench full of parts, the semantic checks aren’t even meaningful. Once I get it put back together again, automated checking can be handy to assure a complete job.
In Python, breaking the whole thing down as part of a redesign is so much simpler. We don’t have the artifice of “interface” to keep to a single inheritance model with static type checking across multiple aspects of a class. We just move the methods around. We have multiple inheritance, and we don’t need formal interface declarations.
Indeed, it’s far, far easier to produce a working design in Python, and use that as a formal specification for a Java program. I can tweak and tinker, optimizing performance and simplifying without the rigid formality of Java. Adding proper class hierarchies and turning multiple inheritance into single+interface inheritance is typically a pretty easy transformation. Since I knew I was aiming at Java in the first place, I avoided Pythonisms that don’t translate.
While it’s true that we don’t need Java’s formality in Python, much of that formality is helpful. I find it easier to work with a proper inheritance hierarchy, one that has explicit Not Implemented exceptions to mark the place-holders. I like to have a tidy interface definition so that I can document the interface. This additional material makes refactoring slightly more complex, but could help an automated tool do some useful method matching among classes.
The Final Test.
Without appropriate unit tests, refactoring is impossible. Even in Java, with a swanky IDE that checks everything, you still have potential problems which are uncheckable. In particular, a mis-named subclass method cannot be detected except by “near-miss” fuzzy-matching rules that will almost always work and will have false-positives. Only unit testing can locate this situation.
Unit testing absolutely is a stand-in for things the compiler can’t check. You can portray the heavy use of unit testing as a negative (“the compiler can’t be trusted”) or as a pragmatic approach to verifying the things you can’t formally state. All of the assertions in the world won’t find a spelling mistake.
Worse, your formal declarations (post-condition assertions or type definitions) could just as easily be wrong. A tidy formal proof with a wrong piece of logic will derive an incorrect program. A misspelled class name may compile, but still fail a suite of tests.
Since the IDE can’t register intent very well, it isn’t a complete solution. In the case of redesign, it isn’t even very helpful.