This interesting piece from Luke Plant went by on Planet Python this morning, and really helped me in understanding many of the complaints I see about Django's Class Based Views. That problem seems to be that when CBVs were introduced, they were brought in as a replacement for the earlier procedural Function Based Views, rather than as a lower level supplemental API that covered an additional set of use cases that weren't being adequately served by the previous approach (I only started using Django with 1.3, so it's taken me a while to come up to speed on this aspect of the framework's history).
The key point in Luke's article that I agree with is that deprecating FBVs in favour of CBVs and saying the latter is always the superior solution is a mistake. The part I disagree with is that saying this also means that introducing the CBV concept itself was a mistake. CBVs may have been oversold as the "one true way" to do Django views, but "There's one - and preferably only one - obvious way to do it" is not meant to apply at the level of programming paradigms. Yes, it's a design principle that's part of the Zen of Python, and it's a good philosophy to help reduce needless API complication, but when it comes to the complexities of real world programming, you need flexibility in your modelling tools, or you end up fighting the limitations of your tools instead of being able to clearly express your intent.
Procedural programming, functional programming, object-oriented programming, pipeline-based programming etc - they're all different ways to approach a problem space, and Python is deliberately designed to support all of them.
It helps to know a bit of programming history and the origins of OOP in the context of this discussion, as Django's FBVs are very similar to implementations of OOP in C and other languages with no native OOP support: you have an object (the HTTP request) and a whole lot of functions that accept that object as their first argument.
Thus, when you don't use CBVs at all, what you're really doing is bypassing Python's native OO support in favour of a truckload of what are effectively methods on request objects (just written in a procedural style). If you want to pass state around you either store it on the request, you store it in global state (which includes your cache and main datastore) or you pass it explicitly as function arguments (which means you have to daisy chain it to anyone else that needs it). If you use classes instead, then you get an additional mechanism that you can use to affect behaviour for a subset of your views. For example, I recently restricted write access to the PulpDist REST API to site admins, when it had previously been open to all logged in users. I could do that in one place and be confident it affected the entire API because every REST view in PulpDist inherits from a common base class. Since that base class now enforces the new access restrictions, the entire API obeys the rules even though I only changed one class.
Where Luke is absolutely right, though, is that switching from a procedural approach to an object-oriented one comes with a cost, mostly in the form of non-local effects and non-obvious flow control. If you look at Python's standard library, a rather common model to alleviate this problem is the idea of providing an implementation class, which you can choose to use directly, as well as a set of module level convenience functions. Much of the time, using the convenience functions is a better choice, since they're designed to be simple and clean solutions to common tasks. However, if you need to start tweaking, then being able to either instantiate or subclass the existing backend implementation directly lets you get a lot further before you have to resort to the brute force copy-paste-edit approach to code reuse.
But please, don't confuse "Django's Generic View implementation is overly complicated and FBVs should be retained as an officially blessed and supported convenience API" with "CBVs are a bad idea". Making the latter claim is really saying "OOP is a bad idea", which is not a supportable assertion (unless you want to argue with decades of CS and software engineering experience). While the weaker claim that "An OOP implementation is often best presented to the API user behind a procedural facade" is less exciting, it has the virtue of being more universally true. Procedural APIs often are simpler and generally introduce less coupling between components. The trick with exposing an OOP layer as well is that it increases the options for your users, as they can now:
- Just use the procedural layer (Huzzah! Low coupling is good)
- Use the OOP layer through composition (OK, better than reinventing the wheel and coupling is still fairly low when using composition)
- Use the OOP layer through inheritance (Eek, coupling is increasing substantially now, but it's typically still better than copy-paste-edit style reuse)
- Use the upstream implementation as a reference or starting point when writing your own (coupling drops back to zero, but the line count of code that is directly part of the current project just went up substantially)
A good example of this layered approach to API design is the str.format method. The main API for that is of course the str.format() method itself and that covers the vast majority of use cases. If you just want to customise the display of a particular custom type, then you can provide a __format__ method directly on that class. However, if you want to write a completely custom formatter (for example, one that automatically quotes interpolated values with shlex.quote), then the string.Formatter class is exposed so that you can take advantage of most of the builtin formatting machinery instead of having to rewrite it yourself. Contrast that with the older %-based approach to formatting - if you want to implement a custom formatter based on that, you're completely on your own, the standard library provides no help whatsoever. PEP 3101 provides some of the rationale behind the layered string formatting API. It's by no means perfect, but perfection wasn't the goal - the goal was providing something more flexible and less quirky than %-style formatting, and in that it succeeded admirably. The key lesson that's applicable to Django is that string.Formatter isn't a replacement for str.format, it's a supplement for the relatively rare cases where the simple method API isn't flexible enough.
A few other examples of this layered API design that spring immediately to mind are the logging module (which provides convenience functions to pass messages directly to the root logger), subprocess (with a few convenience functions that aim to largely hide the Swiss army knife that is subprocess.Popen), textwrap (with textwrap.dedent() providing a shorthand for a particular way of using textwrap.TextWrapper), pickle, json, importlib... You get the idea :)
Update: Toned down the title and the paragraph after the bulleted list slightly. Since I've never used them myself, I don't know enough about the abuses of FBVs to second guess the Django core devs motivations for actively encouraging the switch to CBVs.