From time to time, challenges to various aspects of repoze.bfg design are lodged. To give context to discussions that follow, we detail some of the design decisions and trade-offs here. In some cases, we acknowledge that the framework can be made better and we describe future steps which will be taken to improve it; in some cases we just file the challenge as “noted”, as obviously you can’t please everyone all of the time.
repoze.bfg uses a Zope Component Architecture (ZCA) “component registry” as its application registry under the hood. This is a point of some contention. repoze.bfg is of a Zope pedigree, so it was natural for its developers to use a ZCA registry at its inception. However, we understand that using a ZCA registry has issues and consequences, which we’ve attempted to address as best we can. Here’s an introspection about repoze.bfg use of a ZCA registry, and the trade-offs its usage involves.
The “global” API that may be used to access data in a ZCA “component registry” is not particularly pretty or intuitive, and sometimes it’s just plain obtuse. Likewise, the conceptual load on a casual source code reader of code that uses the ZCA global API is somewhat high. Consider a ZCA neophyte reading the code that performs a typical “unnamed utility” lookup using the zope.component.getUtility() global API:
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from repoze.bfg.interfaces import ISettings from zope.component import getUtility settings = getUtility(ISettings)
After this code runs, settings will be a Python dictionary. But it’s unlikely that any “civilian” would know that just by reading the code. There are a number of comprehension issues with the bit of code above that are obvious.
First, what’s a “utility”? Well, for the purposes of this discussion, and for the purpose of the code above, it’s just not very important. If you really want to know, you can read this. However, still, readers of such code need to understand the concept in order to parse it. This is problem number one.
Second, what’s this ISettings thing? It’s an interface. Is that important here? Not really, we’re just using it as a “key” for some lookup based on its identity as a marker: it represents an object that has the dictionary API, but that’s not very important in this context. That’s problem number two.
Third of all, what does the getUtility function do? It’s performing a lookup for the ISettings “utility” that should return.. well, a utility. Note how we’ve already built up a dependency on the understanding of an interface and the concept of “utility” to answer this question: a bad sign so far. Note also that the answer is circular, a really bad sign.
Fourth, where does getUtility look to get the data? Well, the “component registry” of course. What’s a component registry? Problem number four.
Fifth, assuming you buy that there’s some magical registry hanging around, where is this registry? Homina homina... “around”? That’s sort of the best answer in this context (a more specific answer would require knowledge of internals). Can there be more than one registry? Yes. So which registry does it find the registration in? Well, the “current” registry of course. In terms of repoze.bfg, the current registry is a thread local variable. Using an API that consults a thread local makes understanding how it works non-local.
You’ve now bought in to the fact that there’s a registry that is just “hanging around”. But how does the registry get populated? Why, ZCML of course. Sometimes. Or via imperative code. In this particular case, however, the registration of ISettings is made by the framework itself “under the hood”: it’s not present in any ZCML nor was it performed imperatively. This is extremely hard to comprehend. Problem number six.
Clearly there’s some amount of cognitive load here that needs to be borne by a reader of code that extends the repoze.bfg framework due to its use of the ZCA, even if he or she is already an expert Python programmer and whom is an expert in the domain of web applications. This is suboptimal.
First, the primary amelioration: repoze.bfg does not expect application developers to understand ZCA concepts or any of its APIs. If an application developer needs to understand a ZCA concept or API during the creation of a repoze.bfg application, we’ve failed on some axis.
Instead, the framework hides the presence of the ZCA registry behind special-purpose API functions that do use ZCA APIs. Take for example the repoze.bfg.security.authenticated_userid function, which returns the userid present in the current request or None if no userid is present in the current request. The application developer calls it like so:
from repoze.bfg.security import authenticated_userid userid = authenticated_userid(request)
He now has the current user id.
Under its hood however, the implementation of authenticated_userid is this:
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def authenticated_userid(request): """ Return the userid of the currently authenticated user or ``None`` if there is no authentication policy in effect or there is no currently authenticated user. """ registry = request.registry # the ZCA component registry policy = registry.queryUtility(IAuthenticationPolicy) if policy is None: return None return policy.authenticated_userid(request)
Using such wrappers, we strive to always hide the ZCA API from application developers. Application developers should just never know about the ZCA API: they should call a Python function with some object germane to the domain as an argument, and it should returns a result. A corollary that follows is that any reader of an application that has been written using repoze.bfg needn’t understand the ZCA API either.
Hiding the ZCA API from application developers and code readers is a form of enhancing “domain specificity”. No application developer wants to need to understand the minutiae of the mechanics of how a web framework does its thing. People want to deal in concepts that are closer to the domain they’re working in: for example, web developers want to know about users, not utilities. repoze.bfg uses the ZCA as an implementation detail, not as a feature which is exposed to end users.
However, unlike application developers, framework developers, including people who want to override repoze.bfg functionality via preordained framework plugpoints like traversal or view lookup must understand the ZCA registry API.
repoze.bfg framework developers were so concerned about conceptual load issues of the ZCA registry API for framework developers that a replacement registry implementation named repoze.component was actually developed. Though this package has a registry implementation which is fully functional and well-tested, and its API is much nicer than the ZCA registry API, work on it was largely abandoned and it is not used in repoze.bfg. We continued to use a ZCA registry within repoze.bfg because it ultimately proved a better fit.
We continued using ZCA registry rather than disusing it in favor of using the registry implementation in repoze.component largely because the ZCA concept of interfaces provides for use of an interface hierarchy, which is useful in a lot of scenarios (such as context type inheritance). Coming up with a marker type that was something like an interface that allowed for this functionality seemed like it was just reinventing the wheel.
Making framework developers and extenders understand the ZCA registry API is a trade-off. We (the repoze.bfg developers) like the features that the ZCA registry gives us, and we have long-ago borne the weight of understanding what it does and how it works. The authors of repoze.bfg understand the ZCA deeply and can read code that uses it as easily as any other code.
But we recognize that developers who my want to extend the framework are not as comfortable with the ZCA registry API as the original developers are with it. So, for the purposes of being kind to third-party repoze.bfg framework developers in, we’ve drawn some lines in the sand.
In all “core” code, We’ve made use of ZCA global API functions such as zope.component.getUtility and zope.component.getAdapter the exception instead of the rule. So instead of:
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from repoze.bfg.interfaces import IAuthenticationPolicy from zope.component import getUtility policy = getUtility(IAuthenticationPolicy)
repoze.bfg code will usually do:
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from repoze.bfg.interfaces import IAuthenticationPolicy from repoze.bfg.threadlocal import get_current_registry registry = get_current_registry() policy = registry.getUtility(IAuthenticationPolicy)
While the latter is more verbose, it also arguably makes it more obvious what’s going on. All of the repoze.bfg core code uses this pattern rather than the ZCA global API.
We’ve turned the component registry used by repoze.bfg into something that is accessible using the plain old dictionary API (like the repoze.component API). For example, the snippet of code in the problem section above was:
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from repoze.bfg.interfaces import ISettings from zope.component import getUtility settings = getUtility(ISettings)
In a better world, we might be able to spell this as:
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from repoze.bfg.threadlocal import get_current_registry registry = get_current_registry() settings = registry['settings']
In this world, we’ve removed the need to understand utilities and interfaces, because we’ve disused them in favor of a plain dictionary lookup. We haven’t removed the need to understand the concept of a registry, but for the purposes of this example, it’s simply a dictionary. We haven’t killed off the concept of a thread local either. Let’s kill off thread locals, pretending to want to do this in some code that has access to the request:
registry = request.registry settings = registry['settings']
In this world, we’ve reduced the conceptual problem to understanding attributes and the dictionary API. Every Python programmer knows these things, even framework programmers.
While repoze.bfg still uses some suboptimal unnamed utility registrations, future versions of it will where possible disuse these things in favor of straight dictionary assignments and lookups, as demonstrated above, to be kinder to new framework developers. We’ll continue to seek ways to reduce framework developer cognitive load.
Here are the main rationales involved in the repoze.bfg decision to use the ZCA registry:
If you only develop applications using repoze.bfg, there’s not much to complain about here. You just should never need to understand the ZCA registry or even know about its presence: use documented repoze.bfg APIs instead. However, you may be an application developer who doesn’t read API documentation because it’s unmanly. Instead you read the raw source code, and because you haven’t read the documentation, you don’t know what functions, classes, and methods even form the repoze.bfg API. As a result, you’ve now written code that uses internals and you’ve pained yourself into a conceptual corner as a result of needing to wrestle with some ZCA-using implementation detail. If this is you, it’s extremely hard to have a lot of sympathy for you. You’ll either need to get familiar with how we’re using the ZCA registry or you’ll need to use only the documented APIs; that’s why we document them as APIs.
If you extend or develop repoze.bfg (create new ZCML directives, use some of the more obscure “ZCML hooks” as described in Using Hooks, or work on the repoze.bfg core code), you will be faced with needing to understand at least some ZCA concepts. The ZCA registry API is quirky: we’ve tried to make it at least slightly nicer by disusing it for common registrations and lookups such as unnamed utilities. Some places it’s used unabashedly, and will be forever. We know it’s quirky, but it’s also useful and fundamentally understandable if you take the time to do some reading about it.
In this TOPP Engineering blog entry, Ian Bicking asserts that the way repoze.bfg uses a Zope interface to represent an HTTP request method adds too much indirection for not enough gain. We agreed in general, and for this reason, repoze.bfg version 1.1 added view predicate and route predicate modifiers to view configuration. Predicates are request-specific (or context -specific) matching narrowers which don’t use interfaces. Instead, each predicate uses a domain-specific string as a match value.
For example, to write a view configuration which matches only requests with the POST HTTP request method, you might write a @bfg_view decorator which mentioned the request_method predicate:
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from repoze.bfg.view import bfg_view @bfg_view(name='post_view', request_method='POST', renderer='json') def post_view(request): return 'POSTed'
You might further narrow the matching scenario by adding an accept predicate that narrows matching to something that accepts a JSON response:
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from repoze.bfg.view import bfg_view @bfg_view(name='post_view', request_method='POST', accept='application/json', renderer='json') def post_view(request): return 'POSTed'
Such a view would only match when the request indicated that HTTP request method was POST and that the remote user agent passed application/json (or, for that matter, application/*) in its Accept request header.
“Under the hood”, these features make no use of interfaces.
Many “prebaked” predicates exist. However, use of only “prebaked” predicates, however, doesn’t entirely meet Ian’s criterion. He would like to be able to match a request using a lambda or another function which interrogates the request imperatively. In version 1.2, we acommodate this by allowing people to define “custom” view predicates:
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from repoze.bfg.view import bfg_view from webob import Response def subpath(context, request): return request.subpath and request.subpath == 'abc' @bfg_view(custom_predicates=(subpath,)) def aview(request): return Response('OK')
The above view will only match when the first element of the request’s subpath is abc.
Quick answer: well, it doesn’t really encourage the use of ZCML. In repoze.bfg 1.0 and 1.1, application developers could use decorators for the most common form of configuration. But, yes, a repoze.bfg 1.0/1.1 application needed to possess a ZCML file for it to begin executing successfully even if its only contents were a <scan> directive that kicked off a scan to find decorated view callables.
In the interest of completeness and in the spirit of providing a lowest common denominator, repoze.bfg 1.2 includes a completely imperative mode for all configuration. You will be able to make “single file” apps in this mode, which should help people who need to see everything done completely imperatively. For example, the very most basic repoze.bfg “helloworld” program has become something like:
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from webob import Response from paste.httpserver import serve from repoze.bfg.configuration import Configurator def hello_world(request): return Response('Hello world!') if __name__ == '__main__': config = Configurator() config.begin() config.add_view(hello_world) config.end() app = config.make_wsgi_app() serve(app)
In this mode, no ZCML is required for end users. Hopefully this mode will allow people who are used to doing everything imperatively feel more comfortable.
ZCML is a configuration language in the XML syntax. Due to the “imperative configuration” feature (new in repoze.bfg 1.2), you don’t need to use ZCML at all if you start a project from scratch. But if you really do want to perform declarative configuration, perhaps because you want to build an extensible application, you will need to use and understand it.
ZCML contains elements that are mostly singleton tags that are called declarations. For an example:
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<route view=".views.my_view" path="/" name="root" />
This declaration associates a view with a route pattern.
All repoze.bfg declarations are singleton tags, unlike many other XML configuration systems. No XML values in ZCML are meaningful; it’s always just XML tags and attributes. So in the very common case it’s not really very much different than an otherwise “flat” configuration format like .ini, except a developer can create a directive that requires nesting (none of these exist in repoze.bfg itself), and multiple “sections” can exist with the same “name” (e.g. two <route> declarations) must be able to exist simultaneously.
You might think some other configuration file format would be better. But all configuration formats suck in one way or another. I personally don’t think any of our lives would be markedly better if the declarative configuration format used by repoze.bfg were YAML, JSON, or INI. It’s all just plumbing that you mostly cut and paste once you’ve progressed 30 minutes into your first project. Folks who tend to agitate for another configuration file format are folks that haven’t yet spent that 30 minutes.
The repoze.bfg documentation refers to the graph being traversed when traversal is used as a “model graph”. Some of the repoze.bfg APIs also use the word “model” in them when referring to a node in this graph (e.g. repoze.bfg.url.model_url).
A terminology overlap confuses people who write applications that always use ORM packages such as SQLAlchemy, which has a different notion of the definition of a “model”. When using the API of common ORM packages, its conception of “model” is almost certainly not a directed acyclic graph (as may be the case in many graph databases). Often model objects must be explicitly manufactured by an ORM as a result of some query performed by a view. As a result, it can be unnatural to think of the nodes traversed as “model” objects if you develop your application using traversal and a relational database. When you develop such applications, the things that repoze.bfg refers to as “models” in such an application may just be stand-ins that perform a query and generate some wrapper for an ORM “model” (or set of ORM models). The graph might be composed completely of “model” objects (as defined by the ORM) but it also might not be.
The naming impedance mismatch between the way the term “model” is used to refer to a node in a graph in repoze.bfg and the way the term “model” is used by packages like SQLAlchemy is unfortunate. For the purpose of avoiding confusion, if we had it to do all over again, we might refer to the graph that repoze.bfg traverses a “node graph” or “object graph” rather than a “model graph”, but since we’ve baked the name into the API, it’s a little late. Sorry.
In our defense, many repoze.bfg applications (especially ones which use ZODB) do indeed traverse a graph full of model nodes. Each node in the graph is a separate persistent object that is stored within a database. This was the use case considered when coming up with the “model” terminology.
This is understandable. The people who believe it is wrong almost invariably have all of their data in a relational database. Relational databases aren’t naturally hierarchical, so “traversing” one like a graph is not possible. This problem is related to BFG Uses “Model” To Represent A Node In The Graph of Objects Traversed.
Folks who deem traversal unilaterally “wrong” are neglecting to take into account that many persistence mechanisms are hierarchical. Examples include a filesystem, an LDAP database, a ZODB (or another type of graph) database, an XML document, and the Python module namespace. It is often convenient to model the frontend to a hierarchical data store as a graph, using traversal to apply views to objects that either are the nodes in the graph being traversed (such as in the case of ZODB) or at least ones which stand in for them (such as in the case of wrappers for files from the filesystem).
Also, many website structures are naturally hierarchical, even if the data which drives them isn’t. For example, newspaper websites are often extremely hierarchical: sections within sections within sections, ad infinitum. If you want your URLs to indicate this structure, and the structure is indefinite (the number of nested sections can be “N” instead of some fixed number), traversal is an excellent way to model this, even if the backend is a relational database. In this situation, the graph being traversed is actually less a “model graph” than a site structure.
But the point is ultimately moot. If you use repoze.bfg, and you don’t want to model your application in terms of traversal, you needn’t use it at all. Instead, use URL dispatch to map URL paths to views.
In repoze.bfg, url dispatch is the act of resolving a URL path to a view callable by performing pattern matching against some set of ordered route definitions. The route definitions are examined in order: the first pattern which matches is used to associate the URL with a view callable.
Some people are uncomfortable with this notion, and believe it is wrong. These are usually people who are steeped deeply in Zope. Zope does not provide any mechanism except traversal to map code to URLs. This is mainly because Zope effectively requires use of ZODB, which is a hierarchical object store. Zope also supports relational databases, but typically the code that calls into the database lives somewhere in the ZODB object graph (or at least is a view related to a node in the object graph), and traversal is required to reach this code.
I’ll argue that URL dispatch is ultimately useful, even if you want to use traversal as well. You can actually combine URL dispatch and traversal in repoze.bfg (see Combining Traversal and URL Dispatch). One example of such a usage: if you want to emulate something like Zope 2’s “Zope Management Interface” UI on top of your object graph (or any administrative interface), you can register a route like <route name="manage" path="manage/*traverse"/> and then associate “management” views in your code by using the route_name argument to a view configuration, e.g. <view view=".some.callable" context=".some.Model" route_name="manage"/>. If you wire things up this way someone then walks up to for example, /manage/ob1/ob2, they might be presented with a management interface, but walking up to /ob1/ob2 would present them with the default object view. There are other tricks you can pull in these hybrid configurations if you’re clever (and maybe masochistic) too.
Also, if you are a URL dispatch hater, if you should ever be asked to write an application that must use some legacy relational database structure, you might find that using URL dispatch comes in handy for one-off associations between views and URL paths. Sometimes it’s just pointless to add a node to the object graph that effectively represents the entry point for some bit of code. You can just use a route and be done with it. If a route matches, a view associated with the route will be called; if no route matches, repoze.bfg falls back to using traversal.
But the point is ultimately moot. If you use repoze.bfg, and you really don’t want to use URL dispatch, you needn’t use it at all. Instead, use traversal exclusively to map URL paths to views, just like you do in Zope.
Many web frameworks (Zope, TurboGears, Pylons, Django) allow for their variant of a view callable to accept arbitrary keyword or positional arguments, which are “filled in” using values present in the request.POST or request.GET dictionaries or by values present in the “route match dictionary”. For example, a Django view will accept positional arguments which match information in an associated “urlconf” such as r'^polls/(?P<poll_id>\d+)/$:
def aview(request, poll_id): return HttpResponse(poll_id)
Zope, likewise allows you to add arbitrary keyword and positional arguments to any method of a model object found via traversal:
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from persistent import Persistent class MyZopeObject(Persistent): def aview(self, a, b, c=None): return '%s %s %c' % (a, b, c)
When this method is called as the result of being the published callable, the Zope request object’s GET and POST namespaces are searched for keys which match the names of the positional and keyword arguments in the request, and the method is called (if possible) with its argument list filled with values mentioned therein. TurboGears and Pylons operate similarly.
repoze.bfg has neither of these features. repoze.bfg view callables always accept only context and request (or just request), and no other arguments. The rationale: this argument specification matching done aggressively can be costly, and repoze.bfg has performance as one of its main goals, so we’ve decided to make people obtain information by interrogating the request object for it in the view body instead of providing magic to do unpacking into the view argument list. The feature itself also just seems a bit like a gimmick. Getting the arguments you want explicitly from the request via getitem is not really very hard; it’s certainly never a bottleneck for the author when he writes web apps.
It is possible to replicate the Zope-like behavior in a view callable decorator, however, should you badly want something like it back. No such decorator currently exists. If you’d like to create one, Google for “zope mapply” and adapt the function you’ll find to a decorator that pulls the argument mapping information out of the request.params dictionary.
A similar feature could be implemented to provide the Django-like behavior as a decorator by wrapping the view with a decorator that looks in request.matchdict.
It’s possible at some point that repoze.bfg will grow some form of argument matching feature (it would be simple to make it an always-on optional feature that has no cost unless you actually use it) for, but currently it has none.
By design, repoze.bfg is not a particularly “opinionated” web framework. It has a relatively parsimonious feature set. It contains no built in ORM nor any particular database bindings. It contains no form generation framework. It does not contain a sessioning library. It has no administrative web user interface. It has no built in text indexing. It does not dictate how you arrange your code.
Such opinionated functionality exists in applications and frameworks built on top of repoze.bfg. It’s intended that higher-level systems emerge built using repoze.bfg as a base. See also BFG Applications are Extensible; I Don’t Believe In Application Extensibility.
repoze.bfg provides some features that other web frameworks do not. Most notably it has machinery which resolves a URL first to a context before calling a view (which has the capability to accept the context in its argument list), and a declarative authorization system that makes use of this feature. Most other web frameworks besides Zope, from which the pattern was stolen, have no equivalent core feature.
We consider this an important feature for a particular class of applications (CMS-style applications, which the authors are often commissioned to write) that usually use traversal against a persistent object graph. The object graph contains security declarations as ACL objects.
Having context-sensitive declarative security for individual objects in the object graph is simply required for this class of application. Other frameworks save for Zope just do not have this feature. This is one of the primary reasons that repoze.bfg was actually written.
If you don’t like this, it doesn’t mean you can’t use repoze.bfg. Just ignore this feature and avoid configuring an authorization or authentication policy and using ACLs. You can build “Pylons-style” applications using repoze.bfg that use their own security model via decorators or plain-old-imperative logic in view code.
“The repoze.bfg compressed tarball is 1MB. It must be enormous!”
No. We just ship it with test code and helper templates. Here’s a breakdown of what’s included in subdirectories of the package tree:
repoze/bfg (except for repoze/bfg/tests and repoze/bfg/paster_templates)
The actual repoze.bfg runtime code is about 10% of the total size of the tarball omitting docs, helper templates used for package generation, and test code. Of the approximately 13K lines of Python code in the package, the code that actually has a chance of executing during normal operation, excluding tests and paster template Python files, accounts for approximately 3K lines of Python code. This is comparable to Pylons, which ships with a little over 2K lines of Python code, excluding tests.
This is true. At the time of this writing, the total number of Python package distributions that repoze.bfg depends upon transitively is 14 if you use Python 2.6 or 2.7, or 16 if you use Python 2.4 or 2.5. This is a lot more than zero package distribution dependencies: a metric which various Python microframeworks and Django boast.
The zope.component and zope.configuration packages on which repoze.bfg depends have transitive dependencies on several other packages (zope.schema, zope.i18n, zope.event, zope.interface, zope.deprecation, zope.i18nmessageid). We’ve been working with the Zope community to try to collapse and untangle some of these dependencies. We’d prefer that these packages have fewer packages as transitive dependencies, and that much of the functionality of these packages was moved into a smaller number of packages.
It should be noted that repoze.bfg is positively lithe compared to Grok, a different Zope-based framework. As of this writing, in its default configuration, Grok has 126 package distribution dependencies. The number of dependencies required by repoze.bfg is many times fewer than Grok (or Zope itself, upon which Grok is based). repoze.bfg has a number of package distribution dependencies comparable to similarly-targeted frameworks such as Pylons.
We try not to reinvent too many wheels (at least the ones that don’t need reinventing), and this comes at the cost of some number of dependencies. However, “number of package distributions” is just not a terribly great metric to measure complexity. For example, the zope.event distribution on which repoze.bfg depends has a grand total of four lines of runtime code. As noted above, we’re continually trying to agitate for a collapsing of these sorts of packages into fewer distribution files.
Complaints have been lodged by other web framework authors at various times that repoze.bfg “cheats” to gain performance. One claimed cheating mechanism is our use (transitively) of the C extensions provided by zope.interface to do fast lookups. Another claimed cheating mechanism is the religious avoidance of extraneous function calls.
If there’s such a thing as cheating to get better performance, we want to cheat as much as possible. We optimize repoze.bfg aggressively. This comes at a cost: the core code has sections that could be expressed more readably. As an amelioration, we’ve commented these sections liberally.
“I’m a MVC web framework user, and I’m confused. repoze.bfg calls the controller a view! And it doesn’t have any controllers.”
People very much want to give web applications the same properties as common desktop GUI platforms by using similar terminology, and to provide some frame of reference for how various components in the common web framework might hang together. But in the opinion of the author, “MVC” doesn’t match the web very well in general. Quoting from the Model-View-Controller Wikipedia entry:
Though MVC comes in different flavors, control flow is generally as follows: The user interacts with the user interface in some way (for example, presses a mouse button). The controller handles the input event from the user interface, often via a registered handler or callback and converts the event into appropriate user action, understandable for the model. The controller notifies the model of the user action, possibly resulting in a change in the model's state. (For example, the controller updates the user's shopping cart.) A view queries the model in order to generate an appropriate user interface (for example, the view lists the shopping cart's contents). Note that the view gets its own data from the model. The controller may (in some implementations) issue a general instruction to the view to render itself. In others, the view is automatically notified by the model of changes in state (Observer) which require a screen update. The user interface waits for further user interactions, which restarts the cycle.
To the author, it seems as if someone edited this Wikipedia definition, tortuously couching concepts in the most generic terms possible in order to account for the use of the term “MVC” by current web frameworks. I doubt such a broad definition would ever be agreed to by the original authors of the MVC pattern. But even so, it seems most “MVC” web frameworks fail to meet even this falsely generic definition.
For example, do your templates (views) always query models directly as is claimed in “note that the view gets its own data from the model”? Probably not. My “controllers” tend to do this, massaging the data for easier use by the “view” (template). What do you do when your “controller” returns JSON? Do your controllers use a template to generate JSON? If not, what’s the “view” then? Most MVC-style GUI web frameworks have some sort of event system hooked up that lets the view detect when the model changes. The web just has no such facility in its current form: it’s effectively pull-only.
So, in the interest of not mistaking desire with reality, and instead of trying to jam the square peg that is the web into the round hole of “MVC”, we just punt and say there are two things: the model, and the view. The model stores the data, the view presents it. The templates are really just an implementation detail of any given view: a view doesn’t need a template to return a response. There’s no “controller”: it just doesn’t exist. This seems to us like a more reasonable model, given the current constraints of the web.
Any repoze.bfg application written obeying certain constraints is extensible. This feature is discussed in the repoze.bfg documentation chapter named Extending An Existing repoze.bfg Application. It is made possible by the use of the Zope Component Architecture and ZCML within repoze.bfg.
“Extensible”, in this context, means:
Many developers seem to believe that creating extensible applications is “not worth it”. They instead suggest that modifying the source of a given application for each deployment to override behavior is more reasonable. Much discussion about version control branching and merging typically ensues.
It’s clear that making every application extensible isn’t required. The majority of web applications only have a single deployment, and thus needn’t be extensible at all. However, some web applications have multiple deployments, and some have many deployments. For example, a generic “content management” system (CMS) may have basic functionality that needs to be extended for a particular deployment. That CMS system may be deployed for many organizations at many places. Some number of deployments of this CMS may be deployed centrally by a third party and managed as a group. It’s useful to be able to extend such a system for each deployment via preordained plugpoints than it is to continually keep each software branch of the system in sync with some upstream source: the upstream developers may change code in such a way that your changes to the same codebase conflict with theirs in fiddly, trivial ways. Merging such changes repeatedly over the lifetime of a deployment can be difficult and time consuming, and it’s often useful to be able to modify an application for a particular deployment in a less invasive way.
If you don’t want to think about repoze.bfg application extensibility at all, you needn’t. You can ignore extensibility entirely. However, if you follow the set of rules defined in Extending An Existing repoze.bfg Application, you don’t need to make your application extensible: any application you write in the framework just is automatically extensible at a basic level. The mechanisms that deployers use to extend it will be necessarily coarse: typically, views, routes, and resources will be capable of being overridden, usually via ZCML. But for most minor (and even some major) customizations, these are often the only override plugpoints necessary: if the application doesn’t do exactly what the deployment requires, it’s often possible for a deployer to override a view, route, or resource and quickly make it do what he or she wants it to do in ways not necessarily anticipated by the original developer. Here are some example scenarios demonstrating the benefits of such a feature.
As long as the fundamental design of the upstream package doesn’t change, these types of modifications often survive across many releases of the upstream package without needing to be revisited.
Extending an application externally is not a panacea, and carries a set of risks similar to branching and merging: sometimes major changes upstream will cause you to need to revisit and update some of your modifications. But you won’t regularly need to deal wth meaningless textual merge conflicts that trivial changes to upstream packages often entail when it comes time to update the upstream package, because if you extend an application externally, there just is no textual merge done. Your modifications will also, for whatever its worth, be contained in one, canonical, well-defined place.
Branching an application and continually merging in order to get new features and bugfixes is clearly useful. You can do that with a repoze.bfg application just as usefully as you can do it with any application. But deployment of an application written in repoze.bfg makes it possible to avoid the need for this even if the application doesn’t define any plugpoints ahead of time. It’s possible that promoters of competing web frameworks dismiss this feature in favor of branching and merging because applications written in their framework of choice aren’t extensible out of the box in a comparably fundamental way.
While repoze.bfg application are fundamentally extensible even if you don’t write them with specific extensibility in mind, if you’re moderately adventurous, you can also take it a step further. If you learn more about the Zope Component Architecture, you can optionally use it to expose other more domain-specific configuration plugpoints while developing an application. The plugpoints you expose needn’t be as coarse as the ones provided automatically by repoze.bfg itself. For example, you might compose your own ZCML directive that configures a set of views for a prebaked purpose (e.g. restview or somesuch) , allowing other people to refer to that directive when they make declarations in the configure.zcml of their customization package. There is a cost for this: the developer of an application that defines custom plugpoints for its deployers will need to understand the ZCA or he will need to develop his own similar extensibility system.
Ultimately, any argument about whether the extensibility features lent to applications by repoze.bfg are “good” or “bad” is somewhat pointless. You needn’t take advantage of the extensibility features provided by a particular repoze.bfg application in order to affect a modification for a particular set of its deployments. You can ignore the application’s extensibility plugpoints entirely, and instead use version control branching and merging to manage application deployment modifications instead, as if you were deploying an application written using any other web framework.
“Big Friendly Giant” is not safe for your work? Where do you work? ;-)
The repoze.bfg API is organized in such a way that API imports must come from submodules of the repoze.bfg namespace. For instance:
from repoze.bfg.settings import get_settings from repoze.bfg.url import model_url
Some folks understandably don’t want to think about the submodule organization, and would rather be able to do:
from repoze.bfg import get_settings from repoze.bfg import model_url
This would indeed be nice. However, the repoze.bfg Python package is a namespace package. The __init__.py of a namespace package cannot contain any meaningful code such as imports from submodules which would let us form a flatter API. Sorry.
Though it makes the API slightly “thinkier”, making the repoze.bfg package into a namespace package was an early design decision, which we believe has paid off. The primary goal is to make it possible to move features out of the core repoze.bfg distribution and into add-on distributions without breaking existing imports. The repoze.bfg.lxml distribution is an example of such a package: this functionality used to live in the core distribution, but we later decided that a core dependency on lxml was unacceptable. Because repoze.bfg is a namespace package, we were able to remove the repoze.bfg.lxml module from the core and create a distribution named repoze.bfg.lxml which contains an eponymous package. We were then able, via our changelog, to inform people that might have been depending on the feature that although it no longer shipped in the core distribution, they could get it back without changing any code by adding an install_requires line to their application package’s setup.py.
Often new repoze.bfg features are released as add-on packages in the repoze.bfg namespace. Because repoze.bfg is a namespace package, if we want to move one of these features in to the core distribition at some point, we can do so without breaking code which imports from the older package namespace. This is currently less useful than the ability to move features out of the core distribution, as setuptools does not yet have any concept of “obsoletes” metadata which we could add to the core distribution. This means it’s not yet possible to declaratively deprecate the older non-core package in the eyes of tools like easy_install, pip and buildout.
Self-described “microframeworks” exist: Bottle and Flask are two that are becoming popular. Bobo doesn’t describe itself as a microframework, but its intended userbase is much the same. Many others exist. We’ve actually even (only as a teaching tool, not as any sort of official project) created one using BFG. Microframeworks are small frameworks with one common feature: each allows its users to create a fully functional application that lives in a single Python file.
Some developers and microframework authors point out that BFG’s “hello world” single-file program is longer (by about five lines) than the equivalent program in their favorite microframework. Guilty as charged; in a contest of “whose is shortest”, BFG indeed loses.
This loss isn’t for lack of trying. BFG aims to be useful in the same circumstance in which microframeworks claim dominance: single-file applications. But BFG doesn’t sacrifice its ability to credibly support larger applications in order to achieve hello-world LoC parity with the current crop of microframeworks. BFG’s design instead tries to avoid some common pitfalls associated with naive declarative configuration schemes. The subsections which follow explain the rationale.
Please imagine a directory structure with a set of Python files in it:
. |-- app.py |-- app2.py `-- config.py
The contents of app.py:
from config import decorator from config import L import pprint @decorator def foo(): pass if __name__ == '__main__': import app2 pprint.pprint(L)
The contents of app2.py:
import app @app.decorator def bar(): pass
The contents of config.py:
L =  def decorator(func): L.append(func) return func
If we cd to the directory that holds these files and we run python app.py given the directory structure and code above, what happens? Presuably, our decorator decorator will be used twice, once by the decorated function foo in app.py and once by the decorated function bar in app2.py. Since each time the decorator is used, the list L in config.py is appended to, we’d expect a list with two elements to be printed, right? Sadly, no:
[chrism@thinko]$ python app.py [<function foo at 0x7f4ea41ab1b8>, <function foo at 0x7f4ea41ab230>, <function bar at 0x7f4ea41ab2a8>]
By visual inspection, that outcome (three different functions in the list) seems impossible. We only defined two functions and we decorated each of those functions only once, so we believe that the decorator decorator will only run twice. However, what we believe is wrong because the code at module scope in our app.py module was executed twice. The code is executed once when the script is run as __main__ (via python app.py), and then it is executed again when app2.py imports the same file as app.
What does this have to do with our comparison to microframeworks? Many microframeworks in the current crop (e.g. Bottle, Flask) encourage you to attach configuration decorators to objects defined at module scope. These decorators execute arbitrarily complex registration code which populates a singleton registry that is a global defined in external Python module. This is analogous to the above example: the “global registry” in the above example is the list L.
Let’s see what happens when we use the same pattern with the Groundhog microframework. Replace the contents of app.py above with this:
from config import gh @gh.route('/foo/') def foo(): return 'foo' if __name__ == '__main__': import app2 pprint.pprint(L)
Replace the contents of app2.py above with this:
import app @app.gh.route('/bar/') def bar(): 'return bar'
Replace the contents of config.py above with this:
from groundhog import Groundhog gh = Groundhog('myapp', 'seekrit')
How many routes will be registered within the routing table of the “gh” Groundhog application? If you answered three, you are correct. How many would a casual reader (and any sane developer) expect to be registered? If you answered two, you are correct. Will the double registration be a problem? With our fictional Groundhog framework’s route method backing this application, not really. It will slow the application down a little bit, because it will need to miss twice for a route when it does not match. Will it be a problem with another framework, another application, or another decorator? Who knows. You need to understand the application in its totality, the framework in its totality, and the chronology of execution to be able to predict what the impact of unintentional code double-execution will be.
The encouragement to use decorators which perform population of an external registry has an unintended consequence: the application developer now must assert ownership of every codepath that executes Python module scope code. This code is presumed by the current crop of decorator-based microframeworks to execute once and only once; if it executes more than once, weird things will start to happen. It is up to the application developer to maintain this invariant. Unfortunately, however, in reality, this is an impossible task, because, Python programmers do not own the module scope codepath, and never will. Microframework programmers therefore will at some point then need to start reading the tea leaves about what might happen if module scope code gets executed more than once like we do in the previous paragraph. This is a really pretty poor situation to find yourself in as an application developer: you probably didn’t even know you signed up for the job, because the documentation offered by decorator-based microframeworks don’t warn you about it.
Python application programmers do not control the module scope codepath. Anyone who tries to sell you on the idea that they do is simply mistaken. Test runners that you may want to use to run your code’s tests often perform imports of arbitrary code in strange orders that manifest bugs like the one demonstrated above. API documentation generation tools do the same. Some (mutant) people even think it’s safe to use the Python reload command or delete objects from sys.modules, each of which has hilarious effects when used against code that has import- time side effects. When Python programmers assume they can use the module-scope codepath to run arbitrary code (especially code which populates an external registry), and this assumption is challenged by reality, the application developer is often required to undergo a painful, meticulous debugging process to find the root cause of an inevitably obscure symptom. The solution is often to rearrange application import ordering or move an import statement from module-scope into a function body. The rationale for doing so can never be expressed adequnately in the checkin message which accompanies the fix or documented succinctly enough for the benefit of the rest of the development team so that the problem never happens again. It will happen again next month too, especially if you are working on a project with other people who haven’t yet internalized the lessons you learned while you stepped through module-scope code using pdb.
Folks who have a large investment in eager decorator-based configuration that populates an external data structure (such as microframework authors) may argue that the set of circumstances I outlined above is anomalous and contrived. They will argue that it just will never happen. If you never intend your application to grow beyond one or two or three modules, that’s probably true. However, as your codebase grows, and becomes spread across a greater number of modules, the circumstances in which module-scope code will be executed multiple times will become more and more likely to occur and less and less predictable. It’s not responsible to claim that double-execution of module-scope code will never happen. It will; it’s just a matter of luck, time, and application complexity.
If microframework authors do admit that the circumstance isn’t contrived, they might then argue that “real” damage will never happen as the result of the double-execution (or triple-execution, etc) of module scope code. You would be wise to disbelieve this assertion. The potential outcomes of multiple execution are too numerous to predict because they involve delicate relationships between application and framework code as well as chronology of code execution. It’s literally impossible for a framework author to know what will happen in all circumstances (“X is executed, then Y, then X again.. a train leaves Chicago at 50 mph... “). And even if given the gift of omniscience for some limited set of circumstances, the framework author almost certainly does not have the double-execution anomaly in mind when coding new features. He’s thinking of adding a feature, not protecting against problems that might be caused by the 1% multiple execution case. However, any 1% case may cause 50% of your pain on a project, so it’d be nice if it never occured.
Responsible microframeworks actually offer a back-door way around the problem. They allow you to disuse decorator based configuration entirely. Instead of requiring you to do the following:
gh = Groundhog('myapp', 'seekrit') @gh.route('/foo/') def foo(): return 'foo' if __name__ == '__main__': gh.run()
They allow you to disuse the decorator syntax and go almost-all-imperative:
def foo(): return 'foo' gh = Groundhog('myapp', 'seekrit') if __name__ == '__main__': gh.add_route(foo, '/foo/') gh.run()
This is a generic mode of operation that is encouraged in the BFG documentation. Some existing microframeworks (Flask, in particular) allow for it as well. None (other than BFG) encourage it. If you never expect your application to grow beyond two or three or four or ten modules, it probably doesn’t matter very much which mode you use. If your application grows large, however, imperative configuration can provide better predictability.
Astute readers may notice that BFG has configuration decorators too. Aha! Don’t these decorators have the same problems? No. These decorators do not populate an external Python module when they are executed. They only mutate the functions (and classes and methods) they’re attached to. These mutations must later be found during a “scan” process that has a predictable and structured import phase. Module-localized mutation is actually the best-case circumstance for double-imports; if a module only mutates itself and its contents at import time, if it is imported twice, that’s OK, because each decorator invocation will always be mutating an independent copy of the object its attached to, not a shared resource like a registry in another module. This has the effect that double-registrations will never be performed.
Consider the following simple Groundhog application:
from groundhog import Groundhog app = Groundhog('myapp', 'seekrit') app.route('/admin') def admin(): return '<html>admin page</html>' app.route('/:action') def action(): if action == 'add': return '<html>add</html>' if action == 'delete': return '<html>delete</html>' return app.abort(404) if __name__ == '__main__': app.run()
If you run this application and visit the URL /admin, you will see “admin” page. This is the intended result. However, what if you rearrange the order of the function definitions in the file?
from groundhog import Groundhog app = Groundhog('myapp', 'seekrit') app.route('/:action') def action(): if action == 'add': return '<html>add</html>' if action == 'delete': return '<html>delete</html>' return app.abort(404) app.route('/admin') def admin(): return '<html>admin page</html>' if __name__ == '__main__': app.run()
If you run this application and visit the URL /admin, you will now be returned a 404 error. This is probably not what you intended. The reason you see a 404 error when you rearrange function definition ordering is that routing declarations expressed via our microframework’s routing decorators have an ordering, and that ordering matters.
In the first case, where we achieved the expected result, we first added a route with the pattern /admin, then we added a route with the pattern /:action by virtue of adding routing patterns via decorators at module scope. When a request with a PATH_INFO of /admin enters our application, the web framework loops over each of our application’s route patterns in the order in which they were defined in our module. As a result, the view associated with the /admin routing pattern will be invoked: it matches first. All is right with the world.
In the second case, where we did not achieve the expected result, we first added a route with the pattern /:action, then we added a route with the pattern /admin. When a request with a PATH_INFO of /admin enters our application, the web framework loops over each of our application’s route patterns in the order in which they were defined in our module. As a result, the view associated with the /:action routing pattern will be invoked: it matches first. A 404 error is raised. This is not what we wanted; it just happened due to the order in which we defined our view functions.
You may be willing to maintain an ordering of your view functions which reifies your routing policy. Your application may be small enough where this will never cause an issue. If it becomes large enough to matter, however, I don’t envy you. Maintaining that ordering as your application grows larger will be difficult. At some point, you will also need to start controlling import ordering as well as function definition ordering. When your application grows beyond the size of a single file, and when decorators are used to register views, the non-__main__ modules which contain configuration decorators must be imported somehow for their configuration to be executed.
Does that make you a little uncomfortable? It should, because Application Programmers Don’t Control The Module-Scope Codepath (Import-Time Side-Effects Are Evil).
In another manifestation of “import fascination”, some microframeworks use the import statement to get a handle to an object which is not logically global:
from flask import request @app.route('/login', methods=['POST', 'GET']) def login(): error = None if request.method == 'POST': if valid_login(request.form['username'], request.form['password']): return log_the_user_in(request.form['username']) else: error = 'Invalid username/password' # this is executed if the request method was GET or the # credentials were invalid
The Pylons web framework uses a similar strategy. It calls these things “Stacked Object Proxies”, so, for purposes of this discussion, I’ll do so as well.
Import statements in Python (import foo, from bar import baz) are most frequently performed to obtain a reference to an object defined globally within an external Python module. However, in “normal” programs, they are never used to obtain a reference to an object that has a lifetime measured by the scope of the body of a function. It would be absurd to try to import, for example, a variable named i representing a loop counter defined in the body of a function. For example, we’d never try to import i from the code below:
def afunc(): for i in range(10): print i
By its nature, the request object created as the result of a WSGI server’s call into a long-lived web framework cannot be global, because the lifetime of a single request will be much shorter than the lifetime of the process running the framework. A request object created by a web framework actually has more similarity to the i loop counter in our example above than it has to any comparable importable object defined in the Python standard library or in “normal” library code.
However, systems which use stacked object proxies promote locally scoped objects such as request out to module scope, for the purpose of being able to offer users a “nice” spelling involving import. They, for what I consider dubious reasons, would rather present to their users the canonical way of getting at a request as from framework import request instead of a saner from myframework.threadlocals import get_request; request = get_request() even though the latter is more explicit.
It would be most explicit if the microframeworks did not use thread local variables at all. BFG view functions are passed a request object; many of BFG’s APIs require that an explicit request object be passed to them. It is possible to retrieve the current BFG request as a threadlocal variable but it is a “in case of emergency, break glass” type of activity. This explicitness makes BFG view functions more easily unit testable, as you don’t need to rely on the framework to manufacture suitable “dummy” request (and other similarly-scoped) objects during test setup. It also makes them more likely to work on arbitrary systems, such as async servers that do no monkeypatching.
Some microframeworks offer a run() method of an application object that executes a default server configuration for easy execution.
BFG doesn’t currently try to hide the fact that its router is a WSGI application behind a convenience run() API. It just tells people to import a WSGI server and use it to serve up their BFG application as per the documentation of that WSGI server.
The extra lines saved by abstracting away the serving step behind run() seem to have driven dubious second-order decisions related to API in some microframeworks. For example, Bottle contains a ServerAdapter subclass for each type of WSGI server it supports via its app.run() mechanism. This means that there exists code in bottle.py that depends on the following modules: wsgiref, flup, paste, cherrypy, fapws, tornado, google.appengine, twisted.web, diesel, gevent, gunicorn, eventlet, and rocket. You choose the kind of server you want to run by passing its name into the run method. In theory, this sounds great: I can try Bottle out on gunicorn just by passing in a name! However, to fully test Bottle, all of these third-party systems must be installed and functional; the Bottle developers must monitor changes to each of these packages and make sure their code still interfaces properly with them. This expands the packages required for testing greatly; this is a lot of requirements. It is likely difficult to fully automate these tests due to requirements conflicts and build issues.
As a result, for single-file apps, we currently don’t bother to offer a run() shortcut; we tell folks to import their WSGI server of choice and run it “by hand”. For the people who want a server abstraction layer, we suggest that they use PasteDeploy. In PasteDeploy-based systems, the onus for making sure that the server can interface with a WSGI application is placed on the server developer, not the web framework developer, making it more likely to be timely and correct.
All of the above said, BFG version 1.3 may offer a run() - like shortcut serving API which executes a WSGI server. But I might also chicken out and not add it: I’d rather not deal with needing to supply support answers like this one. If I add such a method, it will likely be named less attractively to indicate it is only a shortcut.
These exist because existing legacy third party configuration (not runtime) code relies on a threadlocal stack being populated. The begin method pushes data on to a threadlocal stack. The end method pops it back off.
For the simplest applications, these lines are actually not required. I could omit them from every BFG hello world app without ill effect. However, when users use certain configuration methods (ones not represented in the hello world app), calling code will begin to fail when it is not bracketed between a begin() and an end(). It is just easier to tell users that this bracketing is required than to try to explain to them which circumstances it is actually required and which it is not, because the explanation is often torturous.
The effectively-required execution of these two methods is a wholly bogus artifact of an early bad design decision which encouraged application developers to use threadlocal data structures during the execution of configuration plugins. However, I don’t hate my framework’s users enough to break backwards compatibility for the sake of removing two boilerplate lines of code, so it stays, at least for the foreseeable future. If I eventually figure out a way to remove the requirement, these methods will turn into no-ops and they will be removed from the documenation.
Here’s a diagrammed version of the simplest repoze.bfg application, where comments take into account what we’ve discussed in the Microframeworks Have Smaller Hello World Programs section.
from webob import Response # explicit response objects, no TL from paste.httpserver import serve # explicitly WSGI def hello_world(request): # accepts a request; no request thread local reqd # explicit response object means no response threadlocal return Response('Hello world!') if __name__ == '__main__': from repoze.bfg.configuration import Configurator config = Configurator() # no global application object. config.begin() # bogus, but required. config.add_view(hello_world) # explicit non-decorator registration config.end() # bogus, but required. app = config.make_wsgi_app() # explicitly WSGI serve(app, host='0.0.0.0') # explicitly WSGI