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CHAPTER

FIFTEEN

MODULAR APPLICATIONS WITH

BLUEPRINTS

New in version 0.7.

Flask uses a concept of blueprints for making application components and supporting

common patterns within an application or across applications. Blueprints can greatly

simplify howlargeapplications work and provide a central means forFlask extensions

to register operations on applications. A Blueprint object works similarly to a Flask

application object, but it is not actually an application. Rather it is a blueprint of how

to construct or extend an application.

15.1 Why Blueprints?

Blueprints in Flask are intended for these cases:

• Factor an applicationinto a set of blueprints. This is ideal for larger applications;

aproject could instantiate an application object, initialize several extensions, and

• Register a blueprint on an application at a URL preﬁx and/or subdomain. Pa-

rameters in the URL preﬁx/subdomain become common view arguments (with

defaults) across all view functions in the blueprint.

• Register a blueprint multiple times on an application with different URL rules.

• Provide template ﬁlters, static ﬁles, templates, and other utilities through

blueprints. A blueprint does not have to implement applications or view func-

tions.

• Register a blueprint on an application for any of these cases when initializing a

Flask extension.

Ablueprint in Flask is not a pluggable app because it is not actually an application

–it’s a set of operations which can be registered on an application, even multiple

times. Why not have multiple application objects? You can do that (see Application

Dispatching), but your applications will have separate conﬁgs and will be managed at

the WSGI layer.

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Blueprints instead provide separation at the Flask level, share application conﬁg, and

can change an application object as necessary with being registered. The downside is

that you cannotunregister a blueprintonce an applicationwas created without having

to destroy the whole application object.

15.2 The Concept of Blueprints

The basic concept of blueprints is that they record operations to execute when reg-

istered on an application. Flask associates view functions with blueprints when dis-

patching requests and generating URLs from one endpoint to another.

15.3 My First Blueprint

This is what a very basic blueprint looks like. In this case we want to implement a

blueprint that does simple rendering of static templates:

from flask import Blueprint, render_template, abort

from jinja2 import TemplateNotFound

simple_page = Blueprint(simple_page, __name__,

template_folder=templates)

@simple_page.route(/, defaults={page: index})

@simple_page.route(/<page>)

def show(page):

try:

return render_template(pages/%s.html % page)

except TemplateNotFound:

abort(404)

When you bind a function with the help of the @simple_page.route decorator the

blueprint will record the intention of registering the function show on the application

when it’s later registered. Additionally it will preﬁx the endpoint of the function with

the name of the blueprint which was given to the Blueprint constructor (in this case

also simple_page).

15.4 Registering Blueprints

So how do you register that blueprint? Like this:

from flask import Flask

from yourapplication.simple_page import simple_page

app = Flask(__name__)

app.register_blueprint(simple_page)

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If you check the rules registered on the application, you will ﬁnd these:

[<Rule /static/<filename> (HEAD, OPTIONS, GET) -> static>,

<Rule /<page> (HEAD, OPTIONS, GET) -> simple_page.show>,

<Rule / (HEAD, OPTIONS, GET) -> simple_page.show>]

The ﬁrst one is obviously from the application ifself for the static ﬁles. The other two

are for the show function of the simple_page blueprint. As you can see, they are also

preﬁxed with the name of the blueprint and separated by a dot (.).

Blueprints however can also be mounted at different locations:

app.register_blueprint(simple_page, url_prefix=/pages)

And sure enough, these are the generated rules:

[<Rule /static/<filename> (HEAD, OPTIONS, GET) -> static>,

<Rule /pages/<page> (HEAD, OPTIONS, GET) -> simple_page.show>,

<Rule /pages/ (HEAD, OPTIONS, GET) -> simple_page.show>]

On top of that you can register blueprints multiple times though not every blueprint

might respond properly to that. In fact it depends on how the blueprint is imple-

mented if it can be mounted more than once.

15.5 Blueprint Resources

Blueprints can provide resources as well. Sometimes you might want to introduce a

blueprint only for the resources it provides.

15.5.1 Blueprint Resource Folder

Like for regular applications, blueprints are considered to be contained in a folder.

While multiple blueprints can originate from the same folder, it does not have to be

the case and it’s usually not recommended.

The folder is inferred from the second argument to Blueprint which is usually

__name__. This argument speciﬁes what logical Python module or package corre-

sponds to the blueprint. Ifit points to an actual Pythonpackage that package (whichis

afolderon the ﬁlesystem) is the resource folder. If it’s a module, the package the mod-

ule is contained inwill be the resource folder. You can access the Blueprint.root_path

property to see what the resource folder is:

>>> simple_page.root_path

/Users/username/TestProject/yourapplication

To quickly open sources from this folder you can use the open_resource() function:

with simple_page.open_resource(static/style.css) as f:

code = f.read()

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15.5.2 Static Files

Ablueprint can expose a folder with static ﬁles by providing a path to a folder on the

ﬁlesystem via the static_folder keyword argument. It can either be an absolute path or

one relative to the folder of the blueprint:

admin = Blueprint(admin, __name__, static_folder=static)

By default the rightmost part of the path is where it is exposed on the web. Because

the folder is called static here it will be available at the location of the blueprint

+ /static. Say the blueprint is registered for /admin the static folder will be at

/admin/static.

The endpoint is named blueprint_name.static so you can generate URLs to it like you

would do to the static folder of the application:

url_for(admin.static, filename=style.css)

15.5.3 Templates

If you want the blueprint to expose templates you can do that by providing the tem-

plate_folder parameter to the Blueprint constructor:

admin = Blueprint(admin, __name__, template_folder=templates)

As for static ﬁles, the path can be absolute or relative to the blueprint resource folder.

The template folder is added to the searchpath of templates but with a lower prior-

ity than the actual application’s template folder. That way you can easily override

templates that a blueprint provides in the actual application.

So if you have a blueprint in the folder yourapplication/admin and you

want to render the template ’admin/index.html’ and you have provided

templates as a template_folder you will have to create a ﬁle like this:

yourapplication/admin/templates/admin/index.html.

15.6 Building URLs

If you want to link from one page to another you can use the url_for() function just

like you normally would do just that you preﬁx the URL endpoint with the name of

the blueprint and a dot (.):

url_for(admin.index)

Additionally if you are in a view function of a blueprint or a rendered template and

you want to link to another endpoint of the same blueprint, you can use relative redi-

rects by preﬁxing the endpoint with a dot only:

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url_for(.index)

This will link to admin.index for instance in case the current request was dispatched

to any other admin blueprint endpoint.

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CHAPTER

SIXTEEN

FLASK EXTENSIONS

Flask extensions extend the functionality of Flask in various different ways. For in-

stance they add support for databases and other common tasks.

16.1 Finding Extensions

Flask extensions are listed on theFlaskExtensionRegistry and can be downloaded

with easy_install or pip. If you add a Flask extension as dependency to your

requirements.rst or setup.py ﬁle they are usually installed with a simple command

or when your application installs.

16.2 Using Extensions

Extensions typically have documentation that goes along that shows how to use it.

There are no general rules in how extensions are supposed to behave but they are

imported from common locations. If you have an extension called Flask-Foo or

Foo-Flask it will be always importable from flask.ext.foo:

from flask.ext import t foo

16.3 Flask Before 0.8

If you are using Flask 0.7 or earlier the flask.ext package will not exist, instead you

have to import from flaskext.foo or flask_foo depending on how the extension is

distributed. If you want to developan applicationthatsupports Flask 0.7 orearlier you

should still import from the flask.ext package. We provide you with a compatibility

module that provides this package for older versions of Flask. You can download it

from github:ﬂaskext_compat.py

And here is how you can use it:

import flaskext_compat

flaskext_compat.activate()

from flask.ext import t foo

Once the flaskext_compat module is activated the flask.ext will exist and you can

start importing from there.

CHAPTER

SEVENTEEN

WORKING WITH THE SHELL

New in version 0.3.

One of the reasons everybody loves Python is the interactive shell. It basically allows

you to execute Python commands in real time and immediately get results back. Flask

itself does not come with an interactive shell, because it does not require any speciﬁc

setup upfront, just import your application and start playing around.

There are however some handy helpers to make playing around in the shell a more

pleasant experience. The main issue with interactive console sessions is that you’re

not triggering a request like a browser does which means that g, request and others

are not available. But the code you want to test might depend on them, so what can

you do?

This is where some helper functions come in handy. Keep in mind however that these

functions are not only there for interactive shell usage, but also for unittesting and

other situations that require a faked request context.

Generally it’s recommended that you read the The Request Context chapter of the doc-

umentation ﬁrst.

17.1 Creating a Request Context

The easiest way to create a proper request context from the shell is by using the

test_request_context method which creates us a RequestContext:

>>> ctx = app.test_request_context()

Normally you would use the with statement to make this request object active, but in

the shell it’s easier to use the push() and pop() methods by hand:

>>> ctx.push()

From that point onwards you can work with the request object until you call pop:

>>> ctx.pop()

17.2 Firing Before/After Request

By just creating a request context, you still don’t have run the code that is normally

run before a request. This might result in your database being unavailable if you are

connecting to the database in a before-request callback or the current user not being

stored on the g object etc.

This however can easily be done yourself. Just call preprocess_request():

>>> ctx = app.test_request_context()

>>> ctx.push()

>>> app.preprocess_request()

Keep in mind that the preprocess_request() function might return a response object,

in that case just ignore it.

To shutdown a request, you need to trick a bit before the after request functions (trig-

gered by process_response()) operate on a response object:

>>> app.process_response(app.response_class())

>>> ctx.pop()

The functions registered as teardown_request() are automatically called when the

context is popped. So this is the perfect place to automatically tear down resources

that were needed by the request context (such as database connections).

17.3 Further Improving the Shell Experience

If you like the idea of experimenting in a shell, create yourself a module with stuff you

want to star import into your interactive session. There you could also deﬁne some

more helper methods for common things such as initializing the database, dropping

tables etc.

Just put them into a module (like shelltools and import from there):

>>> from shelltools import *

100

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