Issues you can help with right now:
Slides of a talk I gave about importd: http://amitu.com/importd/
Django is awesome, but starting a new project in it is a pain. importd is inspired from ruby's sinatra. Hello world django project:
from importd import d
d(DEBUG=True)
@d("/")
def idx(request):
return "index.html"
@d("/post/<int:post_id>/")
def post(request, post_id):
return "post.html", {"post_id": post_id}
if __name__ == "__main__":
d.main()
To run it:
$ python foo.py
This will start the debug server.
To run it in production:
$ gunicorn foo:d
- Simple example : https://github.com/amitu/importd/tree/master/examples
- importd-boilerplate : https://github.com/if1live/importd-boilerplate
- importd + jinja2 + django-debug-toolbar + django REST framework
Managing settings in django is done via a settings.py file. Then people put a
local_settings.py
to override. This does not scale too well, we end up
having very big settings file with almost no structure, and there are many
issues because of lack of synchronization of local_settings.py
among
developer's machines.
importd has some methods to hopefully make this simpler and more standardized.
First of all there is no local_settings.py
. Setting customization are of two
kinds, picking different things for development and prod, eg you want to
activate statsd for prod, but debug_toolbar for development. Both these should
be checked in so there is no scope of people not getting some setting
accidentally. Then there are setting customization for not storing some things
in version control system, say passwords and access tokens and keys. These
should be managed via environment variable.
And then there is also a concern of exposing settings to template. We have a template context processor, which can expost whole settings to templates, but that is uncomfortable to many. You may want to expose only a small subset of things you describe in settings, and you want to do this with minimal fuss.
With that in mind importd has env()
, which simply reads data from
enironment. So in your app.py you can do:
from importd import d, env
d(
DEBUG=not env("IS_PROD", False),
db=env("DB_URL", "mysql://root:@localhost/dbname")
)
It is highly recommended you include envdir
in your project. May be someday
importd will auto detect envdir and set it up.
env
is pretty smart, it takes default=
and factory=
. If default
is passed, the string value of environment variable is converted to the
type()
of default
. You can overwrite this behaviour by passing your own
factory
, or you can disable this behaviour altogether by passing
factory=importd.NotSet
.
env()
also treats booleans by converting strings like "False/off/no" (case
insensitive) to python's False
value (and non empty string to True as
bool()
does).
With .debug()
you can set some setting to have different values based on
DEBUG
.
from importd import d, debug
d(
DEBUG=not env("IS_PROD", False),
STATSD_CLIENT=debug(
'django_statsd.clients.toolbar', prod='django_statsd.clients.normal'
),
)
This will set STATSD_CLIENT
to appropriate value based on if we are in debug
mode or not. This is as simple as putting an if condition, but it gets repeated
so many times, its worth using this shortcut. Also this way things stay in same
place, you do not look for up and down the settings file, and in
local_settings.py to see if the variable has been overwritten.
This lets you "expose" a setting for access in templates. You should not use
"django.core.context_processors.settings"
as a
TEMPLATE_CONTEXT_PROCESSORS
, instead use "importd.esettings"
context
preprocessor, and in templates you will have access to esettings
variable.
To mark a variable as exposed you have to do this:
from importd import d, e
d(
DEBUG=True,
SOME_VAR=e("its value"),
)
This will make SOME_VAR
available in settings as well as in esettings
.
This lets you re-use settings variables. In settings file we define variables and reuse them when needed. In importd you can reuse defined settings variables.
This will set TEMPLATE_DEBUG
settings variable to DEBUG
value.
s
will raise ImproperlyConfiguredError
exception if you will try to use
it inside of key value.
Above example will raise ImproperlyConfiguredError
.
Some settings are only needed in debug environment, or need to be overwritten,
you can use the debug=
keyword argument to set things up.
from importd import d
d(
DEBUG=False,
SOME_VAR="this is prod value",
debug=dict(
SOME_VAR="this is debug value"
)
)
You can also use importd.NotSet as a value in debug dict, and the setting will be removed altogether in the approprite environment (debug or prod).
Above method will open envdir directory in current directory and will load all environment variable inside this directory. If path is realpath i.e. full path then importd will try to look into specified path. If relative path specified into path then importd will look relative to current directory.
It is recommended to call it just after importing d.
It is a common pattern that some apps are only needed in debug environment, say
devserver, or debug_toolbar. And since order of apps in INSTALLED_APPS
, and
middelware etc is important, we end up copying the whole INSTALLED_APPS
,
MIDDLEWARE_CLASSES
etc for prod and dev, and this then tend to diverge since
they are in different locations. Not good.
from importd import d, env
d(
DEBUG=env("IS_PROD", True),
INSTALLED_APPS=[
"django.contrib.contenttypes",
"django.contrib.auth",
"django.contrib.sessions",
"debug:devserver",
"debug:debug_toolbar",
"myapp"
]
)
Notice the debug:
prefix in devserver
and debug_toolbar
. Depending
on the value of DEBUG
, these lines would be included or not. importd looks
for strings in MIDDLEWARE_CLASSES
, INSTALLED_APPS
and
TEMPLATE_CONTEXT_PROCESSORS
.
Similarly if something starts with prod:
, it is only included in production
environment.
d.main()
used to be not required, now it is.
- fully compatible with django
- supports smarturls
- most of regularly used django functions and classes available in d. namespace, eg d.HttpResponse, d.render_to_response, d.get_object_or_404 etc
- automatically maps "templates" folder in foo.py directory to serve templates
- automatically maps "static" folder in foo.py to serve static content
- management commands still available: $ python foo.py shell
- wsgi compliant
- gunicorn support
- works seamlessly with fhurl (http://packages.python.org/fhurl/)
- Auto Add django-debug-toolbar (Needs to add it manually to INSTALLED_APPS)
- Auto SECRET_KEY: If no SECRET_KEY on settings, try to read SECRET_KEY from ./secret.txt , if no ./secret.txt generate a random string then write it to ./secret.txt and finally return it as SECRET_KEY.
- Auto Add coffin/django-jinja (jinja2 integration)
- Support for livereload
$ pip install importd
http://importd.readthedocs.org/en/latest/
https://github.com/amitu/importd/blob/master/ChangeLog.rst
- Amit Upadhyay (https://github.com/amitu)
- Dmytro Vorona (https://github.com/alendit)
- Jannis Leidel (https://twitter.com/jezdez)
- Lukasz Balcerzak (https://github.com/lukaszb)
- Juan Carlos (https://github.com/juancarlospaco)
- Josep Cugat (https://github.com/jcugat)
- Yu Byunghoo (https://github.com/if1live)
- Arpit Singh (https://github.com/arpitremarkable)
- Hitul Mistry (https://github.com/hitul007)
To view this file, or any restructuredtext file locally before comitting on git,
install restview
from pypi.
Pull Requests: If you fork this repository to send pull request, please create a branch for your work instead of working directly on master. This way your master will track my master, and in case the pull request is rejected, or delayed, your master stays clean. This also makes easy to send more than one pull requests from your fork.
- BSD