PyJS DJ Skeletor

In addition to DJ Skeletor, it has support for pyjs (it's simple hello-world pyjs application).

USAGE: make pyjs-prod or: make pyjs-debug

will compile pyjs files into staticfiles/output

DJ Skeletor

DJ Skeletor is a skeleton Django project handy for quick bootstrapping of new empty Django projects. It will help you get up and running with your project in seconds.

The repository contains an empty, relocatable Django project with a selection of useful Django application and setup for development, production and (automated) test settings and environments.

Quickstart

# prepare the virtual environment
mkvirtualenv --no-site-packages myenv

# get the skeleton project
git clone https://github.com/senko/dj-skeletor.git myproject
cd myproject

# set up the development environment
make dev-setup

# run your fully operational Django project
python manage.py runserver_plus

Batteries included

The development environment by default includes:

• South for database migrations (both development and production use it)
• Django Debug Toolbar for displaying extra information about view execution
• SQLite database (dev.db in the project root directory)
• Integrated view debugger making it easy to debug crashes directly from the browser (Werkzeug and django-extension's runserver_plus)
• Full SQL statement logging
• Beefed-up Django shell with model auto-loading and IPython REPL
• Flake8 source code checker (style, passive code analysis)
• Console E-mail backend set by default in dev for simple E-mail send testing
• Automated testing all set-up with nose, optionally creating test coverage reports, and using the in-memory SQLite database (and disabled South) to speed up test execution
• Disabled cache for easier debugging

The production environment by default includes:

• South for database migrations (both development and production use it)
• Gunicorn integration
• Django Compressor for CSS/JS asset minification and compilation
• Database auto-discovery via environment settings, compatible with Heroku
• Sentry client (raven_compat) for exception logging (used only if SENTRY_DSN variable is set in settings or environment)
• Local-memory cache (although memcached is strongly recommended if available)

The extended tour

After setting up your new Django project (see Quickstart above), try these:

# make sure all tests pass (you'll need to write them first, though :)
make test

# get a test coverage report (outputs to stdout, saves HTML format in
# cover/index.html and produces Cobertura report compatible with Jenkins)
make coverage

# clean up test artifacts, *.pyc files and cached compressed assets
make clean

# check if the code follows PEP8 and is free of obvious errors
# this also includes cyclomatic complexity check and will complain if your
# code is too complex (configurable by editing the Makefile)
make lint

# update the environment (eg. after pulling in new code)
make dev-update

# open up the new and improved Django shell
python manage.py shell_plus

Yearn for more? Django-extension comes with tons of useful management commands, run python manage.py help to get an overview.

The production setup

The production environment can't be set up automatically (at it may require setting up databaes details and other per-server settings manually), but there are some helper Makefile tasks to speed it up.

To set up the production environment for a DJ Skeletor-powered project, loosely follow this procedure:

# prepare the virtual environment
mkvirtualenv --no-site-packages myenv

# get your project
git clone <myproject-url>
cd myproject

# install the requirements
make reqs/prod

# create a project/settings/local.py settings file with per-server config
vim project/settings/local.py

# run automatic update (db sync/migrations, collectstatic)
make prod-update

# your production environment is now ready
python manage.py run_gunicorn

Of course, your mileage may vary.

The settings files

The settings files base (base settings used in all environments), prod (production settings), dev (local development settings) and test (settings used when running automated tests) should contain only the settings used by all developers/servers.

Per-server (or per-developer) settings should go into local module (ie. project/settings/local.py). The usual pattern for this module is to first import everything from the settings variant that best matches your environment (prod for servers, dev for local development), and then override/add settings as needed.

Example production settings just specifying the production database:

# file: project/settings/local.py
from .prod import *

DATABASES = {
    'default': { ... }
}

You shouldn't need to add local.py to the repository (in fact, git is already set up to ignore it). If some setting needs to be shared by everyone, it should probably be added to base, dev or prod.

The local settings file isn't required. If it doesn't exist, the production setup will be used by default. This is useful if you don't have per-server settings or they're deployed via Unix environment (as they are on eg. Heroku and similar cloud hosting providers).

Environment settings

In either production or develoment mode, settings can also be set via the environment variables. The following variables are supported:

• DATABASE_URL - Heroku-compatible database URL
• DEBUG - String true enables DEBUG, any other disables
• TEMPLATE_DEBUG - String true enables TEMPLATE_DEBUG, any other disables
• COMPRESS_ENABLED - String true enables django-compressor, any other disables
• SQL_DEBUG - String true enables SQL statement logging, any other disables (disabled by default, available only if using dev.py)
• CACHE_BACKEND - String value to put into CACHES['default']['BACKEND']
• EMAIL_BACKEND - String value for EMAIL_BACKEND (only if using dev.py)

Note that values from local.py override environment settings! You probably want to use either the local settings file or the environment settings, not mix them.

Heroku support

The production setup uses database autodiscovery so if you have a (promoted) database in Heroku, it will automatically get picked up.

For Heroku, you'll probably want to add the Procfile file with contents similar to this:

web: python manage.py run_gunicorn --workers=4 --bind=0.0.0.0:$PORT

If your web app supports uploading of media (eg. images, videos or other files) by users, you'll probably need the django-storages app to automatically host them somewhere else (eg on Amazon S3). When django-storages is set up, the collecstatic management command (run as part of make prod-update) will copy the static assets to the specified service as well.

After pushing the new code to Heroku for update, you should make sure to run all the needed management commands to migrate the database, etc:

heroku run make prod-update

Django Debug Toolbar

Django Debug Toolbar is set up so it's always visible in the dev environment, no matter what the client IP is, and always hidden in the production environment.

Sentry / Raven

To use the Sentry client, you'll need a server to point it to. Installing Sentry server is easy as:

# mkvirtualenv --no-site-packages sentry-env
# pip install sentry
# sentry init
# sentry start

You'll want to install Sentry into its own environment as it requires Django 1.2 or 1.3 at the moment.

If you don't want to install Sentry yourself, you can use a hosted version at http://getsentry.com/.

When you connect to your (or hosted) Sentry server and create a new project there, you'll be given Sentry DSN which you need to put into production settings to activate Sentry exception logging.

Compressor

Django Compressor can minify and compile your CSS and JS assets. DJ Skeletor comes with Compressor support, but to make use of it, you need to use {% compress %} tags in your templates.

By default Compressor runs in online mode, and files are compressed and cached (if needed) when the template that uses them is first served. Optionally, it can also use offline mode (COMPRESSOR_OFFLINE) in which the static files are pre-compressed in deployment phase. To activate this, you'll need to activate the COMPRESSOR_OFFLINE setting (it's commented out in settings/prod.py by default) and update Makefile to run the compressor in the deployment phase.

Note that if you enable offline mode, you will need to run compress after every template or static file change, so it's recommended to only use it for deployed/production environments.

Test code coverage

DJ Skeletor comes with support for nose test runner and code coverage reporting through coverage.py.

To run a normal test without code coverage report, run make test.

To run a test with a coverage report, run make coverage. The report is generated in HTML format in the cover/ subdirectory, and in the Cobertura format in coverage.xml file (useful for integrating with Continuous Integration systems, such as Jenkins). The test run also produces nosetests.xml file in the standard JUnit format, also useful for integration with Jenkins or other CI systems.

Deployments via git

If deployments are done via git (and not fabric, see below), it's recommended to create another Makefile target that will do the deploy, for example:

deploy:
  git pull
  $(MAKE) update
  # command to restart the service(s) as neccessary

Fabric

A fabfile is provided with common tasks for rsyncing local directory to the server for use while developing the project, and for deploying the project using git clone/pull.

Useful commands:

• server - host to connect to (same as -H, but accepts only one argument)
• env - virtualenv name on the server, as used with virtualenvwrapper/workon
• project_path - full path to the project directory on the server
• rsync - use rsync to copy the local folder to the project directory on the server
• setup - set up the project instance on the server (clones the origin repository, creates a virtual environment, initialises the database and runs the tests)
• deploy - deploy a new version of project on the server using git pull
• collecstatic, syncdb, migrate, runserver - run manage.py command
• update - combines collecstatic, syncdb, migrate
• test - run manage.py test with the test settings enabled

For all the commands, run 'fab -l' or look at the source.

Examples:

Copy local directory to the server, update database and static files, and run tests (only files changed from last copy are going to be copied):

fab server:my.server.com env:myenv project_path:/path/to/project rsync update test

Deploy a new instance of a project on a server ('myenv' will be newly created, code will be cloned into /path/to/project):

fab server:my.server.com env:myenv project_path:/path/to/project \
    setup:origin=http://github.com/senko/dj-skeletor

Deploy a new version of the project on the server (a new git tag will be created for each deployment, so it's easy to roll-back if needed):

fab server:my.server.com env:myenv project_path:/path/to/project deploy

Customization

Everyone has a slightly different workflow, so you'll probably want to customize the default fabric tasks or combine them. You can either customize fabfile.py and commit the changes to your repository, or you can create local_fabfile.py, which will be loaded if it exists. The latter can be useful if you have per-team-member fabric customizations you don't want to commit to the repository.

Renaming the project

By default, DJ Skeletor names the project project, so it's generic enough to not requiring the change for each project, so the initial setup is a bit faster (and the manage.py logic is simpler).

If you do want to change the project name though, there's couple of things you need to do. For example, if you want to rename the project to foo:

• rename the folder: git mv project foo
• update Makefile, manage.py and˛fabfile to set PROJECT_NAME to foo
• commit the changes to your git repository and you're done!