Project structure practice
After cloning/downloading the repository, simply install dash-practice as a package into your target virtual environment:
$ pip install PATH_TO_dash_practice
During development you will likely want to perform an editable install so that changes to the source code take immediate effect on the installed package.
$ pip install -e PATH_TO_dash_practice
This project comes with two convenience scripts for running your project in development and production environments, or you can use your own WSGI server to run the app.
Installing this package into your virtualenv will result into the development
executable being installed into your path when the virtualenv is activated. This
command invokes your Dash app's run_server
method, which in turn uses the
Flask development server to run your app. The command is invoked as follows,
with proj_slug
being replaced by the value provided for this cookiecutter
parameter.
$ run-project_slug-dev
The script takes a couple of arguments optional parameters, which you can
discover with the --help
flag. You may need to set the port using the --port
parameter. If you need to expose your app outside your local machine, you will
want to set --host 0.0.0.0
.
While convenient, the development webserver should not be used in
production. Installing this package will also result in a production executable
being installed in your virtualenv. This is a wrapper around the
mod_wsgi-express
command, which streamlines use of the mod_wsgi Apache
module to run your your app. In addition to
installing the mod_wsgi
Python package, you will need to have installed
Apache. See installation instructions in the mod_wsgi
documentation. This script also takes a
range of command line arguments, which can be discovered with the --help
flag.
$ run-project_slug-prod
This script will also apply settings found in the module dash_practice.prod_settings
(or a custom Python file supplied
with the --settings
flag) and which takes precedence over the same settings
found in dash_practice.settings
.
A notable advantage of using mod_wsgi
over other WSGI servers is that we do
not need to configure and run a web server separate to the WSGI server. When
using other WSGI servers (such as Gunicorn or uWSGI), you do not want to expose
them directly to web requests from the outside world for two reasons: 1)
incoming requests will not be buffered, exposing you to potential denial of
service attacks, and 2) you will be serving your static assets via Dash's Flask
instance, which is slow. The production script uses mod_wsgi-express
to spin
up an Apache process (separate to any process already running and listening on
port 80) that will buffer requests, passing them off to the worker processes
running your app, and will also set up the Apache instance to serve your static
assets much faster than would be the case through the Python worker processes.
Note: You will need to reinstall this package in order for changes to the
run-dash_practice-prod
script to take effect even if you
installed its an editable install with (ie pip install -e
).
You can easily run your app using a WSGI server of your choice (such as Gunicorn
for example) with the dash_practice.wsgi
entry point
(defined in wsgi.py
) like so:
$ gunicorn dash_practice.wsgi
Note: if you want to enable Dash's debug mode while running with a WSGI server,
you'll need to export the DASH_DEBUG
environment variable to true
. See the
Dev Tools section of the Dash Docs for more
details.