This is a proof of concept for Wagtail and Whatsapp integration, based on the Wagtail Bakery demo.
Document contents
- Python 3.4, 3.5 or 3.6
- Virtualenv
- VirtualenvWrapper (optional)
With PIP and virtualenvwrapper installed, run:
mkvirtualenv wagtail-whatsapp-poc --python=python3.6
python --version
Now we're ready to set up the project itself:
cd ~/dev [or your preferred dev directory]
git clone https://github.com/wagtail/wagtail-whatsapp-poc.git
cd wagtail-whatsapp-poc
pip install -r requirements/base.txt
Next, we'll set up our local environment variables. We use django-dotenv
to help with this. It reads environment variables located in a file name .env in the top level directory of the project. The only variable we need to start is DJANGO_SETTINGS_MODULE:
$ cp bakerydemo/settings/local.py.example bakerydemo/settings/local.py
$ echo "DJANGO_SETTINGS_MODULE=bakerydemo.settings.local" > .env
To set up your database and load initial data, run the following commands:
./manage.py migrate
./manage.py load_initial_data
./manage.py runserver
Log into the admin with the credentials admin / changeme.
You can deploy a demo site to a publicly accessible server with Heroku's one-click deployment solution to their free 'Hobby' tier:
If you do not have a Heroku account, clicking the above button will walk you through the steps
to generate one. At this point you will be presented with a screen to configure your app. For our purposes,
we will accept all of the defaults and click Deploy. The status of the deployment will dynamically
update in the browser. Once finished, click View to see the public site.
Log into the admin with the credentials admin / changeme.
To prevent the demo site from regenerating a new Django SECRET_KEY each time Heroku restarts your site, you should set
a DJANGO_SECRET_KEY environment variable in Heroku using the web interace or the CLI. If using the CLI, you can set a SECRET_KEY like so:
heroku config:set DJANGO_SECRET_KEY=changeme
To learn more about Heroku, read Deploying Python and Django Apps on Heroku.
If you have deployed the demo site to Heroku or via Docker, you may want to perform some additional setup. Heroku uses an ephemeral filesystem, and Docker-based hosting environments typically work in the same manner. In laymen's terms, this means that uploaded images will disappear at a minimum of once per day, and on each application deployment. To mitigate this, you can host your media on S3.
This documentation assumes that you have an AWS account, an IAM user, and a properly configured S3 bucket. These topics are outside of the scope of this documentation; the following blog post will walk you through those steps.
This demo site comes preconfigured with a production settings file that will enable S3 for uploaded media storage if
AWS_STORAGE_BUCKET_NAME is defined in the shell environment. All you need to do is set the following environment
variables. If using Heroku, you will first need to install and configure the Heroku CLI. Then, execute the following commands to set the aforementioned environment variables:
heroku config:set AWS_STORAGE_BUCKET_NAME=changeme
heroku config:set AWS_ACCESS_KEY_ID=changeme
heroku config:set AWS_SECRET_ACCESS_KEY=changeme
Do not forget to replace the changeme with the actual values for your AWS account. If you're using a different hosting
environment, set the same environment variables there using the method appropriate for your environment.
Once Heroku restarts your application or your Docker container is refreshed, you should have persistent media storage!
To copy the initial data included with this demo to the S3 bucket (assuming you ran ./manage.py load_initial_data per
the above), you can use the AWS CLI included with the requirements:
heroku run aws s3 sync bakerydemo/media/original_images/ s3://<bucket-name>/original_images/
Because we can't (easily) use ElasticSearch for this demo, we use Wagtail's native DB search.
However, native DB search can't search specific fields in our models on a generalized Page query.
So for demo purposes ONLY, we hard-code the model names we want to search into search.views, which is
not ideal. In production, use ElasticSearch and a simplified search query, per
http://docs.wagtail.io/en/v1.13.1/topics/search/searching.html.