moccapi

Repository containing the API server.

PyCharm w/Django

To configure everything so that stuff works properly, do the following:

1. Open settings
2. Go to Languages and frameworks
3. Select Django
4. Configure the settings according to the image below
5. ???
6. Profit

To run the Django application, once you've configured it all you need to do is select the Configuration button in the top right, select Edit configurations, press the + sign in the upper left corner, select Django Server and press OK. While developing you'll frequently need to run managy.py commands. You'll find this console at Run manage.py Task... in the Tools menu.

Initial setup

Initially, you need to create a migration for each app by specifically running makemigrations <app_name> in the manage.py console, but once the initial migration has been made, you only need to write makemigrations to create all the migrations at once. Currently, we have the following applications configured in Django:

• brew
• coffee
• django_celery_results (used for async storing of results)

Developing

NOTE: You need to tell the Django instance that is in debug mode, the easiest way to run the server is with the devserver.sh file, or by setting the environment variable DEBUG to 1. On any unix system you do this by writing export DEBUG=1 in your terminal, or you could configure it from your settings inside PyCharm.

Once you've run the initial (or subsequent) makemigrations, you can update the database tables by running migrate. Next up you should probably import some fixtures so you have some data to work with, you can do this with loaddata api in the manage.py console. Now you can start the application and go to localhost:8000/api/v1/coffee/ to view it. For a view of the Swagger documentation go to localhost:8000/api/v1/swagger/.

Code quality

To ensure that the code meets some standard of quality, we're using Flake8, Black and isort to maintain a consistent standard. For development, to ensure that everything is up to date, run the following commands:

• black . to format all Python code.
• isort --recursive . to sort imports.
• flake8 to check for style warnings, errors etc.
• python manage.py test to run tests.

Reading from the Arduino

There is a separate application for reading from the Arduino in the sensors folder, if you want to read some data from the Arduino you can run it from a terminal and get a single reading from the sensors.

from sensors.arduino import Arduino
arduino = Arduino()

And then read from the Arduino.

arduino.read()
# ('2122.39', '26.31')

Using Celery

We are using Celery for asynchronously being able to query the Arduino and add the results to the database. For this you need to have RabbitMQ installed as it is our broker, then to actually run Celery and RabbitMQ you need to run the following two commands in two separate terminal windows:

1. rabbitmq-server
2. celery -A moccapi worker -l info -B

While you are running the application you'll see the results of the asynchronous queries that are run every few seconds in the celery terminal window:

[2019-03-01 11:57:15,566: INFO/MainProcess] Received task: sensors.tasks.read[58b27a8f-1e9d-4bb2-9118-b4896be2ed3f]
[2019-03-01 11:57:17,394: INFO/ForkPoolWorker-8] Task sensors.tasks.read[58b27a8f-1e9d-4bb2-9118-b4896be2ed3f] succeeded in 1.8236205450000043s: ('2111.73', '23.27')

Logging

The logger logs debug messages to debug.log.

Currently logs the readings from the Arduino, when it's creating a new brew and the old one if not.