Terraso Backend

Terraso backend is a Django project that powers the backend of the Terraso platform.

Requirements

• Docker: version 24 or better
• Python: 3.12 or better

Running locally with Docker

Set up your environment file

sh $ cp .env.sample .env

In the .env file

• set values for GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRETbased on what you have set up in console.cloud.google.com > APIs & Services > Credentials.

• set values for APPLE_CLIENT_ID, APPLE_KEY_ID, APPLE_TEAM_ID, APPLE_PRIVATE_KEY and based on what you have set up on developer.apple.com > Certificates, Identifiers & Profiles > Keys.

• set values for MICROSOFT_CLIENT_ID and either MICROSOFT_CLIENT_SECRET (less secure) or both MICROSOFT_PRIVATE_KEY and MICROSOFT_CERTIFICATE_THUMBPRINT based on what you have set up on portal.azure.com > App Registrations > [App Name] > Certificates & Secrets

Start building the Docker images (make sure there's requirements.txt file created before building the images):

sh $ make build

Run the database migrations before the first run:

sh $ make migrate

Than the run command can be executed:

sh $ make run

If you want to have a user to access the admin panel, you need to create it:

```sh $ make bash

(inside the web container)

$ python terraso_backend/manage.py createsuperuser $ exit ```

Debugging locally with Docker

To debug while running tests, just use regular Python breakpoint() and run the tests normally. Pytest will stop properly on break point giving you access to the Python debugger.

To debug while using the application locally, it's also possible to use Python breakpoint(). To have access to the Python debugger, you'll need to attach to the application running container.

So, assuming that the application is running with make run:

List the running containers

sh $ docker ps

Get the id of the web container before next step

sh $ docker attach <web-container-id>

This will give you access to the web running container

Make the application request call that will pass on breakpoint, like calling an API or clicking in some button. As soon as the process get to the break point, the attached shell should open the Python debugger. To continue the application request processing, just release the debugger.

Interacting with the database

Connect to the database

While the database is running (e.g. via make run), use:

sh make connect_db

Run or rollback a specific migration

You can tell the database to migrate a specific app to a specific number with:

sh APP_MIGRATION_NAME="{app_name} {migration_number}" make migrate

So to e.g. rollback migration 0014 of the soil_id app, you could run:

sh APP_MIGRATION_NAME="soil_id 0014" make migrate

Loading sample data

Import sample landscape data (names, descriptions, links):

sh $ python terraso_backend/manage.py loaddata sampledata.json

Import landscape boundaries geodata:

sh $ python terraso_backend/manage.py load_landscapes_geojson --airtable_api_key xxxxx

Download Soil ID data:

sh $ make download-soil-data

Reset the database

You can reset the database back to its default state:

sh $ python terraso_backend/manage.py flush

Backup the database

The contents of the database can be dumped to a JSON file for backup. Optionally, they can also be uploaded to a S3 bucket. This can be activated to be triggered from a button in the Django admin console. See the relevant README.md for more details.

Print migration SQL

You can view the SQL commands that a migration will issue by running

sh $ python terraso_backend/manage.py sqlmigrate {app_name} {migration_name}

or in Docker using the make command

sh $ APP_MIGRATION_NAME="{app_name} {migration_name}" make print_migration_sql

For example:

sh $ APP_MIGRATION_NAME="story_map 0001_initial" make print_migration_sql

Contributing

Before contributing to the project, it's recommended that you set up your local git running the following command:

sh $ make setup-git-hooks

This will activate two git hooks to automatically check Python code style and commit message structure before each commit.

Dealing with dependencies

It is possible to lock the dependencies to run the project with the following command

sh $ make lock

It is also possible to lock development dependencies with:

sh $ make lock-dev

The lock process creates/updates the files requirements.txt and requirements-dev.txt. With these files in place it's possible to install dependencies running:

sh $ make install

To install development dependencies run:

sh $ make install-dev

Local development

Your local machine needs:

• Docker
• Python

make lock requires GDAL and Cython:

sh $ brew install gdal

sh $ apt install gdal

cython

sh $ pip3 install cython

Generating GraphQL public documentation

The API docs are generated by SpectaQL. So, make sure you followed their README to have it installed before proceding. Run the following command to generate the documentation:

sh $ make api_doc

Enjoy! ;-)