Installation: lookit-api (Django project)¶

lookit-api is the codebase for Experimenter and Lookit, excluding the actual studies themselves. Any functionality you see as a researcher or a participant (e.g., signing up, adding a child, editing or deploying a study, downloading data) is part of the lookit-api repo. This project is built using Django and PostgreSQL. (The studies themselves use Ember.js; see Ember portion of codebase, ember-lookit-frameplayer.), It was initially developed by the Center for Open Science.

If you install only the lookit-api project locally, you will be able to edit any functionality that does not require actual study participation. For instance, you could contribute an improvement to how studies are displayed to participants or create a new CSV format for downloading data as a researcher.

Note

These instructions are for Mac OS. Installing on another OS? Please consider documenting the exact steps you take and submitting a PR to the lookit-api repo to update the documentation! For notes on Linux installation, there may be helpful information in a previous version of invoke tasks.py.

Django¶

These instructions will get walk you through the installation and running of the Django’s local envionment.

Install Homebrew. Run update and upgrade:
```
brew update && brew upgrade
```
Install Docker and make sure it’s running.
Install Git and Poetry:
```
brew install git poetry
```
Change directory to where you want the project to live. Next, clone repo and change directory.
```
git clone git@github.com:lookit/lookit-api.git
cd lookit-api
```

Set Poetry’s Python and install Python packages:

poetry env use python3.9
poetry run pip -U pip wheel setuptools
poetry install

Create database and run setup script:
```
poetry run invoke create-db setup
```
This will create a local .env file with environment variables for local development, run the Django application’s database migrations (“catching up” on changes to the database structure) and create local SSL certificates. If you’re curious about what exactly is happening during this step, or run into any problems, you can reference the file tasks.py.
Run local environment server:
```
poetry run ./manage.py runserver
```
Navigate to local environment at http://localhost:8000.

Rabbitmq¶

These instructions will have you create and start a RabbitMQ image in Docker.

Install and start rabbitmq via docker:

docker run -d --name lookit-rabbit --env-file .env -p 5672:5672 rabbitmq:3.8.16-management-alpine
docker cp ./rabbitmq.sh lookit-rabbit:/rabbitmq.sh
docker exec -it lookit-rabbit /bin/sh -c "sh /rabbitmq.sh"

Postgres¶

This is covered above, but as sometimes databases can be ephemeral during development I felt that it deserved its own section.

Create a Postgres database using the following command:

poetry run create-db

To reset the database:

poetry run reset-db

To reset the database and load an existing sql data file:

poetry run reset-db -s /location/of/sql/file

Create Superuser¶

You can create a user through UI or if you’d rather have Superuser access you can create a user with the manage script.

Create a superuser by running:

poetry run ./manage.py createsuperuser

Now you should be ready for anything. Going forward, you can run the server using the directions below.

Running the server¶

Again, this is covered above, but there is a case you’d need to run the development server with SSL. This section will cover both variants.

To run the Lookit server locally, run:

poetry run ./manage.py runserver

Or to use the invoke script:

poetry run invoke server

Now you can go to http://localhost:8000 to see your local Lookit server! You should be able to log in using the superuser credentials you created during setup.

To view the HTTPS version of the local development add the https argument to the above command:

poetry run invoke server --https

If you are not working extensively with lookit-api - i.e., if you just want to make some new frames - you do not need to run celery, rabbitmq, or docker. For more information about these services and how they interact, please see the Contributing guidelines.

Celery¶

You should already have a rabbitmq server installed and running. You can check this by:

docker ps -f name=lookit-rabbit

If rabbitmq is not running, you can start it using:

docker start lookit-rabbit

Then use the invoke command to start the celery worker:

poetry run invoke celery-service

Authentication¶

You can create participant and researcher accounts through the regular signup flow on your local instance. To access Experimenter you will need to add two-factor authentication to your account following the prompts. In order to access the admin interface (https://localhost:8000/__CTRL__), which provides a convenient way to access and edit records, you will need to log in using the superuser you created earlier using manage.py.

Handling video¶

This project includes an incoming webhook handler for an event generated by the Pipe video recording service used by ember-lookit-frameplayer when video is transferred to our S3 storage. This requires a webhook key for authentication. It can be generated via our Pipe account and, for local testing, stored in .env under PIPE_WEBHOOK_KEY.

Pipe needs to be told where to send the webhook. First, you need to expose your local /exp/renamevideo hook. You can use Ngrok to generate a public URL for your local instance during testing:

ngrok http https://localhost:8000

Then, based on the the assigned URL, you will need to manually edit the webhook on the dev environment of Pipe to send the video_copied_s3 event to (for example) https://8b48ad70.ngrok.io/exp/renamevideo/.

Common Issues¶

During installation, you may see the following:

psql: FATAL:  role "postgres" does not exist

To fix, run something like the following from your home directory:

$../../../usr/local/Cellar/postgresql/9.6.3/bin/createuser -s postgres

If your version of postgres is different than 9.6.3, replace with the correct version above. Running this command should be a one-time thing.