FAIR Tools Discoverer Backend

This repository contains the source code of the backend of the FAIR Tools Discoverer. The backend is composed of two parts: the database and the API. In addition, the repository contains the scripts to process the data in the Software Observatory and insert new entries suitable for the Tool Discoverer.

• The api directory contains the source code of the API.
• The database/prepare-data directory contains the scripts to process the data in the Software Observatory and insert new entries suitable for the Tool Discoverer. In addition, indexes for querying are created.
• The database/mongo-seed directory contains a Dockerfile to generate a docker image of the database for development purposes.

API

Usage

The API is available at https://fair-tool-discoverer.bsc.es/api. The endpoints of the API are descibed in the Documentation.

Development

The API is developed using Python and the FastAPI framework.

Native installation

To install the API locally, it is recommended to use a virtual environment. The following commands install the API in a virtual environment and run it:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload

The database connection details are set through environment variables:

Parameter	Description
MONGO_HOST	Host of the database
MONGO_PORT	Port of the database
MONGO_USER	User of the database
MONGO_PWD	Password of the database
MONGO_AUTH_SRC	Name of the authentication database
MONGO_DB	Name of the database
DISCOV_COLLECTION	Name of the collection where the metadata for the discoverer is stored
RESULTS_COLLECTION	Name of the collection where the results of the queries are stored

Docker installation

The API is available as a Docker image at Docker Hub. The following command runs the API in a Docker container:

docker run -d -p 8000:8000 --env-file .env -v /path/to/host/log/directory:/app/logs/ emartps/tools-discoverer-api:latest 

The environment variables are set in the .env file. The following is an example of the content of the file:

MONGO_HOST=mongo
MONGO_PORT=27017
MONGO_USER=tools-discoverer
MONGO_PWD=tools-discoverer
MONGO_AUTH_SRC=admin
MONGO_DB=tools-discoverer
DISCOV_COLLECTION=discoverer
RESULTS_COLLECTION=results

The API logs are stored in the /app/logs directory. The directory is mounted as a volume in the container.

Using a mock database in a Docker and docker-compose

The API can be run with a mock database in a Docker container. The mock database is generated from the data in the Software Observatory. A seed database for development purposes can be build with the Dockerfile in database/mongo-seed.

The file docker-compose-dev.yml contains the definition of the development environment. It contains all the necessary services for development, which are the following:

CI/CD

The deployment is done through GitHub Actions. The file github/worflows.main.yml contains the definition of the workflow. The workflow is triggered manually. The workflow performs the following steps:

• 1. Build of the docker images of the API application.
• 2. Push of the images to the Docker Hub.