ArtBook

Art catalog in Python, using Flask and Neo4J.

This is a personal project, mainly focused on learning technologies, aiming to build an API for a catalog of arts and artists, on the Flask Framework, with persistence in a Neo4J graph database. The application structure seeks an approach that adheres to the concepts of Domain Driven Design, with a hexagonal architecture.

Work In Progress - It documents a learning process

Starting

Prerequisites

Before starting, you will need to have the following tools installed on your machine:

• Git
• Docker
• Docker Compose

Installation (Local Development)

# Clone this repository
$ git clone https://github.com/rahenrique/artbook-neo4j.git

# Run the application in development mode using the embedded server
$ make init

# If necessary, edit the .env file (based on the .env.example file)
$ nano app/.env

The Flask server will start on port:5000 in development mode. Any source code changes will automatically reflect in the running application.

Acess:

• API Docs (Swagger): http://0.0.0.0:5000/
• App: http://0.0.0.0:5000/api/artists/
• Neo4jBrowser: http://localhost:7474/browser/

Optionally, it is possible to run the application using Gunicorn. Just force the use of docker-compose.yml file without overrides

$ docker-compose -f docker-compose.yml up -d

The Gunicorn server will start at port:8080. In this way, the application will not automatically reload after source code changes. Acess:

• App: http://localhost:8080/api/artists/

Running tests

To run the initial seed of the database, use the following command:

$ make db-seed

To run the tests, from your terminal (on your local machine), run the following command:

$ make test

Other useful commands during development can be consulted using:

$ make help

Built With

• Flask
• Flask-RESTX
• pytest
• Neo4j
• nginx