User-engagement

Python project to provide data analysis and insights from website users, using FastAPI.

Run

docker compose

The easiest and most straightforward way to run this is through docker-compose.

First install Docker and docker-compose. You can find instructions on www.docker.com and https://docs.docker.com/compose/install/. The version used to test this code is docker 27.2.0.

After having installed Docker, you need to create a .env file in the root folder of the API with the following content:

POSTGRES_USER=<username>
POSTGRES_PASSWORD=<password>
POSTGRES_DB=<db_name>
POSTGRES_PORT=5432
POSTGRES_HOST=postgres
TEST_POSTGRES_USER=test
TEST_POSTGRES_PASSWORD=test
TEST_POSTGRES_DB=test
TEST_POSTGRES_PORT=5432
TEST_POSTGRES_HOST=postgres_test

and then run docker compose up in your terminal. The API will then be accessible at http://0.0.0.0:80/docs in your browser. To close the API, press command/ctrl+c in the same terminal, and type docker compose down.

Local

To run it locally (not recommended), you should first set up a database container. When this is set up, and you have saved your environment variables in a .env file in the root folder, you proceed with the installation guide for the API, and finally run it.

Database

The database is run with PostgreSQL.

you can download the latest PostgreSQL image by typing

docker pull postgres

in your terminal.

You can then build the database image to a docker container. Create an empty .env file in the root folder and write

POSTGRES_HOST=localhost
POSTGRES_USER=<username>
POSTGRES_PASSWORD=<password>
POSTGRES_DB=<db_name>

Then, build your image and run the container by typing the following instructions in the terminal in the same folder

docker build -t postgres-img -f Dockerfile_db .

docker run -d --name postgres-cont --env-file .env -p 5432:5432 postgres-img

If you're already using the 5432 port for something, it might throw an error. You can then try and use another port. If everything worked, you should be able to see two empty tables called "activities" and "users" in the database. You can do this by typing

docker exec -it postgres-cont psql -U <username> -d <db_name>

and then typing

\dt

you should obtain something like

            List of relations
 Schema |    Name    | Type  |   Owner
--------+------------+-------+-----------
 public | activities | table | <username>
 public | users      | table | <username>

Install API locally

This package was coded using Python3.12.7. Check on https://www.python.org/downloads/ how to install Python on your operative system.

It is easier to install all dependencies with poetry.

First, install poetry with

pipx install poetry (or use pip if you want to work in a virtual environment). The installation was performed with poetry version 1.8.3, and this or later versions should work. If not, one may install precisely this version using

pipx install poetry==1.8.3.

Then, go to the main folder, and install all the dependencies using

poetry install.

Run

You run the code locally by typing in a terminal window

fastapi run src/application.py --port 80

and then visit http://0.0.0.0:80/docs on your browser.