Assxios / FINNY_DAH

Finny's do at home project

✨ FINNY AI DO-AT-HOME Project ✨

Project Overview

This project is a web-based word counting application that processes URLs to count the words on the corresponding web page. The application stack consists of a Flask backend, a MongoDB database, a Redis cache, and RQ for task queueing.

All the installed images, libraries, etc have a specific version to avoid any compatibility issues.

Installation

To use the FINNY AI DAT project, follow these steps:

git clone https://github.com/Assxios/FINNY_DAH.git
cd FINNY_DAH

Running the Application

To run the application, use the following command:

docker compose --profile default up

The application will be available at http://localhost:3000. You can also access two dashboards:

• Mongo Express: http://localhost:8081
• RQ Dashboard: http://localhost:3000/rq

The following endpoints are available (on http://localhost:3000):

• GET /: The home page of the application.
• POST /api/job: Submit a URL to be processed.
• GET /api/job/<job_id>: View the results of the word count for a job.

Running the Tests

If you want to run the tests, use the following command:

docker compose --profile test up

Cleaning Up

To clean up the application, use the following command:

docker compose --profile default down -v
docker system prune -af

You should replace default with test if you are cleaning up the test environment.

Documentation

Python Libraries

• Flask: A micro web framework for Python.
• pymongo: A Python driver for MongoDB.
• flask-cors: A Flask extension for handling Cross-Origin Resource Sharing (CORS).
• rq: A simple Python library for queueing jobs and processing them in the background with workers.
• redis: A Python client for Redis.
• requests: A Python library for making HTTP requests.
• rq-dashboard: A web-based dashboard for monitoring RQ queues.
• pytest: A testing framework for Python.
• pytest-flask: A Pytest plugin for testing Flask applications.

Made with ❤️ by:

Assxios (droge)