Deployment

This section is for what operations which are needed to make the software work on the users’ machine.

User Installation

Application can be run locally by cloning the GitHub repository or installing directly from PyPI. Two installation options supported:

  • From source (GitHub): for development and contribution

  • From PyPI: for production usage

  • app can be installed as Python package from PyPI using pip install aggfindata (after public deployment)

Requirements

  • Python 3.10 or higher
  • pip (Python package manager)
  • Git (optional, for cloning the repository)
  • make (optional but recommended for automation)
  • coverage.py (for code coverage during tests)

Installation Steps

Users can install the app either by cloning the repository or by installing the PyPI package (if published).

Option 1: Install from GitHub (development)

  1. Clone the repo: 
    git clone https://github.com/unibo-dtm-se-2324-AggFinData/artifact.git
cd artifact
  2. Install dependencies with pip install -r requirements.txt
  3. Set environment variables and run with flask run

Option 2: From PyPI (production install)

  1. Run: 
    pip install aggfindata

  2. Set environment variables (NEWS_API_KEY, etc.)

  3. Run app using: 
     python -m AggFin

Server-Side Installation

This app can also be deployed on a server or cloud platform(like: Render, Heroku, etc.).

  • You can automate setup through:
    • Makefile for Linux/macOS (includes install, test, check, run commands)
    • setup.ps1 for Windows PowerShell users

Requirements on the Server:

Python 3.x pip Gunicorn or similar WSGI server Optional: nginx as reverse proxy(HTTPS)

Developer Automation

To faster development and testing, the project includes automation scripts:

  • Makefile — defines commands:
    • make install → install dependencies
    • make test → run tests
    • make run → run the app
    • make check → check for syntax errors
  • setup.ps1 — a Windows PowerShell script with same purpose

It allows developers to set up and test project with single command, improving onboarding and DevOps flow.