/ddiligence

A web application that gathers and displays historical stock data

Primary LanguagePythonMIT LicenseMIT

DDiligence

A parody application to help financiers make correlations with historic stock data and other historic data such as weather data, space weather, etc.

Table of Contents

  1. Development Setup

Setup

This is a monorepo of the ddiligence project. Clone the repo and refer to each subproject's readme.md for more details TODO create new readmes for each service.

Back End Flask Service Setup:

Required software: Python (3.11.4)

After cloning the entire project and setting up python in your machine:

  1. Create a python venv in the app_flask directory
  2. Within the app_flask directory install the required libraries:
    • run pip install -r requirements.txt
  3. To begin create a development environment, add the following block in api.py (ensure to remove it before deploying to production branch) #TODO include this in validation step during build 
    if __name__ == '__main__':
    app.run(debug=True)
    • To deploy a local testing environment of the server run: python <path_to_app_flask>/api.py through your activated virtual environment.
      • It should create an environment you can begin testing at http://127.0.0.1:5000/
  4. Create unit tests under the app_flask/tests/ directory ensure you also run the existing unit tests before submitting:
    • python -m unittest discover -s tests

Front End React Client Setup:

Required software: Node.js, npm after cloning the project

  1. within the client_react directory:
    • run npm install
      • this should automatically install the required npm packages
  2. To deploy a local testing environment of the server run: npm start
    • It should create an environment you can begin testing at http://localhost:3000

Database & Filesystem Setup

Build & Deployment Setup

additional files for the final deployed project

  1. images & icons (TODO figure out how to handle serving final files during deployment step)

CI/CD Workflow Setup

located in the .github/workflows/ directory

TODO generate documentation for each component