Real-time stock price dashboard

Project overview

The project is built from two main components:

• a backend that periodically fetches user-defined stock data from Finnhub
• a front-end that utilizes Plotly and Dash to visualize the gathered data on interactive charts

Celery backed by Redis used as the message broker.

Prerequisites

• Python 3.8 and above
• Docker & Docker Compose
• Finnhub account and sandbox API key

Installing QuestDB & Redis

To install the services required for our project, Docker and Docker Compose used.

When run docker-compose up, DB and Redis will fire up. Can access DB interactive console on http://127.0.0.1:9000.

Create the database table

CREATE TABLE
      quotes(stock_symbol SYMBOL CAPACITY 5 CACHE INDEX, 
             current_price DOUBLE,
             high_price DOUBLE,
             low_price DOUBLE,
             open_price DOUBLE,
             percent_change DOUBLE,
             tradets TIMESTAMP, 
             ts TIMESTAMP)      
      timestamp(ts)
PARTITION BY DAY;

Create venv and install dependencies

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Create .env file where API KEY and tickers are stored

SMD_API_KEY = "<SANDBOX API KEY>"
SMD_FREQUENCY = 10
SMD_SYMBOLS = ["AAPL","DOCN","EBAY"]

To retrieve the key, sign up to Finnhub, and your API key will appear on the dashboard after login.

Shedule a job using Celery to retrieve data. Execute command in venv:

python -m celery --app app.worker.celery_app worker --beat -l info -c 1

Run dashboard

Docker containers should be started then execute PYTHONPATH=. python app/main.py from the project root:

$ PYTHONPATH=. python app/main.py

Navigate to http://127.0.0.1:8050/, to see the application in action.

If have problems with Dash:

pip uninstall werkzeug pip install -v https://github.com/pallets/werkzeug/archive/refs/tags/2.0.1.tar.gz

To run tests:

coverage run -m unittest discover