Run the commands:

git clone https://github.com/OmarAtyqy/stock-prediction-using-sentiment-analysis
cd stock-prediction-using-sentiment-analysis

Create an .env containg the credentials to a MongoDB cluster that has the following:

• Database named main
• Collection within this database named tweets

DB_USERNAME = _______________ # cluster username
DB_PASSWORD = _______________ # cluster password

Run the ./build.bat script

Run the ./build.sh script

To start the various services of the project, you can either manually run each service or use the provided scripts for convenience.

1. Dashboard Service:

   docker-compose exec -it dash-app bash
   cd /mnt && python3 -m src.dashboard.main_dashboard

2. Prediction Service:

   docker-compose exec -it spark-master bash
   cd /mnt && python3 -m src.spark.main_pipeline

3. Data Fetching Service:

   docker-compose exec -it kafka bash
   cd /mnt && python3 -m src.kafka.main <stock_name> <interval>

   Replace <stock_name> with the desired stock symbol and <interval> with the data fetching interval.

Alternatively, you can use the provided scripts to start all services simultaneously:

Run the run.bat script:

./run.bat <stock_name> <interval>

Run the run.sh script:

./run.sh <stock_name> <interval>

In both scripts, replace <stock_name> with the stock symbol and <interval> with the data fetching interval.