Time-Series-Stock-Predictor

Tech Stack Used:

• Python fastApi for backend
• HTML & JS for Frontend
• postgreSQL 14 as Database

Follow the steps below to setup your project.

installation packages:

• pip install ta
• pip install fastapi uvicorn
• pip install python-dotenv
• pip install tensorflow
• pip install celery
• pip install sqlalchemy
• pip install psycopg2

create a .env file

Write the below things in the env file

• API_KEY_1 = "YOUR_API_KEY"
• API_KEY_2 = "YOUR_API_KEY"
• API_KEY_3 = "YOUR_API_KEY"
• BASE_URL = 'https://www.alphavantage.co/query'
• DATABASE_URL = "postgresql://{user}:{password}@localhost:{portnumber}/{database_name}"

To run application in vscode:

• uvicorn main:app --reload

To predict model :

http://127.0.0.1:8000/api/v1/stock_prices/{bse_stock_name}

replace bse_stock_name with your stock name.