Real-Time Stock Price Monitoring Using Kafka

This project is a real-time stock price monitoring web application built with Flask, Kafka, and Plotly. It allows users to track real-time and historical stock prices of selected companies.

Table of Contents

• Prerequisites
• Getting Started
• Usage
• Project Structure
• Configuration
• License

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.7 or higher installed on your system.
• Access to a Confluent Cloud Kafka cluster.
• Confluent Kafka Python library installed (included in requirements.txt).
• A valid API key and secret for accessing the Confluent Cloud Kafka cluster.

Getting Started

To get this project up and running on your local machine, follow these steps:

1. Clone the Repository

git clone https://github.com/Shikha-code36/Real-Time-Stock-Price-Tracker-using-Kafka.git
cd Real-Time-Stock-Price-Tracker-using-Kafka

2. Set Up a Virtual Environment

It's a good practice to create a virtual environment to isolate project dependencies. Run the following commands to create and activate a virtual environment:

python -m venv venv
venv\Scripts\activate # On Windows
source ./venv/bin/activate # On Linux & Mac OS X

3. Install Dependencies

Use pip to install the project's dependencies from the requirements.txt file:

pip install -r requirements.txt

4. Configure the Project

Edit the config.py file and provide the following details:

• KAFKA_BOOTSTRAP_SERVERS: The Confluent Cloud
• Kafka cluster's bootstrap servers.
• KAFKA_TOPIC: The Kafka topic where stock prices will be published and consumed.
• API_KEY: Your Confluent Cloud API key.
• API_SECRET: Your Confluent Cloud API secret.

5. Run the Application

Start the Flask web application by running the following command:

python main.py

The app should now be available at http://localhost:5000/.

Usage

• Visit http://localhost:5000 to access the main dashboard.
• You can start and stop data production and consumption by clicking the respective buttons.
• Real-time and historical stock price charts will be displayed on the dashboard.

Project Structure

The project is organized as follows:

• producer.py: Handles fetching real-time stock prices and publishing them to Kafka.
• consumer.py: Consumes stock price data from Kafka and places it in a queue for the main thread.
• main.py: The main Flask application that serves the web interface.
• config.py: Configuration file for Kafka and API credentials.
• templates/: Contains HTML templates for the web pages.

Configuration

In the config.py file, you can configure the following settings:

• KAFKA_BOOTSTRAP_SERVERS: The Kafka bootstrap servers.
• KAFKA_TOPIC: The Kafka topic for stock price data.
• API_KEY: Your Confluent Cloud API key.
• API_SECRET: Your Confluent Cloud API secret.

License

This project is licensed under the MIT License. See the LICENSE file for details.