A fully serverless web application built on AWS that allows users to upload a CSV file, process the data in real-time, and visualize the results as an interactive bar chart. This project demonstrates a modern, event-driven architecture using core cloud services.
- Interactive Front-End 🎨: A responsive and visually appealing user interface where users can upload files.
- Serverless Back-End 🖥️: The entire back-end is powered by AWS Lambda, requiring no server management.
- Real-Time Processing ⚡: Data is processed and visualized instantly upon upload.
- Scalable & Cost-Effective 💰: The architecture scales automatically to handle demand and leverages the AWS Free Tier, making it highly cost-efficient.
This project uses a simple yet powerful serverless architecture:
- Amazon S3 🗂️: Hosts the static front-end web application (index.html, CSS, JS).
- Amazon API Gateway 🌐: Provides a secure and scalable HTTP endpoint that the front-end can call.
- AWS Lambda 🛠️: Contains the Python code that processes the CSV data using the Pandas library. It's triggered by the API Gateway.
- AWS IAM 🔒: Provides a secure role with the exact permissions needed for the Lambda function to operate, following the principle of least privilege.
- Cloud ☁️: AWS (S3, Lambda, API Gateway, IAM)
- Back-End 🐍: Python, Pandas
- Front-End 🌐: HTML5, CSS3, JavaScript (with HTML Canvas for visualization)
- The user visits the static website hosted on Amazon S3.
- When the user uploads a CSV file and clicks "Generate Chart," the JavaScript on the page sends the file's content to the API Gateway endpoint via a POST request.
- The API Gateway triggers the AWS Lambda function, passing the CSV data in the request body.
- The Python script in Lambda uses the Pandas library to read the data, perform a
groupby()aggregation to calculate the average price per category, and formats the result as a JSON object. - The Lambda function returns the JSON result back to the API Gateway.
- The front-end JavaScript receives the JSON data and uses the HTML Canvas API to draw an animated bar chart, providing an instant visualization to the user.
I am an AI Engineer with experience in building innovative and impactful projects. I have worked on numerous projects, including those that are more advanced and complex than this one. My passion lies in leveraging technology to solve real-world problems and creating solutions that are scalable, efficient, and user-friendly.