KCET is one of the biggest engineering entrance exams conducted in India for the purpose of admission of students to the first year or first semester of full-time courses in medical, dental and engineering courses in professional Universities
KCET Counselling/Allotment is very similar to The National Resident Matching Program (NRMP) of the USA, the only major difference being the field of study. The scraper scrapes information off of the allotment result page and displays it in an organized manner helpful as an analyzing tool
- MongoDB for database management.
- Express as the backend framework.
- Next.js with React for the frontend.
- Server-Side Rendering (SSR) and Static Site Generation (SSG) with Next.js.
- REST API for seamless communication between frontend and backend.
The Scraper utilizes the native Fetch API to retrieve data from the results website. It parses the retrieved information and stores it in the MongoDB database for subsequent usage by the Server. It is recommended to run this process prior to the deployment of the server or the client application. By default, the Scraper examines all potential 675,000 combinations of roll numbers; however, this exhaustive check can be bypassed for subsequent rounds if already completed.
IMPORTANT: Large-scale data scraping, particularly when performed at a rapid pace, demands substantial resources from both the client and server side. In certain instances, it may be deemed illegal or considered a "Denial of Service" attack. The responsibility of ensuring legal and ethical use of this code lies with the person using the code. Please refer to the LICENSE for further important notices.
The server is built using Express and is responsible for handling all backend operations. It fetches information from the MongoDB database and responds to request calls made by the client. The server ensures efficient data retrieval and management, providing the necessary endpoints for the frontend to interact with. This enables seamless communication between the client and the database, facilitating features such as user queries and result analysis using REST API
The Client leverages the robust capabilities of Next.js and React to facilitate a seamless and interactive user experience. By utilizing Next.js's Server-Side Rendering (SSR) and Static Site Generation (SSG), the client application ensures optimal performance and quicker load times. When an end user performs a search query, the Client dynamically makes API calls to the server using RESTful endpoints established in the Express backend. These API calls securely fetch the required information from the MongoDB database, enabling real-time data retrieval and display on the client interface. This approach ensures efficient communication between the client and server, delivering accurate and timely results to the user.
To set up and run the KCET Allotment Analyzer application locally, follow these detailed steps:
Ensure you have the following installed:
- Node.js (version 20.x or above)
- npm (Node Package Manager)
- MongoDB (either local instance or cloud-based like MongoDB Atlas)
Clone the GitHub repository to your local machine:
git clone https://github.com/SinisterDeveloper/kcet
cd kcetThis code repository consists of 3 sub-applications or programs that need to be run in a specific order and the instructions for running the program are given below: