Real Estate

Project Description

This project involves developing a Database Management System (DBMS) for a real estate office that handles the sale and rental of houses and apartments within a city. The system will store data for agents, property details, and handle various queries to assist the real estate office in its operations.

Data Requirements

The system must manage the following data:

• Agents: Agents facilitate interactions with buyers and sellers, showcase properties, and handle sales or rental agreements.
• Properties: The model should provide
  • Buy/Rent
  • Category(Type of property)
  • Property size (e.g., 1500 sq. ft)
  • Location
  • Furnishing Status

Data Generation

You can refer to real estate websites such as MagicBricks, 99Acres, and Makaan for inspiration on data generation.

Project Requirements

1. E-R Model

• Construct an E-R Diagram representing the conceptual design of the database.
• Identify primary keys, relationship cardinalities, and any assumptions.

2. Relational Model

• Convert the E-R design into a relational model and refine it according to relational design principles.
• Create the relations in MySQL.
• Create indices and constraints as needed.
• Refine both the E-R and relational models as necessary to ensure consistency.

3. Populating Relations

• Populate the relations with enough data to make the queries meaningful and non-trivial.
• You may write a program to generate the test data.

4. Queries

You are required to implement the following queries:

• List houses in your city (e.g., Guwahati) built after 2020 that are available for rent.
• Find addresses of houses in your city costing between Rs. 30,00,000 and Rs. 50,00,000.
• Find addresses of rental houses on a specific road (e.g., G.S. Road) with at least 2 bedrooms and a rent below Rs. 15,000 per month.
• Find the agent who sold the most properties by total amount in rupees in the year 2023.
• For each agent, calculate the average selling price of properties sold in 2018 and the average time properties remained on the market.
• List the details of the most expensive houses and those with the highest rent in the database.

5. Interfaces

The database will be accessed by three types of users, each with their own interface:

• Database Administrator: Can access the system using SQL via the command line.
• Real Estate Office: A GUI interface to:
  • Get sales reports for each agent, including sale dates, property details, and selling prices.
  • View rental reports for each agent, including rent amount, area, and rental dates.
• Agents: Can update the database when a property is rented or sold. This can be implemented using:
  • Web applications
  • Standalone JavaScript applications.

E-R Diagram(Entity Relationship)

An ER diagram shows the relationship among entity sets. An entity set is a group of similar entities and these entities can have attributes. In terms of DBMS, an entity is a table or attribute of a table in database, so by showing relationship among tables and their attributes, ER diagram shows the complete logical structure of a database.

Know more about the ER-Diagram here.

Schemas

To see the detailed schema see schemas.md

Tools and Technologies

Frontend

• HTML
• CSS (including Bootstrap)
• JavaScript
• React.js

Backend

• Express
• Node.js
• MySQL

Prerequisites

Before you can install and run this software, you must have the following prerequisites installed:

• Node.js (version 14 or later)
• npm (version 6 or later)
• MySQL (version 8 or later)
• MySQL Workbench (latest version)

If you don't have Node.js or npm installed, you can download and install them from the Node.js website. If you don't have MySQL or MySQL Workbench installed, you can download and install them from the MySQL website.

Make sure to install the latest versions of Node.js, npm, MySQL, and MySQL Workbench to ensure compatibility with this software.

To import the provided database, follow these steps:

• Extract the database file present in the root directory.
• Open MySQL Workbench and connect to your MySQL database.
• Click on Server > Data Import.
• Select Import from Self-Contained File and browse to the location of the extracted database file.
• Under Default Schema to be Imported To, select New... and enter the name "project" for the database.
• Click Start Import to import the database.

Installation

• Clone the repository or download the source code

git clone https://github.com/Parshantkumar2033/Real_estate_website.git

• Install dependencies by running the following command in the project directory

npm install`

Configuration

Create a .env similar to the .env.example file in the root directory and make the following changes to it:

• Replace Your mysql username with with the username of your mysql local server (usually "root").
• Replace Your mysql password with with the password of your mysql local server.

Starting the app

• Run the following command in the project directory:

nodemon .\app.js` or `node .\app.js