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A project that helps handles data for real estate sales and insights

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SurajBhari/real_estate_managment

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Real Estate Management System

Experience a comprehensive system with both frontend and backend capabilities designed to streamline the management of real estate sales.

Each plot is characterized by three key properties:

  1. Plot Number
  2. Sector
  3. Colony

Download

Download the latest version from the automatic build:

Package Application with Pyinstaller

Login

Login Image

If using the default hash, the password will be displayed in the console.

Optional (but recommended): Change the hash here and use PyOTP to enhance security by adding it to your Google Authenticator app.

Design Choice

The system, designed for single-user local management, avoids unnecessary complications by opting for a single-user approach without usernames.

Search

Search Image

The search functionality offers nine columns for filtering. For instance, you can search for an advisor like "John Harris" with the status "booked."

New Sale

New Sale Image

The new sale or modification feature allows for easy property status changes, and opting for "available" or "not for sale" removes all associated attributes.

Receipt

Receipt Image

Each entry of money received from the buyer is recorded as a receipt. It provides insights into pending and received amounts.

Incentive

Incentive Image

Advisors receive a percentage of the sale as an incentive, calculated based on the date of receipt. The system also tracks uncollected incentives.

EMI

EMI Image

EMI details showcase received amounts for a specific advisor in a given month, with uncollected payments highlighted in red.

Global Features

  • Export options for EMI, Incentive, and Receipt entries in xlsx format.
  • Manual backup option on the home page, ensuring data integrity.
  • Changes in data trigger an automatic backup.

Future Plans

While future updates may include statistical insights into company and sales growth, the current focus is on stability and core functionality.

Compiling

  1. Install requirements from requirements.txt using pip install -r requirements.txt.
  2. Install pyinstaller with pip install pyinstaller.
  3. Compile using the command: pyinstaller --onefile --add-data "templates;templates" --add-data "static;static" --add-data "scripts;scripts" main.py.
  4. Move backup, export folders, and data.json to the newly created dist folder.
  5. Use main.exe from the dist folder.

Note

This system was designed for local use and has not been exposed to the internet. While some security measures are in place, responsible usage is advised.


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A project that helps handles data for real estate sales and insights

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