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Land-record utility focused on Khasra information and structured land-data workflows.

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Haryana Partition Manager

A desktop application for managing land ownership, khewat partition workflows, khasra allocations, and audit history for Haryana revenue records.

Built using Python, PySide6, SQLAlchemy, and SQLite.


Overview

Haryana Partition Manager is designed to simplify and digitize land partition workflows traditionally managed through revenue records such as:

  • Villages
  • Khewats
  • Ownership Shares
  • Khasras
  • Partition Registers
  • Allocation Transactions

The application provides a structured workflow for managing ownership records, partition operations, and khasra allocation history with full audit tracking.


Key Features

Village Management

  • Village master records
  • District, Tehsil, and Sub-Tehsil support
  • Hadbast number tracking
  • Jamabandi year management

Owner Management

  • Owner master database
  • Ownership share management
  • Multiple owners per khewat

Khewat Management

  • Create and edit khewats
  • Owner mapping
  • Share calculations
  • Ownership tracking

Partition Management

Full Partition Wizard

  • Complete khewat partition workflow
  • Automatic share calculations
  • New khewat generation

Partial Partition Wizard

  • Partial ownership separation
  • Share transfer management
  • Remaining share calculations
  • New khewat creation

Khasra Allocation Wizard

  • Allocate area from one khewat to another
  • Area split preview
  • Validation checks
  • Allocation transaction recording

Allocation Audit Trail

  • Allocation history recording
  • Undo allocation support
  • Audit tracking
  • Transaction logging

Search & Reporting

  • Universal Search
  • Partition Register
  • Khewat History
  • Ownership Reports

Database Utilities

  • Database Backup
  • Database Restore
  • SQLite storage engine

Technology Stack

Component Technology
Language Python 3
GUI Framework PySide6
ORM SQLAlchemy
Database SQLite
Architecture Desktop Application

Project Structure

Haryana_Partition_Manager/
│
├── database/
│   ├── db.py
│   ├── models.py
│   └── seed_data.py
│
├── gui/
│   ├── main_window.py
│   ├── owner_screen.py
│   ├── village_screen.py
│   ├── khewat_screen.py
│   ├── partition_wizard.py
│   ├── partial_partition_wizard.py
│   ├── khasra_allocation_wizard.py
│   ├── partition_register.py
│   └── khewat_history.py
│
├── data/
│   └── haryana.db
│
├── main.py
└── README.md

Current Functionality

Implemented

  • Village Management
  • Owner Management
  • Khewat Management
  • Full Partition Wizard
  • Partial Partition Wizard
  • Khasra Allocation Wizard
  • Allocation Recording
  • Allocation History Recording
  • Undo Allocation
  • Partition Register
  • Khewat History
  • Universal Search
  • Database Backup & Restore

In Progress

  • Allocation Register Screen
  • Khasra History Screen
  • Allocation Service Layer

Planned

  • Parent/Child Khasra Split Engine
  • Khewat Family Tree
  • Road Reservation Module
  • Watercourse Reservation Module
  • Advanced Reporting Dashboard

Installation

Clone the repository:

git clone https://github.com/Fanu2/Khasra.git
cd Khasra

Install dependencies:

pip install -r requirements.txt

Run the application:

python main.py

Database

The application uses SQLite for local storage.

Database file:

data/haryana.db

All partition and allocation operations are stored for audit and recovery purposes.


Roadmap

Release B

  • Allocation Register
  • Khasra History Register
  • Allocation Service Layer

Release C

  • Parent/Child Khasra Split Engine
  • Allocation Progress Tracking
  • Khewat Family Tree

Release D

  • Road Reservation
  • Watercourse Reservation
  • Advanced Land Record Analytics

Contributing

Contributions, bug reports, and feature suggestions are welcome.

Please create an issue or submit a pull request.


License

MIT License


Author

Developed for digitizing Haryana land partition and revenue record management workflows.

About

Land-record utility focused on Khasra information and structured land-data workflows.

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Contributing

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