TahaGorme
InstaMassUnliker
Python

A powerful Instagram bulk unlike tool to mass unlike Instagram reels and posts all at once for managing your digital footprint.

Last updated Jun 22, 2026
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README

๐Ÿ“ฑ InstaMassUnliker

A powerful, free & open-source Instagram bulk unlike tool to mass unlike instagram reels and posts for managing your digital footprint.

Python Version License Open Source Maintenance PRs Welcome

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๐Ÿ“‘ Table of Contents

๐ŸŒŸ Why InstaMassUnliker?

A powerful and free open-source Instagram automation tool for managing your digital footprint. Perfect for:

  • ๐Ÿ”’ Privacy-conscious social media users
  • ๐Ÿ‘ฅ Social media managers
  • ๐Ÿ“ฑ Instagram power users
  • ๐Ÿ›ก๏ธ Digital privacy enthusiasts

๐Ÿ’ซ Key Features

๐Ÿš€ Performance

  • Smart Rate Limiting: Completely undetected by Instagram
  • Bulk Processing: Handle hundreds of thousands of posts efficiently
  • Resource Friendly: Minimal system requirements
  • Cross-Platform: Works on Windows, macOS, and Linux

๐Ÿ›ก๏ธ Security

  • Local Operation: All processing happens on your machine
  • 2FA Support: Two-factor authentication support
  • Session Management: Secure cookie handling
  • No Data Collection: Your data stays with you

๐Ÿ“Š Features

  • Progress Tracking: Real-time progress monitoring
  • Error Handling: Automatic retry on failures
  • Configurable Settings: Customize to your needs
  • Activity Logging: Track your operations

๐Ÿš€ Quick Start Guide

Prerequisites

  • Export Your Instagram Data
- Go to Instagram Settings > Account Center > Your Information and Permissions > Download your Information - Request "Download Data" in JSON format - Wait for Instagram's email (can take up to 48 hours, usually takes 15 mins for me tho) - Download and extract the ZIP file - Locate liked_posts.json in the extracted files - Copy liked_posts.json to the InstaMassUnliker folder

Windows Users

1. Download & Extract
๐Ÿ“ฅ Download ZIP from the green "Code" button above
๐Ÿ“‚ Extract to your preferred location
  • Run Installer
โ–ถ๏ธ Double-click run.bat

macOS/Linux Installation

1. Download & Extract
๐Ÿ“ฅ Download ZIP from the green "Code" button above
๐Ÿ“‚ Extract to preferred location
  • Run Installer
chmod +x run.sh ./run.sh

๐Ÿ’ป System Requirements

Automatic Setup

The installer handles all dependencies automatically:
  • Python 3.7+ (auto-installed)
  • Required Python packages (auto-installed)
  • FFmpeg for media processing (auto-installed)
  • Virtual environment setup (automatic)

Supported Platforms

  • Windows 10/11 (64-bit)
  • macOS 10.15+ (Intel/Apple Silicon)
  • Linux (Major distributions)

๐ŸŒ Configuration

Basic Settings

image
{
    "delay": {
        "min": 0.1,
        "max": 0.2
    },
    "break": {
        "min": 900,
        "max": 3600,
        "probability": 0.001
    },
    "accounts": {
        "account_username": {
            "enabled": true,
            "delay_multiplier": 1.0
        }
    },
    "log_level": "INFO",
    "max_retries": 3,
    "retry_delay": 60,
    "pythonminversion": "3.7.0"
}

๐Ÿ“š Documentation

Quick Usage Guide

  • Installation
- Windows: Run run.bat - macOS/Linux: Execute run.sh
  • Setup: Add Instagram Account, then provide your login credentials, and then start the unliking process
  • Operation: Follow the interactive dashboard
  • Monitoring: Track progress in real-time

Safety Features

  • Intelligent rate limiting
  • Random action delays
  • Smart cooldown periods
  • Automatic error recovery
  • Secure session management

๐Ÿค Contributing

We welcome contributions! Here's how you can help:

  • Report bugs
  • Suggest features
  • Submit pull requests
  • Improve documentation

๐Ÿ’ Support

Need help? We're here for you!

  • ๐Ÿ› Report issues on GitHub
  • ๐Ÿ“ง Contact: u/TahaGorme on reddit

๐Ÿ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.

โš ๏ธ Disclaimer

This tool is for educational purposes only. Use responsibly and in accordance with Instagram's terms of service.


Issues โ€ข License


Made with โค๏ธ by u/TahaGorme

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