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InstaMassUnliker

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

Install / Use

/learn @TahaGorme/InstaMassUnliker

README

📱 InstaMassUnliker

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

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Python Version License Open Source Maintenance PRs Welcome

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📑 Table of Contents

🌟 Why InstaMassUnliker?

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

  • 🔒 Privacy-conscious social media users
  • 👥 Social media managers
  • 📱 Instagram power users
  • 🛡️ Digital privacy enthusiasts

💫 Key Features

🚀 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

🛡️ 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

📊 Features

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

🚀 Quick Start Guide

Prerequisites

  1. 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
📥 Download ZIP from the green "Code" button above
📂 Extract to your preferred location

2. Run Installer
▶️ Double-click run.bat

macOS/Linux Installation

1. Download & Extract
📥 Download ZIP from the green "Code" button above
📂 Extract to preferred location

2. Run Installer
chmod +x run.sh
./run.sh

💻 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)

🌐 Configuration

Basic Settings

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{
    "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,
    "python_min_version": "3.7.0"
}

📚 Documentation

Quick Usage Guide

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

Safety Features

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

🤝 Contributing

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

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

💁 Support

Need help? We're here for you!

  • 🐛 Report issues on GitHub
  • 📧 Contact: u/TahaGorme on reddit

📄 License

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

⚠️ Disclaimer

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


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IssuesLicense

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<div align="center"> Made with ❤️ by u/TahaGorme </div>
View on GitHub
GitHub Stars75
CategoryDevelopment
Updated1d ago
Forks8

Languages

Python

Security Score

100/100

Audited on Mar 20, 2026

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