ActivityWatch

ActivityWatch

ActivityWatch automatically tracks how you spend time on your devices. It provides comprehensive activity monitoring, privacy-focused data collection, and detailed analytics to help you understand and optimize your digital habits and productivity.

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Repository activity:
Stars
14,461
Forks
659
Watchers
125
Open Issues
166
Last commit
4 months ago
Details:
Estimated Popularity
60
Pricing Model
Free
Hosting Type
Self-Hosted
License
MPL-2.0
Deployment Difficulty
Easy
Language
Python

ActivityWatch is an open-source, privacy-focused automatic time tracker that monitors how you spend time on your devices. Unlike cloud-based alternatives, it keeps all data locally while providing comprehensive insights into your digital habits, application usage, and productivity patterns.

Key Features

  • Automatic Activity Tracking:

    • Continuous monitoring of active applications
    • Website and browser activity tracking
    • Window title and document tracking
    • Keyboard and mouse activity detection
    • Idle time recognition and categorization
    • Cross-device activity correlation
  • Privacy-First Design:

    • All data stored locally on your device
    • No cloud services or external servers
    • Complete data ownership and control
    • Privacy-focused architecture
    • Offline operation capability
    • Optional data sharing controls
  • Comprehensive Analytics:

    • Interactive timeline visualization
    • Detailed activity reports and summaries
    • Productivity metrics and insights
    • Category-based time analysis
    • Historical data trends
    • Custom time period analysis
  • Cross-Platform Support:

    • Native desktop applications for Windows, macOS, Linux
    • Android mobile application
    • Browser extensions for web tracking
    • Synchronized data across devices
    • Platform-specific optimizations
    • Consistent user experience
  • Data Management:

    • Flexible data export options
    • Backup and restore functionality
    • Configurable data retention policies
    • Custom activity categorization
    • Rule-based automatic classification
    • Data filtering and processing
  • Extensibility & Integration:

    • Modular watcher system
    • Plugin architecture for custom functionality
    • REST API for data access
    • Custom data processors
    • Third-party integration support
    • Developer-friendly architecture
  • User Control:

    • Granular privacy controls
    • Selective tracking options
    • Custom blacklists and whitelists
    • Activity pause and resume
    • Data deletion controls
    • Transparency in data collection

Technical Specifications

  • Language: Python
  • Database: Local SQLite
  • Frontend: Web-based dashboard
  • API: REST API
  • License: MPL-2.0
  • Platforms: Windows, macOS, Linux, Android

Use Cases

  • Personal Productivity: Understanding and optimizing personal work habits
  • Time Awareness: Gaining insights into digital device usage patterns
  • Habit Tracking: Monitoring and improving digital wellness
  • Work Analysis: Analyzing work patterns and productivity trends
  • Research: Academic research on digital behavior and productivity
  • Self-Improvement: Data-driven approach to time management

Unique Advantages

  • Privacy-Focused: Complete local data storage with no cloud dependency
  • Automatic Tracking: Passive monitoring requiring no manual input
  • Cross-Platform: Comprehensive coverage across desktop and mobile devices
  • Open Source: Transparent, auditable, and customizable codebase
  • No Subscription: Free forever with no usage limitations
  • Extensible: Plugin system for custom functionality and integrations

Based on the ActivityWatch GitHub repository, this tool provides individuals with a powerful, privacy-respecting way to understand their digital habits and optimize their productivity without compromising data privacy or requiring ongoing subscriptions.

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