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A graphical Python utility for visualizing historical Toggl time-tracking data, helping users explore and analyze how their time is spent over time.

A Go (Golang) wrapper for Toggl API v8 that enables Go applications and tools to interact with Toggl’s time-tracking endpoints.

A PHP library for Toggl API v8 built on the Guzzle HTTP client, allowing PHP applications to integrate with Toggl’s time-tracking features programmatically.

A Java wrapper for the Toggl time-tracking API v8, providing an object-oriented interface for integrating Toggl time tracking into Java applications.

A Node.js library for the Toggl API v8 that provides a programmatic interface for integrating Toggl time tracking into JavaScript/Node applications.

A KDE plasmoid that integrates Toggl Track time tracking into the KDE desktop, allowing users to start and manage Toggl timers directly from their panel.

An Arduino-based physical time tracking cube that uses the Toggl Track API. Each side of the paper cube can be configured to start tracking a different task when that side faces upwards.

A RESTful JSON API for Toggl’s time tracking service, enabling developers and third‑party applications to programmatically manage users, projects, and time entries in Toggl Track. It supports ISO 8601/RFC 3339 timestamps, per-user API tokens for authentication, and rate limiting via a leaky bucket algorithm, making it suitable for building custom time tracking integrations, automations, and reporting tools.

A Python project that uses the Toggl API to calculate how many hours you need to work to hit monthly goals, extending Toggl time tracking with goal management and planning capabilities.

An efficient Python command-line interface for quickly entering time-insensitive Toggl entries, streamlining bulk or approximate time tracking from the terminal.

A Java wrapper for the Toggl Reports API that simplifies accessing and processing detailed time-tracking reports from Toggl in Java applications.

A Spring Boot application built with Vaadin and MongoDB that imports your Toggl TimeEntries to provide fine-grained reporting and analysis, including detailed working hours comparisons between team members. A Docker image is also available for easy deployment.