rsalmei/alive-progress

A new kind of Progress Bar, with real-time throughput, ETA, and very cool animations!

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Summary Information

Updated 33 minutes ago
Added to GitGenius on September 10th, 2026
Created on August 5th, 2019
Open Issues & Pull Requests: 20 (+0)
GitHub issues: Enabled
Number of forks: 236
Total Stargazers: 6,305 (+0)
Total Subscribers: 52 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 30.2 hours
Mean response time: 38.0 days
90th percentile: 98.6 days
Tracked items: 43

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 9% of issues opened in the past year have been closed. Three people close 89% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 11
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,279 days
Stale 30+ days: 10
Stale 90+ days: 10

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • feature request (8)
  • improvement (3)
  • only on windows (2)
  • bug (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

alive-progress is a Python library that provides animated progress bars for terminal applications with real-time throughput calculation and estimated time of arrival displays.

The library addresses the need for more engaging and informative progress feedback in command-line tools. Rather than static progress bars, it renders animated visual elements that update in real time, showing not just completion percentage but also the rate at which work is being processed and how long until completion. The animations are designed to be visually interesting while remaining functional, giving users confidence that a long-running operation is still progressing.

The tool suits developers building CLI applications, scripts, or any Python code that performs operations taking noticeable time. It works in standard terminal environments and supports multi-threaded scenarios where multiple progress indicators may run concurrently. The library offers customizable spinner styles and animations, allowing developers to match the visual presentation to their application's character. Anyone integrating progress feedback into existing Python projects will find it a drop-in replacement for simpler progress bar implementations, with the added benefit of throughput and ETA information without requiring additional configuration.

The project shows consistent maintenance with regular updates addressing user feedback and edge cases. Development activity demonstrates responsiveness to issues raised by users, with fixes and improvements being incorporated into the codebase. The maintainer engages with the community through issue discussions and pull request reviews, indicating active stewardship of the project's direction and quality.