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alive-progress is an advanced Python progress bar library that introduces a highly animated and adaptive approach to tracking long-running tasks. Unlike traditional static progress indicators, it dynamically adjusts spinner speed and visual feedback based on actual throughput, giving users a more intuitive sense of activity. The library is designed with performance efficiency in mind, using multithreaded updates that minimize CPU overhead and terminal noise. It includes sophisticated ETA estimation powered by exponential smoothing algorithms, improving prediction accuracy for variable workloads. Developers can easily integrate it into scripts thanks to automatic logging hooks and flexible configuration options. With its emphasis on responsiveness, customization, and developer ergonomics, alive-progress stands out as a modern replacement for conventional Python progress bars.
Features
- Adaptive animated progress bars and spinners
- Intelligent ETA prediction with smoothing algorithm
- Low-overhead multithreaded rendering
- Automatic logging and print integration
- Pause and resume processing capability
- Highly customizable styles and animation factories
Project Samples
