Knock Knock is a lightweight Python utility created by the Hugging Face team that allows developers to receive notifications when long-running machine learning tasks finish or fail. Training deep learning models often takes hours or even days, making it inconvenient for engineers to constantly monitor progress manually. The library solves this problem by adding simple decorators or command-line commands that automatically send notifications when a process completes or crashes. These alerts can be delivered through several communication platforms such as email, Slack, Telegram, or other messaging services. The goal of the project is to allow developers to monitor experiments remotely without needing to stay connected to the training environment. By adding only a few lines of code, the library can wrap around a training function and report execution status.

Features

  • Automatic notifications when machine learning training completes or crashes
  • Simple decorator-based integration with Python scripts
  • Support for notification services such as email, Slack, and Telegram
  • Command-line interface for wrapping arbitrary scripts
  • Designed for monitoring long-running ML experiments
  • Minimal setup requiring only a few lines of code

Project Samples

Project Activity

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Categories

Machine Learning

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Machine Learning Software

Registered

2026-03-11