Sacred
A tool to help you configure, organize, log and reproduce experiments.
Overview
Sacred is a Python tool that helps you keep track of your computational experiments. It allows you to define and configure your experiments in a clean and organized way, and it automatically logs all the important information, including your code, parameters, and results. Sacred is designed to make your experiments more reproducible and easier to manage.
✨ Key Features
- Experiment Configuration
- Automatic Logging
- Reproducibility
- Command-line Interface
- Extensible with Observers
🎯 Key Differentiators
- Focus on experiment configuration and reproducibility
- Lightweight and easy to integrate into existing code
- Extensible with different backends for storing results
Unique Value: Sacred provides a simple and effective way to organize and reproduce your computational experiments, helping you to do better science.
🎯 Use Cases (4)
✅ Best For
- Running and logging hyperparameter tuning experiments
- Keeping a record of all experiments for a research paper
- Reproducing the results of a previous experiment
💡 Check With Vendor
Verify these considerations match your specific requirements:
- The entire end-to-end MLOps lifecycle
- Users who need a graphical user interface for experiment tracking
🏆 Alternatives
Compared to more comprehensive platforms like MLflow or Weights & Biases, Sacred is a more lightweight and focused tool for experiment configuration and logging. It is less opinionated and can be easily integrated into a variety of workflows.
💻 Platforms
✅ Offline Mode Available
🔌 Integrations
💰 Pricing
Free tier: Open-source and free to use.
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