Comet From $19/mo · Free plan 9.4 Visit Sacred
github.com
Spec sheet
- Purpose
- Sacred helps configure, organize, log, and reproduce computational experiments.Read 10 Oct 2026 · github.com
- Integrations
- The README describes a Neptune integration that logs Sacred experiments through an observer.Read 4 Oct 2026 · github.com
- Support
- The README directs usage questions to Stack Overflow under the python-sacred tag and invites bug reports and feature requests through GitHub issues.Read 10 Oct 2026 · github.com
- License
- The project is released under the MIT license.Read 10 Oct 2026 · github.com
- Command line
- Its command-line interface can change parameters to run experiments with modified settings.Read 10 Oct 2026 · sacred.readthedocs.io
- Config access
- Configuration parameters can be injected by name into functions.Read 4 Oct 2026 · github.com
- Configuration
- Config scopes turn local variables in decorated functions into experiment configuration entries.Read 10 Oct 2026 · sacred.readthedocs.io
- Experiment parameters
- Config scopes let local variables in a function define an experiment’s parameters.Read 4 Oct 2026 · github.com
- External dashboards
- The README lists external frontends including Omniboard, Incense, and Sacredboard for viewing Sacred experiment data.Read 10 Oct 2026 · github.com
- Installation
- The README says Sacred can be installed from PyPI using pip or installed from its Git repository.Read 10 Oct 2026 · github.com
- Integration
- The documentation includes a dedicated integration section for TensorFlow.Read 10 Oct 2026 · sacred.readthedocs.io
- Limit
- Sacred is designed for Python experiments; the README contrasts it with Sumatra for non-Python experiments.Read 4 Oct 2026 · github.com
- Optional dependencies
- NumPy and PyMongo are optional dependencies that offer additional features.Read 10 Oct 2026 · github.com
- Parameter access
- Captured functions can receive configuration entries through dependency injection.Read 10 Oct 2026 · sacred.readthedocs.io
- Reproducibility
- Automatic seeding helps control randomness so experiment results remain reproducible.Read 10 Oct 2026 · sacred.readthedocs.io
- Run logging
- Observers log experiment information and configuration and can save it to a database.Read 10 Oct 2026 · sacred.readthedocs.io
Where Specifiction places it
- ML Experiment Tracking Software#33 of 396.5
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