Sacred

What it is

Sacred is a Python tool designed to help configure, organize, log, and reproduce experiments. It provides a standard framework that can be extended with various add-ons, making it useful for researchers and developers in machine learning and data science.

Sacred stands out as an open-source, flexible tool that provides a standardized framework for experiment management and reproducibility in Python.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited community support and documentation

   The official documentation lacks comprehensive examples and troubleshooting guides. Community forums and Q&A sites have limited activity compared to more popular tools.

2. 02

   Frequent breaking changes between versions

   Historical updates, such as the transition from v0.1 to v0.2, required significant rework of existing configurations and experiment definitions.

3. 03

   Limited scalability for large-scale experiments

   Performance bottlenecks can occur with a high volume of concurrent experiments or very complex configurations, leading to slower execution times.

What it does well

• Standardized experiment configuration and logging

• Support for extensions through add-ons

• Reproducibility of experiments

• Integration with various storage backends

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.