Aeromancy
Framework for reproducible AI and ML experiments
- Status
- UnmaintainedNo commits in 690 days.
- Last checked
- Checked · Oct 5, 2026
- License
- Open source
- Pricing
- Free tier
What it is
Aeromancy is a Python-based framework designed to facilitate reproducible AI and machine learning experiments. It emphasizes reproducibility in data science by providing tools to manage and document experiments effectively. The framework supports reproducible research practices, making it easier for data scientists to share and validate their work. Aeromancy is open-source under the Apache-2.0 license, and it is actively maintained with a focus on improving reproducibility in scientific computing.
Strong emphasis on reproducibility in AI and ML experiments.
When it fits — and when it doesn’t
A good fit for
Academic research projects
Emphasizes reproducibility, which is crucial for academic validation.
Data science teams focusing on reproducibility
Provides tools to ensure experiments can be reliably reproduced.
Look elsewhere if
Large-scale enterprise deployments
Emerging tool with limited community support and contributors.
Non-Python environments
Designed specifically for Python, limiting use in other programming environments.
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited community engagement
Only 11 stars and 3 watchers on GitHub.
- 02
Few contributors
Only 3 contributors listed on GitHub.
- 03
High number of open issues
23 open issues on GitHub.
What it does well
Focus on reproducibility
Includes features for managing experiment metadata and dependencies.
Open-source with Apache-2.0 license
Available on GitHub with an open-source license.
Python-based
Written in Python, a popular language for data science.
Pricing
- Free tier
- Yes
- Paid from
- —
- Model
- N/A
- Enterprise plan
- No
Pricing last confirmed Oct 1, 2026.
Performance benchmarks
How Fast Is It?
Set up Aeromancy
Setup steps, common gotchas and what to check after 30 days.