Mandala
A simple & elegant experiment tracking framework for Python.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Mandala?
Mandala is an experiment tracking framework that integrates persistence logic and best practices directly into Python, making it easier to manage and track machine learning experiments.
Key differentiator
“Mandala stands out by integrating persistence logic directly into Python, making it a lightweight yet powerful tool for managing ML experiments without the need for external services.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development is focused on Python, with minimal official support for other languages
Users have reported slow performance when tracking a large number of experiments concurrently
Fit analysis
Who is it for?
✓ Best for
Developers who need a simple, integrated solution for tracking ML experiments in Python.
Teams that prioritize reproducibility and best practices in their machine learning workflows.
✕ Not a fit for
Projects requiring real-time experiment tracking or monitoring.
Users looking for cloud-based experiment management solutions.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Next step
Get Started with Mandala
Step-by-step setup guide with code examples and common gotchas.