Show HN: Skeights – Serialize sklearn models to safetensors and JSON, no pickle

Description and use

Here's a brief summary and explanation of the project:

**Summary:**
Skeights is an open-source project that enables serialization of sklearn models to safetensors and JSON formats without using pickle, providing a proven implementation pattern for learning and implementing.

**Value:**
The value of Skeights lies in its ability to teach users implementation patterns through working code, making it a valuable resource for learning and building tutorials. It also helps in training teams on a specific stack.

**Practical Adoption Path:**
For practical adoption, users should start by manually inspecting the code and dependencies before integrating Skeights into their workflow. This is due to the sparse integration signals in the discovered metadata. Once inspected, users can adopt Skeights for prototype development or internal workflows, keeping in mind the need for dependency and maintenance checks before moving to production.

**Production Readiness:**
Skeights has a medium-level production readiness score, indicating that it can be useful for prototypes or internal workflows but requires verification of its quality signals, license, maintenance, documentation, issues, and release cadence before being used in production environments.

Use in a workflow

Show HN: Skeights – Serialize sklearn models to safetensors and JSON, no pickle helps learn proven implementation patterns from working code.

• learn an implementation pattern
• build tutorials
• train a team on a stack

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.