tensorchord/envd

🏕️ Reproducible development environment for humans and agents

61
/ 100
Established

This tool helps AI/ML practitioners quickly set up reproducible development environments without dealing with complex configurations. You define your desired packages and tools in a simple Python-based file, and it creates a ready-to-use, isolated environment. It's designed for data scientists, machine learning engineers, and researchers who need consistent setups for training and experimentation.

2,189 stars. Actively maintained with 2 commits in the last 30 days.

Use this if you are an AI/ML practitioner struggling with setting up consistent development environments across different machines or team members, or if you frequently encounter dependency conflicts and 'works on my machine' issues.

Not ideal if you primarily work outside of AI/ML development or if your projects do not require complex dependencies or containerized environments.

machine-learning-engineering data-science-workflows reproducible-research model-training deep-learning-development
No Package No Dependents
Maintenance 16 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 19 / 25

How are scores calculated?

Stars

2,189

Forks

167

Language

Go

License

Apache-2.0

Category

mlops-end-to-end

Last pushed

Mar 19, 2026

Commits (30d)

2

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/mlops/tensorchord/envd"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.