dependency-planner

Dependency planning prevents runtime failures by detecting your OS, Python, and CUDA environment, then generating a locked installation plan with explicit user confirmation before proceeding.

The best way to audit installations is to generate an auditable plan that parses dependencies from requests or error messages, looks up official guidance, and creates reproducible lockfiles before execution.

Yes, dependency planning works with conda and pip environments by automatically detecting the active environment status and generating tailored installation plans to ensure reproducibility.

To generate reproducible lockfiles, you can parse required dependencies, verify official guidance, and output locked files like requirements-pinned.txt or environment-lock.yml for a safe installation.

You should verify dependencies before installing new packages to prevent runtime failures, resolve command not found errors, and ensure compatibility across your detected OS, Python, and CUDA environments.