scooby

What it is and what it does

Scooby is a lightweight environment reporting tool that captures your Python setup—OS, Python version, CPU count, RAM, architecture, and installed package versions—and formats it as an HTML table in Jupyter notebooks or plain text elsewhere. It has no runtime dependencies and is designed to be added as a dependency to other projects so users can easily generate diagnostic reports when debugging issues.

The package is commonly used by library maintainers to let users quickly report their environment when filing bug reports. You can customize reports by specifying core packages (mandatory for your project), optional packages, and additional packages users want to include. It also supports soft-dependency patterns so projects can use scooby without making it a hard requirement.

Use it for:

• Generate environment snapshots in bug reports to help maintainers diagnose version conflicts and platform-specific issues.
• Embed in a library's Report class so users can call your_package.Report() to see all relevant versions at once.
• Display system resources and Python environment in Jupyter notebooks for reproducibility and documentation.
• Implement as a soft dependency in projects that want environment reporting without forcing scooby on all users.
• Audit package versions and hardware specs across different machines or CI/CD environments.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Scooby generates formatted reports of your Python environment's package versions, Python version, OS details, CPU count, RAM, and hardware architecture.

Yes. Scooby is lightweight, has zero runtime dependencies, carries a permissive MIT license, and is actively maintained. Install it if you need to report Python environment details—either directly for debugging or as a dependency in your own library to help users submit better bug reports.

Install

scooby on PyPI

pip install scooby

uv add scooby

poetry add scooby

Installing scooby

Before you install

Low install friction with no runtime dependencies. Active maintenance with recent commits and stable production status.

License in practice

MIT license permits unrestricted use, modification, and distribution with minimal restrictions.

Quickstart

pip install scooby

import scooby
scooby.Report()

# or use the alias
scooby.doo()

Requires Python 3.10 or later.

Verify before relying

• Whether scooby can detect all modern hardware configurations (GPU, specialized accelerators) beyond CPU/RAM/architecture
• Performance impact when reporting on projects with hundreds of dependencies

Package facts

Evidence: scooby-0.11.2-py3-none-any.whl

Keywords: environment, reporting, versioning

Tags

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