watermark

What it is and what it does

Watermark is an IPython magic extension that captures and displays metadata about your computational environment. It works both as a magic command in Jupyter notebooks and IPython sessions (via %watermark) and as a callable function in regular Python code. The extension prints timestamps, Python implementation details, system information (OS, CPU, machine type), and versions of any packages you specify.

The package depends on ipython, importlib-metadata, and setuptools. It supports Python 3.7 and later and has been in production use since 2016. Common use cases include documenting notebook execution time, recording environment snapshots for reproducibility, and checking installed package versions at runtime.

Use it for:

• Add a timestamp and environment snapshot to the top of a Jupyter notebook for reproducibility tracking.
• Check versions of key dependencies (numpy, scipy, etc.) at runtime without separate import statements.
• Document system information (CPU cores, OS, Python version) in notebook output for debugging or reporting.
• Verify GPU availability and NVIDIA driver information in machine learning workflows.
• Track which Jupyter environment (Colab, VS Code, Jupyter Lab) a notebook is running in.

Worth the install?

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

Watermark is an IPython magic extension that prints date/time stamps, Python and system version information, package versions, and hardware details in Jupyter notebooks and IPython sessions.

Yes. Watermark is a lightweight, stable utility with low install friction and no known vulnerabilities. It solves a real problem—capturing reproducible environment metadata—with a simple, well-established API. Install it if you work regularly in Jupyter notebooks or IPython and need to document or inspect your computational environment.

Install

watermark on PyPI

pip install watermark

uv add watermark

poetry add watermark

Installing watermark

Before you install

Low install friction with a pure-Python wheel distribution. Maintenance is aging (236 days since last release), but the repository remains active with recent commits and the package is marked Production/Stable.

License in practice

Licensed under the permissive BSD license, which allows free use, modification, and distribution with minimal restrictions.

Quickstart

pip install watermark

# In IPython/Jupyter:
%load_ext watermark
%watermark -v -m

# Or as a module:
from watermark import watermark
print(watermark(packages="numpy,scipy"))

Verify before relying

• Whether GPU information printing (--gpu flag) works reliably on non-NVIDIA hardware or if py3nvml is truly optional.
• How well the retrospective import capture (-iv flag) handles complex import patterns or dynamic imports.

Package facts

Evidence: watermark-2.6.0-py3-none-any.whl

Tags

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