tools

What it is and what it does

tools is a collection of convenience functions for common Python programming tasks. It provides basic utilities like pickle serialization shortcuts (save_pickle, load_pickle) and optional API-specific helpers for scikit-learn metrics and PyTorch optimization. The package is intentionally undocumented—the author notes that most code contains inline explanations and recommends using help() to explore functions. It has no external runtime dependencies, making installation frictionless.

The package is actively maintained as of 2026-08-13 with a recent release, but its minimal documentation and reliance on inline comments mean you'll need to inspect the source code to understand what each function does. It's positioned as a personal toolkit for faster programming rather than a polished, production-ready library. The author is open to questions via email but has not yet implemented formal documentation.

Use it for:

• Quickly save and load Python objects to disk using pickle without writing boilerplate serialization code.
• Access pre-built scikit-learn metrics helpers with named axis parameters (axis_ref, axis_bias) for convenience.
• Explore PyTorch optimization utilities bundled under tools.torch.optim for common training patterns.
• Use inline-documented utility functions for ad-hoc data manipulation and syntax shortcuts during development.
• Extend or customize the toolkit by reading inline code comments and adapting functions to your workflow.

Worth the install?

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

A collection of Python utility functions for common programming tasks, including pickle serialization, data manipulation, and optional API-specific tools for libraries like scikit-learn and PyTorch.

Yes, if you want lightweight utility functions with zero external dependencies and don't mind reading source code to understand what's available. No, if you require formal documentation, API stability guarantees, or production-grade support. The package is actively maintained and permissively licensed, but its undocumented nature and small user base (3 GitHub stars) make it best suited for personal projects or as a reference implementation rather than a dependency for critical systems.

Install

tools on PyPI

pip install tools

uv add tools

poetry add tools

Installing tools

Before you install

Low install friction with no runtime dependencies. Active maintenance as of 2026-08-13, though the package is minimally documented and relies on inline code comments rather than formal docs.

License in practice

MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open and closed projects.

Quickstart

pip install tools

import tools as T
T.save_pickle(data, 'data.p')
data = T.load_pickle('data.p')

Requires Python 3.6 or later. API-specific submodules (e.g., tools.torch, tools.sklearn) require those libraries to be installed separately.

Verify before relying

• Whether undocumented functions are stable or subject to breaking changes between releases
• Scope and completeness of API-specific tool coverage (torch.optim, sklearn.metrics, etc.)
• Whether the package is actively maintained beyond the single recent commit shown

Package facts

Evidence: tools-1.0.32-py3-none-any.whl

Tags

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