tools
python syntax tool
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.6 or later.
- API-specific submodules (e.g., tools.torch, tools.sklearn) require those libraries to be installed separately.
- Low install friction with no runtime dependencies.
License · maintenance · safety
permissive license (permissive) — MIT license permits free use, modification, and distribution with minimal restrictions, making it suitable for both open and closed projects.
last release 2026-08-13 (1 days) · last repo commit 2026-08-13 · 3 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 147,661 downloads/mo, #11,055 on PyPI
Alternatives
Verify before relying
pip install tools
import tools as T
T.save_pickle(data, 'data.p')
data = T.load_pickle('data.p')- 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
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 on it.
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
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.
Requires Python 3.6 or later. API-specific submodules (e.g., tools.torch, tools.sklearn) require those libraries to be installed separately.
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')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
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 1 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 147,661 / month, #11,055 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: tools-1.0.32-py3-none-any.whl
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See also torch-einops-utils · dictknife · cloudpickle · scikit-learn · bpyutils · shutils · english · sphinxcontrib-serializinghtml · oslo.utils · wimpy