Python Script Minifier

The Python Minifier (powered by python-minifier) reduces a script's on-disk size by removing what the interpreter doesn't need and shortening names. By default it strips comments, renames local variables to short names, and removes type annotations. You can additionally remove docstrings, remove asserts, rename global names, hoist repeated literals, and combine imports — each is a toggle with a live byte-count and percentage-saved readout. In constrained targets like MicroPython firmware or serverless bundles, every kilobyte counts.

Most of these transforms preserve behavior, but not all are risk-free, which is why the tool exposes them separately rather than promising a single "safe" mode. Renaming local variables and stripping comments are safe. Renaming global names is aggressive — if another module imports one of those names, the rename breaks it (that option is off by default and labeled accordingly). Removing type annotations changes code that reads __annotations__ at runtime (dataclasses, pydantic, typing-based dispatch). Removing asserts drops assertion checks entirely. Review the output — especially with the aggressive options enabled — before you ship it.

Minifying Python is different from minifying JavaScript. JavaScript minifiers rename everything and collapse the file onto one line; Python can't collapse lines because indentation is syntax — the structure of your loops and functions lives in the leading whitespace — so the tool preserves that structure exactly. It still renames identifiers and removes docstrings and annotations, which is where most of the savings come from, but you won't reach JavaScript's ratios because the structural whitespace has to stay.

Minification isn't protection. Renaming makes a script harder for a casual reader, but the logic, control flow and string literals are all still present, and short names can be re-expanded by re-formatting. If your goal is to make the logic genuinely hard to reverse, that's the job of the AST obfuscator — identifier renaming plus string encryption, import hiding and control-flow flattening — which you can layer on top of minification. Our minification vs obfuscation guide explains the difference, and how to obfuscate Python code covers real source protection.

A practical workflow is to keep your fully commented source in version control as the thing you actually maintain, and treat the minified file as a build artifact you regenerate on each release rather than edit by hand. If you're deploying to a device or function where size is the binding constraint, minify last — after formatting and testing — so the code you validated is the code you ship.