mtshiba / pylyzer

A fast static code analyzer & language server for Python
http://mtshiba.github.io/pylyzer/
MIT License
2.27k stars 33 forks source link
language-server python rust static-analysis type-checker

pylyzer ⚑

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pylyzer is a static code analyzer / language server for Python, written in Rust.

Installation

pip

pip install pylyzer

cargo (rust package manager)

cargo install pylyzer --locked

build from source

git clone https://github.com/mtshiba/pylyzer.git
cargo install --path . --locked

Make sure that cargo/rustc is up-to-date, as pylyzer may be written with the latest language features.

GitHub Releases

What is the advantage over pylint, pyright, pytype, etc.?

On average, pylyzer can inspect Python scripts more than 100 times faster than pytype and pyright 1. This is largely due to the fact that pylyzer is implemented in Rust.

performance

While pytype/pyright's error reports are illegible, pylyzer shows where the error occurred and provides clear error messages.

pylyzer πŸ˜ƒ

report

pyright πŸ™ƒ

pyright_report

pylyzer as a language server supports various features, such as completion and renaming (The language server is an adaptation of the Erg Language Server (ELS). For more information on the implemented features, please see here).

lsp_support

autoimport

VSCode extension

You can install the VSCode extension from the Marketplace or from the command line:

code --install-extension pylyzer.pylyzer

What is the difference from Ruff?

Ruff, like pylyzer, is a static code analysis tool for Python written in Rust, but Ruff is a linter and pylyzer is a type checker & language server. pylyzer does not perform linting, and Ruff does not perform type checking.

How it works

pylyzer uses the type checker of the Erg programming language internally. This language is a transpiled language that targets Python, and has a static type system.

pylyzer converts Python ASTs to Erg ASTs and passes them to Erg's type checker. It then displays the results with appropriate modifications.

Limitations

TODOs


1 The performance test was conducted on MacBook (Early 2016) with 1.1 GHz Intel Core m3 processor and 8 GB 1867 MHz LPDDR3 memory.↩