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pylyzer ⚡#

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

Installation#

cargo (rust package manager)#

cargo install pylyzer

pip#

pip install pylyzer

If installed this way, you also need to install Erg.

curl -L https://github.com/mtshiba/ergup/raw/main/ergup.py | python3

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

  • Performance 🌟

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

  • Detailed analysis 🩺

pylyzer can do more than the type checking. For example, it can detect out-of-bounds accesses to lists and accesses to nonexistent keys in dicts.

analysis

  • Reports readability 📖

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

pylyzer 😃#

report

pyright 🙃#

pyright_report

  • Rich LSP support 📝

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#

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#

  • pylyzer's type inspector only assumes (potentially) statically typed code, so you cannot check any code uses reflections, such as exec, setattr, etc.

  • pylyzer (= Erg's type system) has its own type declarations for the Python standard APIs. Typing of all APIs is not complete and may result in an error that such an API does not exist.

TODOs#

  • type checking
  • variable
  • operator
  • function/method
  • class
  • type inference
  • variable
  • operator
  • function/method
  • class
  • builtin modules resolving (partially)
  • local scripts resolving
  • local packages resolving
  • compound type checking
  • Union
  • Optional
  • list
  • dict
  • tuple
  • Literal
  • TypedDict
  • others
  • type variable (TypeVar, Generic)
  • Protocol
  • Final
  • Annotated
  • TypeAlias
  • type assertion (typing.cast)
  • type narrowing (is, isinstance)
  • type guard (TypeGuard)

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.↩