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Automated Python refactoring

Project description

pyrefact

Pyrefact does advanced python refactoring, with the goal of simplifying complicated code, deleting dead code, and improving performance.

Pyrefact can break code, and is not suitable for your company's CI chain.

Features

Readability

  • Move common code in if/else blocks before or after the if/else.
  • De-indent code with early continue and return statements.
  • Replace for loops with immediate if conditions with filter.
  • Remove commented code.
  • Move code into primitive functions.
  • Replace loops that only fill up lists, dicts or sets with comprehensions.
  • Invert if/else to put the smaller block first.
  • Rename variables, functions and classes with conventions.
  • Rewrite defaultdict-like use of dictionaries with collections.defaultdict().
  • Formats lines that are longer than 100 characters with black.
  • Put overused constant expressions in variables.
  • Remove redundancies and improve definitions of lists, sets, dicts.
  • Use is instead of == for comparisons to None, True and False.

Performance

  • Replace sum comprehensions and for loops with constant expressions. The symbolic algebra tool Sympy is used under the hood.
  • Replace hardcoded inlined collections and comprehensions with set or generator equivalents in places where that would improve performance.
  • Replace sorted()[:n] with heapq.nsmallest, replace sorted()[0] with min.
  • Replace matrix operation comprehensions with equivalent np.matmul() and np.dot() calls, for code that already depends on numpy.
  • Replace pandas .loc[], .iloc[] and .iterrows() with .at[], .iat[] and .itertuples()/.index where appropriate.
  • Move constant code in loops before the loops.
  • De-interpolate interpolated logging calls.

Removing dead and useless code

  • Delete unused functions, classes and variables.
  • Remove most pointless simple statements.
  • Remove branches of code that obviously do nothing useful.
  • Remove unreachable code.
  • Rename unused variables to _.
  • Delete variables named _, unless where that would cause a syntax error.
  • Remove redundant chained calls involving sorted(), set(), tuple(), reversed(), iter() and list().
  • Remove duplicate function definitions.
  • Remove redundant elif and else.
  • Remove unused self and cls function arguments, and add @staticmethod or @classmethod.
  • Move functions decorated with @staticmethod outside of their class namespaces.
  • Simplify deterministic if, elif and else statements.

Imports

  • Delete unused imports.
  • Move builtin and otherwise safe imports to toplevel.
  • Add missing imports by guessing what you probably wanted.
    • For example, if Sequence is used but never defined, it will insert from typing import Sequence at the top of the file.

Cleanup

  • Run isort to organize imports.
  • Run black on added code, modified code, and lines that are longer than 100 characters.

Usage

The --preserve flag lets you define places where code is used. When this is set, pyrefact will try to keep these usages intact. The --safe flag will entirely prevent pyrefact from renaming or removing code. The --from-stdin flag will format code recieved from stdin, and output the result to stdout.

pip install pyrefact
pyrefact /path/to/filename.py --preserve /path/to/module/where/filename/is/used
pyrefact /path/to/filename.py --safe
cat /path/to/filename.py | pyrefact --from-stdin

VS Code Extension

Pyrefact is also available as a VS Code extension, simply named Pyrefact. The extension allows you to use pyrefact as your formatter, similar to how other formatting extensions work.

Pyrefact always runs with the --safe flag when used through the VS Code extension.

The extension is published through the VS Code Marketplace, and the source code is available at pyrefact-vscode-extension.

Prerequisites

CPython

Pyrefact requires python>=3.8, and is tested on CPython 3.8, 3.9, 3.10, 3.11 and 3.12. Pyrefact works best on python>=3.9.

Pypy

Pyrefact is supported and tested on Pypy3.9. Pypy3.8 is not supported. Pyrefact is slightly faster on Pypy3.9 than on CPython3.9, but only for large repos as the JIT compile overhead is otherwise too large to make up.

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