Pros of pfff

• Supports multiple programming languages (OCaml, PHP, JavaScript, Java, C++, etc.)
• Offers a wide range of code analysis tools and visualizations
• Provides a framework for building custom static analysis tools

Cons of pfff

• Less actively maintained (last commit in 2019)
• More complex setup and usage due to its comprehensive nature
• Steeper learning curve for users unfamiliar with OCaml

Code Comparison

pfff (OCaml):

let parse_program file =
  let ast = Parse_php.parse_program file in
  ast

Undebt (Python):

def parse_grammar(grammar):
    return Grammar(grammar)

Summary

pfff is a more comprehensive tool supporting multiple languages and offering various code analysis features. However, it's less actively maintained and has a steeper learning curve. Undebt, on the other hand, focuses specifically on automated code refactoring in Python, making it simpler to use for its intended purpose but less versatile overall.

Both tools serve different needs: pfff is better suited for large-scale code analysis across multiple languages, while Undebt excels at targeted Python refactoring tasks. The choice between them depends on the specific requirements of the project and the user's familiarity with the respective technologies.

Pros of YAPF

• More comprehensive code formatting capabilities, covering a wide range of Python syntax
• Highly configurable with style options to match different coding standards
• Actively maintained with regular updates and improvements

Cons of YAPF

• Focuses solely on Python, while Undebt supports multiple languages
• May require more configuration to achieve desired formatting results
• Can be slower for large codebases compared to Undebt's targeted approach

Code Comparison

YAPF example:

def long_function_name(
    var_one, var_two, var_three,
    var_four):
    print(var_one)

Undebt example (pattern file):

grammar = [
    (Literal("def") + NAME + LP + Optional(PARAMS) + RP + COLON,
     Literal("def") + NAME + LP + Optional(PARAMS) + RP + COLON + NEWLINE + INDENT)
]

YAPF provides a more straightforward approach to formatting entire Python files, while Undebt requires defining specific patterns for targeted code modifications. YAPF offers greater flexibility in formatting options, but Undebt's pattern-based approach allows for more precise control over specific code changes across multiple languages.

Pros of Black

• Opinionated and consistent formatting, reducing debates over code style
• Widely adopted in the Python community, with integration in many IDEs and CI tools
• Faster execution time for formatting large codebases

Cons of Black

• Less flexible than Undebt, with fewer customization options
• Limited to Python, while Undebt supports multiple languages
• May make significant changes to existing code formatting

Code Comparison

Black:

def long_function_name(
    var_one, var_two, var_three, var_four
):
    print(var_one)

Undebt:

def long_function_name(var_one,
                       var_two,
                       var_three,
                       var_four):
    print(var_one)

Black enforces a specific style, while Undebt allows for more flexibility in formatting. Black's output is more compact, but Undebt's can be customized to match existing project styles.

Both tools aim to improve code quality and consistency, but they approach the task differently. Black is focused on Python and provides a standardized format, while Undebt offers more versatility across languages and formatting options. The choice between them depends on project requirements and team preferences.

Pros of pyupgrade

• Specifically designed for Python code modernization
• Actively maintained with frequent updates
• Supports a wide range of Python versions (2.7 to 3.10+)

Cons of pyupgrade

• Limited to Python language upgrades
• Requires manual application of changes
• May not handle complex refactoring scenarios

Code Comparison

pyupgrade example:

# Before
x = dict((a, b) for a, b in some_iterable)

# After
x = {a: b for a, b in some_iterable}

Undebt example:

# Before
def old_function(arg1, arg2):
    return arg1 + arg2

# After
def new_function(arg1: int, arg2: int) -> int:
    return arg1 + arg2

Summary

pyupgrade focuses on modernizing Python code syntax, while Undebt is a more general-purpose refactoring tool. pyupgrade excels in Python-specific upgrades but lacks broader refactoring capabilities. Undebt offers more flexibility for various languages and complex transformations but requires more setup and configuration. Choose pyupgrade for quick Python modernization tasks, and consider Undebt for more extensive refactoring projects across multiple languages.