layercparse 0.2.2

Layered C parser

"Fat Token" Parser and Modularity Checker for C Code

This library provides a parser for C code that extracts tokens and checks the modularity of the code based on the rules defined in the Modularity document.

The core concept of the library is the "Fat Token" which represents a higher-level abstraction of elements in C code rather than a simple sequence of characters. A Fat Token can represent items such as "words", "comments", "strings", "expressions within parentheses", etc.

With this this higher-level representation, the library enables a layered approach to parsing, focusing on high level structures without getting bogged down in unnecessary details. The parser extracts Fat Tokens from the C code and groups them into "statements" representing logical units like function definitions, struct declarations, variable declarations, etc.

For example, a function definition might be represented as a sequence of: "comment", "word", "word", "expression in parentheses", and "expression in curly braces". We can recognize this as a function definition without needing to parse the internal details of the function body or arguments list.

This approach makes it possible to perform a variety of analyses on C code or other languages with clear syntax rules.

Implementation details are described in the Implementation document.

Installation

$ pip install layercparse

Usage

import os
from layercparse import *

def main():
    # setLogLevel(LogLevel.WARNING)
    setRootPath(os.path.realpath(sys.argv[1]))
    setModules([
        Module("module1"),
        Module("module2", fileAliases=["m2"], sourceAliases = ["mod2", "m2"]),
    ])

    code = Codebase()
    code.scanFiles(get_files(), twopass=True, multithread=True)
    AccessCheck(code).checkAccess(multithread=True)

    return not workspace.errors

if __name__ == "__main__":
    # When using multithreaded processing, it's criticak to check __name__
    # rather than doing things directly in the global scope.
    sys.exit(main())

Links

• This project on GitHub: layercparse.