---
id: pyparsing
version: "3.3.2"
license: MIT
license_treatment: permissive
maintenance: active
---

# pyparsing — pyparsing - Classes and methods to define and execute parsing grammars

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install pyparsing
uv add pyparsing
poetry add pyparsing

## Description

PyParsing -- A Python Parsing Module
====================================

|Version| |Build Status| |Coverage| |License| |Python Versions| |Snyk Score|

Introduction
============

The pyparsing module is an alternative approach to creating and
executing simple grammars, vs. the traditional lex/yacc approach, or the
use of regular expressions. The pyparsing module provides a library of
classes that client code uses to construct the grammar directly in
Python code.

*[Since first writing this description of pyparsing in late 2003, this
technique for developing parsers has become more widespread, under the
name Parsing Expression Grammars - PEGs. See more information on PEGs*
`here <https://en.wikipedia.org/wiki/Parsing_expression_grammar>`__
*.]*

Here is a program to parse ``"Hello, World!"`` (or any greeting of the form
``"salutation, addressee!"``):

.. code:: python

    from pyparsing import Word, alphas
    greet = Word(alphas) + "," + Word(alphas) + "!"
    hello = "Hello, World!"
    print(hello, "->", greet.parse_string(hello))

The program outputs the following::

    Hello, World! -> ['Hello', ',', 'World', '!']

The Python representation of the grammar is quite...

## AI interpretation — verify before relying

pyparsing provides a Python library for building and executing text parsing grammars directly in code, handling common parsing challenges like whitespace variation, quoted strings, and comments without requiring traditional lex/yacc tools.

Verdict: pyparsing is a mature, well-maintained parsing library with no known vulnerabilities, zero dependencies, and permissive licensing. It is suitable for production use across a wide range of text-parsing tasks from simple grammars to complex domain-specific languages.

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