============ Parsimonious

Parsimonious aims to be the fastest arbitrary-lookahead parser written in pure Python—and the most usable. It's based on parsing expression grammars (PEGs), which means you feed it a simplified sort of EBNF notation. Parsimonious was designed to undergird a MediaWiki parser that wouldn't take 5 seconds or a GB of RAM to do one page, but it's applicable to all sorts of languages.

:Code: https://github.com/erikrose/parsimonious/ :Issues: https://github.com/erikrose/parsimonious/issues :License: MIT License (MIT) :Package: https://pypi.org/project/parsimonious/

Goals

• Speed
• Frugal RAM use
• Minimalistic, understandable, idiomatic Python code
• Readable grammars
• Extensible grammars
• Complete test coverage
• Separation of concerns. Some Python parsing kits mix recognition with instructions about how to turn the resulting tree into some kind of other representation. This is limiting when you want to do several different things with a tree: for example, render wiki markup to HTML or to text.
• Good error reporting. I want the parser to work with me as I develop a grammar.

Install

To install Parsimonious, run::

$ pip install parsimonious

Example Usage

Here's how to build a simple grammar:

.. code:: python

>>> from parsimonious.grammar import Grammar
>>> grammar = Grammar(
...     """
...     bold_text  = bold_open text bold_close
...     text       = ~"[A-Z 0-9]*"i
...     bold_open  = "(("
...     bold_close = "))"
...     """)

You can have forward references and even right recursion; it's all taken care of by the grammar compiler. The first rule is taken to be the default start symbol, but you can override that.

Next, let's parse something and get an abstract syntax tree:

.. code:: python

>>> print(grammar.parse('((bold stuff))'))
<Node called "bold_text" matching "((bold stuff))">
    <Node called "bold_open" matching "((">
    <RegexNode called "text" matching "bold stuff">
    <Node called "bold_close" matching "))">

You'd typically then use a nodes.NodeVisitor subclass (see below) to walk the tree and do something useful with it.

Another example would be to implement a parser for .ini-files. Consider the following:

.. code:: python

grammar = Grammar(
    r"""
    expr        = (entry / emptyline)*
    entry       = section pair*

    section     = lpar word rpar ws
    pair        = key equal value ws?

    key         = word+
    value       = (word / quoted)+
    word        = ~r"[-\w]+"
    quoted      = ~'"[^\"]+"'
    equal       = ws? "=" ws?
    lpar        = "["
    rpar        = "]"
    ws          = ~r"\s*"
    emptyline   = ws+
    """
)

We could now implement a subclass of NodeVisitor like so:

.. code:: python

class IniVisitor(NodeVisitor):
    def visit_expr(self, node, visited_children):
        """ Returns the overall output. """
        output = {}
        for child in visited_children:
            output.update(child[0])
        return output

    def visit_entry(self, node, visited_children):
        """ Makes a dict of the section (as key) and the key/value pairs. """
        key, values = visited_children
        return {key: dict(values)}

    def visit_section(self, node, visited_children):
        """ Gets the section name. """
        _, section, *_ = visited_children
        return section.text

    def visit_pair(self, node, visited_children):
        """ Gets each key/value pair, returns a tuple. """
        key, _, value, *_ = node.children
        return key.text, value.text

    def generic_visit(self, node, visited_children):
        """ The generic visit method. """
        return visited_children or node

And call it like that:

.. code:: python

from parsimonious.grammar import Grammar
from parsimonious.nodes import NodeVisitor

data = """[section]
somekey = somevalue
someotherkey=someothervalue

[anothersection]
key123 = "what the heck?"
key456="yet another one here"

"""

tree = grammar.parse(data)

iv = IniVisitor()
output = iv.visit(tree)
print(output)

This would yield

.. code:: python

{'section': {'somekey': 'somevalue', 'someotherkey': 'someothervalue'}, 'anothersection': {'key123': '"what the heck?"', 'key456': '"yet another one here"'}}

Status

• Everything that exists works. Test coverage is good.
• I don't plan on making any backward-incompatible changes to the rule syntax in the future, so you can write grammars with confidence.
• It may be slow and use a lot of RAM; I haven't measured either yet. However, I have yet to begin optimizing in earnest.
• Error reporting is now in place. repr methods of expressions, grammars, and nodes are clear and helpful as well. The Grammar ones are even round-trippable!
• The grammar extensibility story is underdeveloped at the moment. You should be able to extend a grammar by simply concatenating more rules onto the existing ones; later rules of the same name should override previous ones. However, this is untested and may not be the final story.
• Sphinx docs are coming, but the docstrings are quite useful now.
• Note that there may be API changes until we get to 1.0, so be sure to pin to the version you're using.

Coming Soon

• Optimizations to make Parsimonious worthy of its name
• Tighter RAM use
• Better-thought-out grammar extensibility story
• Amazing grammar debugging

A Little About PEG Parsers

PEG parsers don't draw a distinction between lexing and parsing; everything is done at once. As a result, there is no lookahead limit, as there is with, for instance, Yacc. And, due to both of these properties, PEG grammars are easier to write: they're basically just a more practical dialect of EBNF. With caching, they take O(grammar size * text length) memory (though I plan to do better), but they run in O(text length) time.

More Technically

PEGs can describe a superset of LL(k) languages, any deterministic LR(k) language, and many others—including some that aren't context-free (http://www.brynosaurus.com/pub/lang/peg.pdf). They can also deal with what would be ambiguous languages if described in canonical EBNF. They do this by trading the | alternation operator for the / operator, which works the same except that it makes priority explicit: a / b / c first tries matching a. If that fails, it tries b, and, failing that, moves on to c. Thus, ambiguity is resolved by always yielding the first successful recognition.

Writing Grammars

Grammars are defined by a series of rules. The syntax should be familiar to anyone who uses regexes or reads programming language manuals. An example will serve best:

.. code:: python

my_grammar = Grammar(r"""
    styled_text = bold_text / italic_text
    bold_text   = "((" text "))"
    italic_text = "''" text "''"
    text        = ~"[A-Z 0-9]*"i
    """)

You can wrap a rule across multiple lines if you like; the syntax is very forgiving.

If you want to save your grammar into a separate file, you should name it using .ppeg extension.

Syntax Reference

==================== ======================================================== "some literal" Used to quote literals. Backslash escaping and Python conventions for "raw" and Unicode strings help support fiddly characters.

b"some literal" A bytes literal. Using bytes literals and regular expressions allows your grammar to parse binary files. Note that all literals and regular expressions must be of the same type within a grammar. In grammars that process bytestrings, you should make the grammar string an r"""string""" so that byte literals like \xff work correctly.

[space] Sequences are made out of space- or tab-delimited things. a b c matches spots where those 3 terms appear in that order.

a / b / c Alternatives. The first to succeed of a / b / c wins.

thing? An optional expression. This is greedy, always consuming thing if it exists.

&thing A lookahead assertion. Ensures thing matches at the current position but does not consume it.

!thing A negative lookahead assertion. Matches if thing isn't found here. Doesn't consume any text.

things* Zero or more things. This is greedy, always consuming as many repetitions as it can.

things+ One or more things. This is greedy, always consuming as many repetitions as it can.

~r"regex"ilmsuxa Regexes have ~ in front and are quoted like literals. Any flags_ (asilmx) follow the end quotes as single chars. Regexes are good for representing character classes ([a-z0-9]) and optimizing for speed. The downside is that they won't be able to take advantage of our fancy debugging, once we get that working. Ultimately, I'd like to deprecate explicit regexes and instead have Parsimonious dynamically build them out of simpler primitives. Parsimonious uses the regex_ library instead