search

erikrose / parsimonious

The fastest pure-Python PEG parser I can muster
MIT License
1.81k stars 127 forks source link

readme

============ 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

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

Coming Soon

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 of the built-in re module.

~br"regex" A bytes regex; required if your grammar parses bytestrings.

(things) Parentheses are used for grouping, like in every other language.

thing{n} Exactly n repetitions of thing.

thing{n,m} Between n and m repititions (inclusive.)

thing{,m} At most m repetitions of thing.

thing{n,} At least n repetitions of thing.

==================== ========================================================

.. _flags: https://docs.python.org/3/howto/regex.html#compilation .. _regex: https://github.com/mrabarnett/mrab-regex

Optimizing Grammars

Don't Repeat Expressions

If you need a ~"[a-z0-9]"i at two points in your grammar, don't type it twice. Make it a rule of its own, and reference it from wherever you need it. You'll get the most out of the caching this way, since cache lookups are by expression object identity (for speed).

Even if you have an expression that's very simple, not repeating it will save RAM, as there can, at worst, be a cached int for every char in the text you're parsing. In the future, we may identify repeated subexpressions automatically and factor them up while building the grammar.

How much should you shove into one regex, versus how much should you break them up to not repeat yourself? That's a fine balance and worthy of benchmarking. More stuff jammed into a regex will execute faster, because it doesn't have to run any Python between pieces, but a broken-up one will give better cache performance if the individual pieces are re-used elsewhere. If the pieces of a regex aren't used anywhere else, by all means keep the whole thing together.

Quantifiers

Bring your ? and * quantifiers up to the highest level you can. Otherwise, lower-level patterns could succeed but be empty and put a bunch of useless nodes in your tree that didn't really match anything.

Processing Parse Trees

A parse tree has a node for each expression matched, even if it matched a zero-length string, like "thing"? might.

The NodeVisitor class provides an inversion-of-control framework for walking a tree and returning a new construct (tree, string, or whatever) based on it. For now, have a look at its docstrings for more detail. There's also a good example in grammar.RuleVisitor. Notice how we take advantage of nodes' iterability by using tuple unpacks in the formal parameter lists:

.. code:: python

def visit_or_term(self, or_term, (slash, _, term)):
    ...

For reference, here is the production the above unpacks::

or_term = "/" _ term

When something goes wrong in your visitor, you get a nice error like this::

[normal traceback here...]
VisitationException: 'Node' object has no attribute 'foo'

Parse tree:
<Node called "rules" matching "number = ~"[0-9]+"">  <-- *** We were here. ***
    <Node matching "number = ~"[0-9]+"">
        <Node called "rule" matching "number = ~"[0-9]+"">
            <Node matching "">
            <Node called "label" matching "number">
            <Node matching " ">
                <Node called "_" matching " ">
            <Node matching "=">
            <Node matching " ">
                <Node called "_" matching " ">
            <Node called "rhs" matching "~"[0-9]+"">
                <Node called "term" matching "~"[0-9]+"">
                    <Node called "atom" matching "~"[0-9]+"">
                        <Node called "regex" matching "~"[0-9]+"">
                            <Node matching "~">
                            <Node called "literal" matching ""[0-9]+"">
                            <Node matching "">
            <Node matching "">
            <Node called "eol" matching "
            ">
    <Node matching "">

The parse tree is tacked onto the exception, and the node whose visitor method raised the error is pointed out.

Why No Streaming Tree Processing?

Some have asked why we don't process the tree as we go, SAX-style. There are two main reasons:

  1. It wouldn't work. With a PEG parser, no parsing decision is final until the whole text is parsed. If we had to change a decision, we'd have to backtrack and redo the SAX-style interpretation as well, which would involve reconstituting part of the AST and quite possibly scuttling whatever you were doing with the streaming output. (Note that some bursty SAX-style processing may be possible in the future if we use cuts.)

  2. It interferes with the ability to derive multiple representations from the AST: for example, turning wiki markup into first HTML and then text.

Future Directions

Rule Syntax Changes

Optimizations

Niceties

Version History

(Next release)

0.10.0

0.9.0

0.8.1

0.8.0

0.7.0

0.6.2

0.6.1

0.6 .. warning::

  This release makes backward-incompatible changes:

  * The ``default_rule`` arg to Grammar's constructor has been replaced
    with a method, ``some_grammar.default('rule_name')``, which returns a
    new grammar just like the old except with its default rule changed.
    This is to free up the constructor kwargs for custom rules.
  * ``UndefinedLabel`` is no longer a subclass of ``VisitationError``. This
    matters only in the unlikely case that you were catching
    ``VisitationError`` exceptions and expecting to thus also catch
    ``UndefinedLabel``.

0.5 .. warning::

  This release makes some backward-incompatible changes. See below.

0.4

0.3

0.2

0.1

Thanks to Wiki Loves Monuments Panama for showing their support with a generous gift.