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TatSu takes a grammar in a variation of EBNF as input, and outputs a memoizing PEG/Packrat parser in Python.

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At least for the people who send me mail about a new language that they’re designing, the general advice is: do it to learn about how to write a compiler. Don’t have any expectations that anyone will use it, unless you hook up with some sort of organization in a position to push it hard. It’s a lottery, and some can buy a lot of the tickets. There are plenty of beautiful languages (more beautiful than C) that didn’t catch on. But someone does win the lottery, and doing a language at least teaches you something.

Dennis Ritchie (1941-2011) Creator of the C programming language and of Unix


def WARNING():
    TatSu>=5.6 requires Python>=3.8
    TatSu>=5.7 will require Python>=3.9

    Python 3.8 and 3.9 introduced new language features that allow
    writing better programs more clearly. All code written for
    Python 3.7 should run fine on Python 3.9 with minor, or no changes.

    Python has adopted an annual release schedule (PEP-602).

    Python 3.10 will be released in Oct 2021
    Python 3.9  was released on Oct 20220
    Python 3.8  bugfix releases final in May 2021
    Python 3.7  bugfix releases final in mid 2020
    Python 3.6  had its last bugfix release on Dec 2019
    Python 2.7  reached its end of life on Jan 2020

    Compelling reasons to upgrade projects to the latest Python

TatSu is a tool that takes grammars in a variation of EBNF as input, and outputs memoizing (Packrat) PEG parsers in Python.

TatSu can compile a grammar stored in a string into a tatsu.grammars.Grammar object that can be used to parse any given input, much like the re module does with regular expressions, or it can generate a Python module that implements the parser.

TatSu supports left-recursive rules in PEG grammars using the algorithm by Laurent and Mens. The generated AST has the expected left associativity.


$ pip install TatSu

Using the Tool

TatSu can be used as a library, much like Python’s re, by embedding grammars as strings and generating grammar models instead of generating Python code.

  • tatsu.compile(grammar, name=None, **kwargs)

    Compiles the grammar and generates a model that can subsequently be used for parsing input with.

  • tatsu.parse(grammar, input, **kwargs)

    Compiles the grammar and parses the given input producing an AST as result. The result is equivalent to calling:

    model = compile(grammar)
    ast = model.parse(input)

    Compiled grammars are cached for efficiency.

  • tatsu.to_python_sourcecode(grammar, name=None, filename=None, **kwargs)

    Compiles the grammar to the Python sourcecode that implements the parser.

This is an example of how to use 竜 TatSu as a library:


    start = expression $ ;

        | expression '+' term
        | expression '-' term
        | term

        | term '*' factor
        | term '/' factor
        | factor

        | '(' expression ')'
        | number

    number = /\d+/ ;

if __name__ == '__main__':
    import json
    from tatsu import parse
    from tatsu.util import asjson

    ast = parse(GRAMMAR, '3 + 5 * ( 10 - 20 )')
    print(json.dumps(asjson(ast), indent=2))

TatSu will use the first rule defined in the grammar as the start rule.

This is the output:



For a detailed explanation of what 竜 TatSu is capable of, please see the documentation.


Please use the [tatsu] tag on StackOverflow for general Q&A, and limit Github issues to bugs, enhancement proposals, and feature requests.


See the CHANGELOG for details.


You may use 竜 TatSu under the terms of the BSD-style license described in the enclosed LICENSE.txt file. If your project requires different licensing please email.

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