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Parser Generator and DSL-construction-kit

Project description


DHParser - A parser generator and domain specific language (DSL) construction kit for the Digital Humanities


  • Handles all context-free grammars; based on Parsing Expression Grammars, but with added support for left-recursive grammars

  • Full unicode support

  • Unit testing framework and post-mortem debugger for grammars

  • Customizable error reporting

  • Customizable recovery after syntax errors and support for fail-tolerant parsers

  • Support for Language-servers

  • Digital Humanities features, like support for XML-workflows

  • no mandatory dependencies other than the Python Standard Library

  • Soon to come: Extensive documentation and documented examples

Ease of use

Directly compile existing EBNF-grammars:

DHParser recognizes various dialects of EBNF or PEG-syntax for specifying grammars. For any already given grammar-specification in EBNF or PEG, it is not unlikely that DHParser can generate a parser either right away or with only minor changes or additions.

You can try this by compiling the file XML_W3C_SPEC.ebnf in the examples/XML of the source-tree which contains the official XML-grammar directly extracted from

$ dhparser examples/XML/XML_W3C_SPEC.ebnf

This command produces a Python-Skript in the same directory as the EBNF-file. This file can be run on any XML-file and will yield its concrete syntax tree, e.g.:

$ python examples/XML/ examples/XML/example.xml

Note, that the concrete syntax tree of an XML file as returned by the generated parser is not the same as the data-tree encoded by that very XML-file. In order to receive the data tree, further transformations are necessary. See examples/XML/ for an example of how this can be done.

Use (small) grammars on the fly in Python code:

Small grammars can also directly be compiled from Python-code. (Here, we use DHParser's preferred syntax which does not require trailing semicolons and uses the tilde ~ as a special sign to denote "insignificant" whitespace.)

#!/usr/bin/env python 
# A mini-DSL for a key value store
from DHParser import *

# specify the grammar of your DSL in EBNF-notation
grammar = '''@ drop = whitespace, strings
key_store   = ~ { entry }
entry       = key "="~ value          # ~ means: insignificant whitespace 
key         = /\w+/~                  # Scannerless parsing: Use regular
value       = /\"[^"\n]*\"/~          # expressions wherever you like'''

# generating a parser is almost as simple as compiling a regular expression
parser = create_parser(grammar)       # parser factory for thread-safety

Now, parse some text and extract the data from the Python-shell:

>>> from key_value_store import parser
>>> text = '''
        title    = "Odysee 2001"
        director = "Stanley Kubrick"
>>> data = parser(text)
>>> for entry in'entry'):
        print(entry['key'], entry['value'])

title "Odysee 2001"
director "Stanley Kubrick"

Or, serialize as XML:

>>> print(data.as_xml())

    <value>"Odysee 2001"</value>
    <value>"Stanley Kubrick"</value>

Set up DSL-projects with unit-tests for long-term-development:

For larger projects that require testing and incremental grammar development, use:


to setup a project-directory with all the scaffolding for a new DSL-project, including the full unit-testing-framework.


You can install DHParser from the Python package index

python -m pip install --user DHParser

Alternatively, you can clone the latest version from

Getting Started

See for the motivation and an overview how DHParser works or jump right into the Step by Step Guide to learn how to setup and use DHParser. Or have a look at the comprehensive overview of DHParser's features to see how DHParser supports the construction of domain specific languages.


For the full documentation see:


DHParser is open source software under the Apache 2.0 License.

Copyright 2016-2022 Eckhart Arnold, Bavarian Academy of Sciences and Humanities

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Optional Post-Installation

It is recommended that you install the regex-module ( If present, DHParser will use regex instead of the built-in re-module for regular expressions. regex is faster and more powerful than re.

In order to speed up DHParser even more, it can be compiled with the Python to C compiler Cython. First, you mustt install cython with the command:

pip install cython

Once cython is installed, you can run the dhparser_build_cython script from the command line:


Alternatively, if you have cloned DHParser from the git-Repository, you can run the (or buildpackages.bat on Windows-systems) after installation.

The Cython-compiled version is about 2-3 times faster than the CPython interpreted version.

Depending on the use case, e.g. when parsing large files, PyPy3 yields even more impressive speed-ups, up to 8 times faster than CPython. To circumvent the longer startup times of pypy3 in comparison to CPython, it is recommended to use the rather than calling the each time when parsing many documents subsequently.


Find the sources on . Get them with:

git clone

There exists a mirror of this repository on github: Be aware, though, that the github-mirror may occasionally lag behind a few commits.


DHParser is a parser-combinator-based parsing and compiling infrastructure for domain specific languages (DSL) in Digital Humanities projects. It leverages the power of Domain specific languages for the Digital Humanities.

Domain specific languages are widespread in computer sciences, but seem to be underused in the Digital Humanities. While DSLs are sometimes introduced to Digital-Humanities-projects as practical adhoc-solution, these solutions are often somewhat "quick and dirty". In other words they are more of a hack than a technology. The purpose of DHParser is to introduce DSLs as a technology to the Digital Humanities. It is based on the well known technology of EBNF-based parser generators, but employs the more modern form called "parsing expression grammar" and parser combinators as a variant of the classical recursive descent parser.

Why another parser generator? There are plenty of good parser generators out there, e.g. Añez's grako parser generator, Eclipse XText. However, DHParser is intended as a tool that is specifically geared towards digital humanities applications, while most existing parser generators come from compiler construction toolkits for programming languages. While I expect DSLs in computer science and DSLs in the Digital Humanities to be quite similar as far as the technological realization is concerned, the use cases, requirements and challenges are somewhat different. For example, in the humanities annotating text is a central use case, which is mostly absent in computer science treatments. These differences might sooner or later require to develop the DSL-construction toolkits in a different direction. Also DHParser emphasizes and evolutionary development model for grammars with unit-testing support, which fits the typical use cases in DH where DSLs evolve in a discussion process between technicians and humanists. Because the users of DSLs in the humanities are not necessarily very technically minded people, DHParser supports the construction of fail-tolerant parsers with good error reporting in terms of locating the errors at the right spot and giving useful error messages.

Also, DHParser shall (in the future) serve as a teaching tool, which influences some of its design decisions such as, for example, clearly separating the parsing, syntax-tree-transformation and compilation stages. Finally, DHParser is intended as a tool to experiment with. One possible research area is, how non context-free grammars such as the grammars of TeX or CommonMark can be described with declarative langauges in the spirit of but beyond EBNF, and what extensions of the parsing technology are necessary to capture such languages.

Primary use case at the Bavarian Academy of Sciences and Humanities (for the time being): A DSL for the "Mittellateinische Wörterbuch"!

Further (intended) use cases are:

  • LaTeX -> XML/HTML conversion. See this discussion on why an EBNF-parser for the complete TeX/LaTeX-grammar is not possible.
  • CommonMark and other DSLs for cross media publishing of scientific literature, e.g. journal articles. (Common Mark and Markdown also go beyond what is feasible with pure EBNF-based-parsers.)
  • EBNF itself. DHParser is already self-hosting ;-)
  • XML-parser, just for the fun of it ;-)
  • Digital and cross-media editions
  • Digital dictionaries

For a simple self-test run from the command line. This compiles the EBNF-Grammar in examples/EBNF/EBNF.ebnf and outputs the Python-based parser class representing that grammar. The concrete and abstract syntax tree as well as a full and abbreviated log of the parsing process will be stored in a subdirectory named "LOG".


Author: Eckhart Arnold, Bavarian Academy of Sciences Email:

References and Acknowledgement

Juancarlo Añez: grako, a PEG parser generator in Python, 2017. URL:

Eckhart Arnold: Domänenspezifische Notationen. Eine (noch) unterschätzte Technologie in den Digitalen Geisteswissenschaften, Präsentation auf dem dhmuc-Workshop: Digitale Editionen und Auszeichnungssprachen, München 2016. Short-URL:

Brian Ford: Parsing Expression Grammars: A Recognition-Based Syntactic Foundation, Cambridge Massachusetts, 2004.

Richard A. Frost, Rahmatullah Hafiz and Paul Callaghan: Parser Combinators for Ambiguous Left-Recursive Grammars, in: P. Hudak and D.S. Warren (Eds.): PADL 2008, LNCS 4902, pp. 167–181, Springer-Verlag Berlin Heidelberg 2008.

Elizabeth Scott and Adrian Johnstone, GLL Parsing, in: Electronic Notes in Theoretical Computer Science 253 (2010) 177–189,

Dominikus Herzberg: Objekt-orientierte Parser-Kombinatoren in Python, Blog-Post, September, 18th 2008 on denkspuren. gedanken, ideen, anregungen und links rund um informatik-themen, short-URL:

Dominikus Herzberg: Eine einfache Grammatik für LaTeX, Blog-Post, September, 18th 2008 on denkspuren. gedanken, ideen, anregungen und links rund um informatik-themen, short-URL:

Dominikus Herzberg: Uniform Syntax, Blog-Post, February, 27th 2007 on denkspuren. gedanken, ideen, anregungen und links rund um informatik-themen, short-URL:

John MacFarlane, David Greenspan, Vicent Marti, Neil Williams, Benjamin Dumke-von der Ehe, Jeff Atwood: CommonMark. A strongly defined, highly compatible specification of Markdown, 2017.

Stefan Müller: DSLs in den digitalen Geisteswissenschaften, Präsentation auf dem dhmuc-Workshop: Digitale Editionen und Auszeichnungssprachen, München 2016. Short-URL:

Markus Voelter, Sbastian Benz, Christian Dietrich, Birgit Engelmann, Mats Helander, Lennart Kats, Eelco Visser, Guido Wachsmuth: DSL Engineering. Designing, Implementing and Using Domain-Specific Languages, 2013.

Christopher Seaton: A Programming Language Where the Syntax and Semantics are Mutuable at Runtime, University of Bristol 2007,

Vegard Øye: General Parser Combinators in Racket, 2012,

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