DHParser - Rapid prototyping of formal grammars and domain specific languages (DSL) in the Digital Humanities. See https://dhparser.readthedocs.io/en/latest/
This software is open source software under the Apache 2.0-License (see section License, below).
Copyright 2016-2025 Eckhart Arnold, Bavarian Academy of Sciences and Humanities
DHParser is a parser development-framwork that has been developed with three main purposes in mind:
Developing parsers for domain specific languages and notations, either existing notations, like, LaTeX, or newly created DSLs, like the Medieval-Latin-Dictionary-DSL.
Typically, these languages are strict formal languages the grammar of which can be described with context-free grammars. (In cases where this does not hold like TeX, it is often still possible to describe a reasonably large subset of the formal language with a context free grammar.)
Developing parsers for semi-structured or informally structured text-data.
This kind of data is typically what you get when retro-digitizing textual data like printed bibliographies, or reference works or dictionaries. Often such works can be captured with a formal grammar, but these grammars require a lot of iterations and tests to develop and usually become much more ramified than the grammars of well-designed formal languages. Thus, DHParser's elaborated testing and debugging-framework for grammars.
(See Florian Zacherl's Dissertation on the retro-digitalization of dictionary data for an interesting case study. I am confident that the development of a suitable formal grammar is much easier with an elaborated framework like DHParser than with the PHP-parsing-expression-grammar-kit that Florian Zacherl has used.)
Developing processing-pipelines for tree-structured data.
In typical digital humanities applications one wants to produce different forms of output (say, printed, online-human-readable, online-machine-readable) from one and the same source of data. Therefore, the parsing stage (if the data source is structured text-data) will be followed by more or less intricate bifurcated processing pipelines.
Memoizing packrat-parser based on Parsing Expression Grammars. This means:
Linear parsing time
Any EBNF-grammar supported, including left-recursive grammars (via "seed and grow"-algorithm)
Unlimited look ahead and look behind
Macros to avoid code-repetition within grammars
Declarative tree-transformations for post-processing syntax-trees
Unit testing framework and post-mortem-debuger for test-driven grammar development and rapid-prototyping of grammars
Customizable error reporting, recovery after syntax errors and support for fail-tolerant parsers
Support for Language-servers
Workflow-support and data-processing-pipelines
XML-support like mapping flat-text to the DOM-tree ("node-tree" in DHParser's terminology) and adding markup in arbitrary places, even if this requires splitting tags.
Full Unicode support
No dependencies except the Python Standard Library
Extensive documentation and examples
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 www.w3.org/TR/xml/:
$ dhparser examples/XML/XML_W3C_SPEC.ebnf
This command produces a Python-Script XML_W3C_SPECParser.py 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/XML_W3C_SPECParser.py 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/XMLParser.py 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.)
key_value_store.py:
#!/usr/bin/env python
# A mini-DSL for a key value store
from DHParser.dsl import create_parser
# specify the grammar of your DSL in EBNF-notation
grammar = '''@ drop = whitespace, strings
key_store = ~ { entry }
entry = key "="~ value # ~ means: insignificant whitespace
key = /\w+/~ # Scanner-less 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 data.select('entry'):
print(entry['key'], entry['value'])
title "Odysee 2001"
director "Stanley Kubrick"
Or, serialize as XML:
>>> print(data.as_xml())
<key_store>
<entry>
<key>title</key>
<value>"Odysee 2001"</value>
</entry>
<entry>
<key>director</key>
<value>"Stanley Kubrick"</value>
</entry>
</key_store>
Set up DSL-projects with unit-tests for long-term-development:
For larger projects that require testing and incremental grammar development, use:
$ dhparser NEW_PROJECT_NAME
to set up 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 pypi.org:
python -m pip install --user DHParser
Alternatively, you can clone the latest version from gitlab.lrz.de/badw-it/DHParser
And these are the steps, if you want set up a DHParser-Project with the latest DHParser-development version:
$ git clone --depth=1 --branch development https://gitlab.lrz.de/badw-it/DHParser
$ python3 DHParser/DHParser/scripts/dhparser.py MyNewParserProject
$ ln -s ../DHParser/DHParser MyNewParserProject/DHParser
$ cd MyNewParserProject
See Introduction.md for the motivation and an overview how DHParser works or jump right into the Step by Step Guide to learn how to set up 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.readthedocs.io
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
https://www.apache.org/licenses/LICENSE-2.0
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.
DHParser includes the following third-party-software:
typing_extensions: needed for backwards compatibility with older Python versions. Licensed under the Python Software Foundation License
shadow_cython: a single module from Cython to avoid error-messages resulting from the use of the cython-decorators when cython is not installed on the system using DHParser. License: Apache 2.0 License
The following are only needed for building the documentation:
Sphinx book theme: Makes the documentation look better than the built-in sphinx-themes. License: BSD 3-clause license
pydata sphinx theme: Nedded by sphinx_book_theme, also licensed under the BSD 3-clause license.
beautifulsoup4: Needed by by pydata_sphinx_theme, licensed unter the MIT-License
soupsive: Needed by Beautifulsoup, licensed unter the MIT-License
It is recommended that you install the regex-module
(https://bitbucket.org/mrabarnett/mrab-regex). 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. Cython version 3.0 or higher is required to compile DHParser. Type:
pip install cython
on the command-line to install cython. Once cython has been built and installed, you can run the "dhparser_cythonize"-script from the command line:
dhparser_cythonize
On Linux-systems, in case you want to use clang instead of the gcc-compiler, type:
export CC=/usr/bin/clang; dhparser_cythonize
Using clang may also help to circumvent C-errors like "incompatible pointer types".
The Cython-compiled version is about 2-3 times faster than the
CPython-interpreted version. Compiling can take quite a while.
If you are in a hurry, you can just can also just call
dhparser_cythonize_stringview which just compiles the
stringview-module, which profits the most from being "cythonized".
Depending on the use case, e.g. when parsing large files, PyPy3 yields even greater speed-ups. However, in other cases pypy can also be noticeably slower than cpython! To circumvent the longer startup times of pypy3 in comparison to CPython, it is recommended to use the xxxServer.py-scripts rather than calling the xxxParser.py-script each time when parsing many documents subsequently.
Another way to speed up your parser is by adding "@ optimizations = all" at the beginning of your EBNF-grammar-file. DHParser then tries to compile (some) non-recursive parts of your grammar to entirely to regular rexpressions which yields a 10-20% speedup. Beware that this option is still experimental!
Find the sources on gitlab.lrz.de/badw-it/DHParser . Get them with:
git clone https://gitlab.lrz.de/badw-it/DHParser
There exists a mirror of this repository on Github: https://github.com/jecki/DHParser Be aware, though, that the github-mirror may occasionally lag behind a few commits.
DHParser uses Poetry for packaging and dependency-management. In order to build a package from the sources, type:
poetry build
on the command line. The packages will then appear in the "dist" subdirectory.
Author: Eckhart Arnold, Bavarian Academy of Sciences Email: arnold@badw.de
If you use DHParser for Scientific Work, then please cite it as:
DHParser. A Parser-Generator for Digital-Humanities-Applications,
Division for Digital Humanities Research & Development, Bavarian Academy of Science and Technology,
Munich Germany 2017-2025, https://gitlab.lrz.de/badw-it/dhparser
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: tiny.badw.de/2JVT
Brian Ford: Parsing Expression Grammars: A Recognition-Based Syntactic Foundation, Cambridge Massachusetts, 2004. Short-URL:t1p.de/jihs
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, dotat.at/tmp/gll.pdf
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: t1p.de/bm3k
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: t1p.de/7jzh
Dominikus Herzberg: Uniform Syntax, Blog-Post, February, 27th 2007 on denkspuren. gedanken, ideen, anregungen und links rund um informatik-themen, short-URL: t1p.de/s0zk
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. commonmark.org
Stefan Müller: DSLs in den digitalen Geisteswissenschaften, Präsentation auf dem dhmuc-Workshop: Digitale Editionen und Auszeichnungssprachen, München 2016. Short-URL: tiny.badw.de/2JVy
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. dslbook.org/
Christopher Seaton: A Programming Language Where the Syntax and Semantics are Mutuable at Runtime, University of Bristol 2007, chrisseaton.com/katahdin/katahdin.pdf
Vegard Øye: General Parser Combinators in Racket, 2012, epsil.github.io/gll/
and many more...
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Parser Generator and DSL-construction-kit
We found that DHParser demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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