Introduction to [DHParser](https://gitlab.lrz.de/badw-it/DHParser) ================================================================== *This is just an appetizer. Full documentation coming soon...* Motto: **Computers enjoy XML, humans don't.** Why use domain specific languages in the humanities? ---------------------------------------------------- Suppose you are a literary scientist and you would like to edit a poem like Heinrich Heine's "Lyrisches Intermezzo". Usually, the technology of choice would be XML and you would use an XML-Editor to write to code something like this: Heinrich Heine Buch der Lieder Hamburg 1927 Lyrisches Intermezzo IV. Wenn ich in deine Augen seh', so schwindet all' mein Leid und Weh! Doch wenn ich küsse deinen Mund, so werd' ich ganz und gar gesund. Wenn ich mich lehn' an deine Brust, kommt's über mich wie Himmelslust, doch wenn du sprichst: Ich liebe dich! so muß ich weinen bitterlich. Now, while you might think that this all works well enough, there are a few drawbacks to this approach: - The syntax is cumbersome and the encoding not very legible to humans working with it. (And I did not even use [TEI-XML](http://www.tei-c.org/index.xml), yet...) Editing and revising XML-encoded text is a pain. Just ask the literary scientists who have to work with it. - The XML encoding, especially TEI-XML, is often not intuitive. Only experts understand it. Now, if you had the idea that your humanist friend, who is not into digital technologies, might help you with proof-reading, you better think about it again. - There is an awful lot of typing to do: All those lengthy opening and closing tags. This takes time... - While looking for a good XML-Editor, you find that there hardly exist any XML-Editors any more. (And for a reason, actually...) In particular, there are no good open source XML-Editors. On the other hand, there are good reasons why XML is used in the humanities: Important encoding standards like TEI-XML are defined in XML. Its strict syntax and the possibility to check data against a schema help to detect and avoiding encoding errors. If the schema is well-defined, it is unambiguous, and it is easy to parse for a computer. Most of these advantages, however, are on a technical level and few of them are actually exclusive advantages of XML. All in all this means, that while XML is a solid back-end-technology, it still is a pain to work with XML as a frontend-technology. This is where DHParser comes in. It allows you to define your own domain specific notation that is specifically tailored to your editing needs and provides an infrastructure that - if you know a little Python-programming - makes it very easy to convert your annotated text into an XML-encoding of your choice. With DHParser, the same poem above can be simply encoded like this: Heinrich Heine , Buch der Lieder , Hamburg , 1927. Lyrisches Intermezzo IV. Wenn ich in deine Augen seh', so schwindet all' mein Leid und Weh! Doch wenn ich küsse deinen Mund, so werd' ich ganz und gar gesund. Wenn ich mich lehn' an deine Brust, kommt's über mich wie Himmelslust, doch wenn du sprichst: Ich liebe dich! so muß ich weinen bitterlich. Yes, that's right. It is as simple as that. Observe, how much more effacious a verse like "Wenn ich mich lehn' an deine Brust, / kommt's über mich wie Himmelslust," can be if it is not cluttered with XML tags ;-) You might now wonder whether the second version really does encode the same information as the XML version. How, for example, would the computer know for sure where a verse starts and ends or a stanza or what is title and what stanza? Well, for all these matters there exist conventions that poets have been using for several thousand years. For example, a verse always starts and ends on the same line. There is always a gap between stanzas. And the title is always written above the poem and not in the middle of it. So, if there is a title at all, we can be sure that what is written in the first line is the title and not a stanza. DHParser is able to exploit all those hints in order to gather much the same information as was encoded in the XML-Version. Don't believe it? You can try: Download DHParser from the [gitlab-repository](https://gitlab.lrz.de/badw-it/DHParser) and enter the directory `examples/Tutorial` on the command line interface (shell). Just run `python LyrikCompiler_example.py` (you need to have installed [Python](https://www.python.org/) Version 3.4 or higher on your computer). The output will be something like this: Heinrich Heine gnd:118548018 Buch der Lieder urn:nbn:de:kobv:b4-200905192211 Hamburg gnd:4023118-5 1927 Lyrisches Intermezzo IV. Wenn ich in deine Augen seh', so schwindet all' mein Leid und Weh! Doch wenn ich küsse deinen Mund, so werd' ich ganz und gar gesund. Wenn ich mich lehn' an deine Brust, kommt's über mich wie Himmelslust, doch wenn du sprichst: Ich liebe dich! so muß ich weinen bitterlich. Now, you might notice that this is not exactly the XML-encoding as shown above. (Can you spot the differences?) But you will probably believe me without further proof that it can easily be converted into the other version and contains all the information that the other version contains. How does DHParser achieve this? Well, there is the rub. In order to convert the poem in the domain specific version into the XML-version, DHParser requires a structural description of the domain specific encoding. This is a bit similar to a document type definition (DTD) in XML. This structural description uses a slightly enhanced version of the [Extended-Backus-Naur-Form (EBNF)](https://en.wikipedia.org/wiki/Extended_Backus%E2%80%93Naur_form) that is a well-established formalism for the structural description of formal languages in computer sciences. And excerpt of the EBNF-definition of our domain-specific encoding for the poem looks like this. (We leave out the meta-data here. See [`examples/Tutorial/Lyrik.ebnf`](https://gitlab.lrz.de/badw-it/DHParser/blob/master/examples/Tutorial/Lyrik.ebnf) for the full EBNF): gedicht = { LEERZEILE }+ [serie] §titel §text /\s*/ §ENDE serie = !(titel vers NZ vers) { NZ zeile }+ { LEERZEILE }+ titel = { NZ zeile}+ { LEERZEILE }+ zeile = { ZEICHENFOLGE }+ text = { strophe {LEERZEILE} }+ strophe = { NZ vers }+ vers = { ZEICHENFOLGE }+ ZEICHENFOLGE = /[^ \n<>]+/~ NZ = /\n/~ LEERZEILE = /\n[ \t]*(?=\n)/~ ENDE = !/./ Without going into too much detail here, let me just explain a few basics of this formal description: The slashes `/` enclose ordinary regular expressions. Thus, `NZ` for ("Neue Zeile", German for: "new line") is defined as `/\n/~` which is the newline-token `\n` in a regular expression, plus further horizontal whitespace (signified by the tilde `~`), if there is any. The braces `{` `}` enclose items that can be repeated zero or more times; with a `+` appended to the closing brace it means one or more times. Now, look at the definition of `text` in the 6th line: `{ strophe {LEERZEILE} }+`. This reads as follows: The text of the poem consists of a sequence of stanzas, each of which is followed by a sequence of empty lines (German: "Leerzeilen"). If you now look at the structural definition of a stanza, you find that it consists of a sequence of verses, each of which starts, i.e. is preceeded by a new line. Can you figure out the rest? Hint: The angular brackets `[` and `]` mean that and item is optional and the `§` sign means that it is obligatory. (Strictly speaking, the §-signs are not necessary, because an item that is not optional is always obligatory, but the §-signs help the converter to produce the right error messages.) This should be enough for an introduction to the purpose of DSLs in the humanities. It has shown the probably most important use case of DHParser, i.e. as a frontend-technology form XML-encodings. Of course, it can just as well be used as a frontend for any other kind of structured data, like SQL or graph-strcutured data. The latter is by the way is a very reasonable alternative to XML for edition projects with a complex transmission history. See Andreas Kuczera's Blog-entry on ["Graphdatenbanken für Historiker"](http://mittelalter.hypotheses.org/5995). Tutorial: First Steps with DHParser ----------------------------------- Disclaimer: *You'll need to be able to use a shell and have some basic knowledge of Python programming to be able to follow this section!* In order to try the example above, you should fetch DHParsers from its git-repository: $ git clone git@gitlab.lrz.de:badw-it/DHParser.git Now, if you enter the repo, you'll find three subdirectories: DHParser examples test The directory `DHParser` contains the Python modules of the DHParser-package, `test` - as you can guess - contains the unit-tests for DHParser. Now, enter the `examples/Tutorial`-directory. Presently, most other examples are pretty rudimentary. So, don't worry about them. In this directory, you'll find a simple EBNF Grammar for poetry in the file `Lyrik.ebnf`. Have a look at it. You'll find that is the same grammar (plus a few additions) that has been mentioned just before. You'll also find a little script `recompile_grammar.py` that is used to compile an EBNF-Grammar into an executable Python-module that can be used to parse any piece of text that this grammar is meant for; in this case poetry. Any DHParser-Project needs such a script. The content of the script is pretty self-explanatory: from DHParser.testing import recompile_grammar if not recompile_grammar('.', force=True): with open('Lyrik_ebnf_ERRORS.txt') as f: print(f.read()) sys.exit(1) The script simply (re-)compiles any EBNF grammar that it finds in the current directory. "Recompiling" means that DHParser notices if a grammar has already been compiled and overwrites only that part of the generated file that contains the actual parser. All other parts - we will come to that later what these are - can safely be edited by you. Now just run `recompile_grammar.py` from the command line: $ python3 recompile_grammar.py You'll find that `recompile_grammar.py` has generated a new script with the name `LyrikCompiler.py`. This script contains the Parser for the `Lyrik.ebnf`-grammar and some skeleton-code for a DSL->XML-Compiler (or rather, a DSL-whatever compiler), which you can later fill in. Now let's see how this script works: $ python3 LyrikCompiler.py Lyrisches_Intermezzo_IV.txt >result.xml The file `Lyrisches_Intermezzo_IV.txt` contains the fourth part of Heinrich Heine's Lyrisches Intermezzo encoded in our own human-readable poetry-DSL that has been shown above. Since we have redirected the output to `result.xml`, you'll find a new file with this name in the directory. If you look at it with an editor - preferably one that provides syntax-highlighting for XML-files, you'll find that it look's pretty much like XML. However, this XML-code still looks much more obfuscated than in the Introduction before. If you look closely, you can nonetheless see that the poem itself has faithfully been preserved. For example, if you scroll down a few lines, you'll find the (hardly recognizable!) first verse of the poem: ... <:RegExp>Wenn <:Whitespace> <:RegExp>ich <:Whitespace> <:RegExp>in <:Whitespace> <:RegExp>deine <:Whitespace> <:RegExp>Augen <:Whitespace> <:RegExp>seh', ... How come it is so obfuscated, and where do all those pseudo-tags like `<:RegExp>` and `<:Whitespace>` come from? Well, this is probably the right time to explain a bit about parsing and compilation in general. Parsing and compilation of a text with DHParser takes place in three strictly separated steps: 1. Parsing of the text and generation of the "concrete syntax tree" (CST) 2. Transformation of the CST into an "abstract syntax tree" (AST) 3. And, finally, compilation of the AST into valid XML, HTML, LaTeX or what you like. DHParser automatically only generates a parser for the very first step. The other steps have to be programmed by hand, though DHParser makes tries to make those parts as easy as possible. What you have just seen in your editor is a Pseudo-XML-representation of the concrete syntax tree. (The output of a parser is always a tree structure, just like XML.) It is called concrete syntax tree, because it contains all the syntactic details that have been described in the `Lyrik.ebnf`-grammar; and the grammar needs to describe all those details, because otherwise it would not be possible to parse the text. On the other hand most of these details do not carry any important information. This is the reason why in the second step the transformation into an abstract syntax tree that leaves out the unimportant details. There is now general rule of how to derive abstract syntax trees from concrete syntax trees, and there cannot be, because it depends on the particular domain of application which details are important and which not. For poems these might be different from, say, for a catalogue entry. Therefore, the AST-transformation has to be specified for each grammar separately, just as the grammar has to be specified for each application domain. Before I'll explain how to specify an AST-transformation for DHParser, you may want to know what difference it makes. There is a script `LyrikCompiler_example.py` in the directory where the AST-transformations are already included. Running the script $ python LyrikCompiler_example.py Lyrisches_Intermezzo_IV.txt yields the fairly clean Pseudo-XML-representation of the DSL-encoded poem that we have seen above. Just as a teaser, you might want to look up, how the AST-transformation is specified with DHParser. For this purpose, you can have a look in file `LyrikCompiler_example.py`. If you scrool down to the AST section, you'll see something like this: Lyrik_AST_transformation_table = { # AST Transformations for the Lyrik-grammar "+": remove_empty, "bibliographisches": [remove_parser('NZ'), remove_tokens], "autor, werk, untertitel, ort": [], "jahr": [reduce_single_child], "wortfolge": [flatten(has_name('WORT'), recursive=False), remove_last(is_whitespace), collapse], "namenfolge": [flatten(has_name('NAME'), recursive=False), remove_last(is_whitespace), collapse], "verknüpfung": [remove_tokens('<', '>'), reduce_single_child], "ziel": reduce_single_child, "gedicht, strophe, text": [flatten, remove_parser('LEERZEILE'), remove_parser('NZ')], "titel, serie": [flatten, remove_parser('LEERZEILE'), remove_parser('NZ'), collapse], "vers": collapse, "zeile": [], "ZEICHENFOLGE, NZ, JAHRESZAHL": reduce_single_child, "WORT, NAME, LEERZEILE, ENDE": [], ":Whitespace": replace_content(lambda node : " "), ":Token, :RE": reduce_single_child, "*": replace_by_single_child } As you can see, AST-transformations a specified declaratively (with the option to add your own Python-programmed transformation rules). This keeps the specification of the AST-transformation simple and concise. At the same, we avoid adding hints for the AST-transformation in the grammar specification, which would render the grammar less readable. Next, I am going to explain step by step, how a domain specific language for poems like Heine's Lyrisches Intermezzo can be designed, specified, compiled and tested. *to be continued, stay tuned...*