Apertium-apy

Apertium-APy stands for "Apertium API in Python". It's a simple apertium API server written in python, meant as a drop-in replacement for ScaleMT. It is currently found in the svn under trunk/apertium-tools/apertium-apy, where servlet.py is basically its entirety. This is meant for front ends like the simple one in trunk/apertium-tools/simple-html (where index.html is the main deal).

Installation

First, compile and install apertium/lttoolbox/apertium-lex-tools, and compile your language pairs. See Minimal_installation_from_SVN for how to do this. Then

svn co https://svn.code.sf.net/p/apertium/svn/trunk/apertium-tools/apertium-apy
cd apertium-apy
export APERTIUMPATH="/path/to/apertium/svn/trunk"
./servlet.py "$APERTIUMPATH"

Optional arguments include:

• --langNamesDB: path to database of localized language names
• -port --port: port to run server on (2737 by default)
• --ssl: path to SSL certificate

Usage

APY supports three types of requests: GET, POST, and JSONP. Using GET/POST are possible only if APY is running on the same server as the client due to cross-site scripting restrictions; however, JSONP requests are permitted in any context and will be useful. Using curl, APY can easily be tested:

curl --data "lang=kaz-tat&modes=morph&q=алдым" http://localhost:2737/perWord

Note that this sends a POST request, using curl or your browser to send a GET request is also possible.

URL	Function	Parameters	Example
/listPairs	List available language pairs	None	$ curl http://localhost:2737/listPairs {"responseStatus": 200, "responseData": [ {"sourceLanguage": "kaz", "targetLanguage": "tat"}, {"sourceLanguage": "tat", "targetLanguage": "kaz"}, {"sourceLanguage": "mk", "targetLanguage": "en"} ], "responseDetails": null}
/list	List available mode information	q: type of information to list pairs (alias for /listPairs) analyzers/analysers generators taggers/disambiguators	$ curl http://localhost:2737/list?q=analyzers {"mk-en": "mk-en-morph", "en-es": "en-es-anmor", "kaz-tat": "kaz-tat-morph", "tat-kaz": "tat-kaz-morph", "fin": "fin-morph", "es-en": "es-en-anmor", "kaz": "kaz-morph"} $ curl http://localhost:2737/list?q=generators {"en-es": "en-es-generador", "fin": "fin-gener", "es-en": "es-en-generador"} $ curl http://localhost:2737/list?q=taggers {"es-en": "es-en-tagger", "en-es": "en-es-tagger", "mk-en": "mk-en-tagger", "tat-kaz": "tat-kaz-tagger", "kaz-tat": "kaz-tat-tagger", "kaz": "kaz-tagger"}
/translate	Translate text	langpair: language pair to use for translation q: text to translate	$ curl 'http://localhost:2737/translate?langpair=kaz|tat&q=Сен+бардың+ба?' output
/analyze	Morphologically analyze text	mode: language to use for analysis q: text to analyze	$ curl --data "mode=kaz&q=Сен+бардың+ба?" http://localhost:2737/analyze [["Сен/сен<v><tv><imp><p2><sg>/сен<prn><pers><p2><sg><nom>","Сен "], ["бардың ба/бар<adj><subst><gen>+ма<qst>/бар<v><iv><ifi><p2><sg>+ма<qst>","бардың ба"], ["?/?<sent>","?"],["./.<sent>",".\n"]]
/generate	Generate surface forms from text	mode: language to use for generation q: text to generate	$ curl --data "mode=kaz&q=^сен<v><tv><imp><p2><sg>$" http://localhost:2737/generate [["сен","^сен<v><tv><imp><p2><sg>$ "]]
/perWord	Perform morphological tasks per word	language: language to use for tasks modes: morphological tasks to perform on text tagger/disambig biltrans translate biltrans+morph (in any order) translate+tagger (in any order) morph+tagger/morph+disambig (in any order) q: text to perform tasks on	$ curl "http://localhost:2737/perWord?lang=en-es&modes=morph&q=light" [{"analyses": ["light<n><sg>", "light<adj><sint>", "light<vblex><inf>", "light<vblex><pres>"], "input": "light"}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=tagger&q=light" [{"analyses": ["light<adj><sint>"], "input": "light"}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=biltrans&q=light" [{"input": "light", "translations": ["luz<n><f><sg>", "ligero<adj>", "encender<vblex><inf>", "encender<vblex><pres>"]}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=translate&q=light" [{"input": "light", "translations": ["ligero<adj>"]}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=biltrans+morph&q=light" [{"analyses": ["light<n><sg>", "light<adj><sint>", "light<vblex><inf>", "light<vblex><pres>"], "input": "light", "translations": ["luz<n><f><sg>", "ligero<adj>", "encender<vblex><inf>", "encender<vblex><pres>"]}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=translate+tagger&q=light" [{"analyses": ["light<adj><sint>"], "input": "light", "translations": ["ligero<adj>"]}] $ curl "http://localhost:2737/perWord?lang=en-es&modes=morph+tagger&q=light" [{"ambiguousAnalyses": ["light<n><sg>", "light<adj><sint>", "light<vblex><inf>", "light<vblex><pres>"], "input": "light", "disambiguatedAnalyses": ["light<adj><sint>"]}]

Threading

Currently it uses TCPServer inheriting ThreadingMixIn. A lock on translateNULFlush (which has to have at most one thread per pipeline) ensures that part stays single-threaded (to avoid Alice getting Bob's text).

Try it out

Try testing with e.g.

   export APERTIUMPATH="/path/to/svn/trunk"
   python3 servlet "$APERTIUMPATH" 2737 &
   
   curl -s --data-urlencode 'langpair=nb|nn' --data-urlencode \
   'q@/tmp/reallybigfile' 'http://localhost:2737/translate' >/tmp/output &
   
   curl 'http://localhost:2737/translate?langpair=nb%7Cnn&q=men+ikke+den'
   curl 'http://localhost:2737/translate?langpair=nb%7Cnn&q=men+ikke+den'
   curl 'http://localhost:2737/translate?langpair=nb%7Cnn&q=men+ikke+den'
   

And see how the last three (after a slight wait) start outputting before the first request is done.

Morphological Analysis and Generation

To analyze text, send a POST or GET request to /analyze with parameters mode and q set. For example:

   $ curl --data "mode=kaz&q=Сен+бардың+ба?" http://localhost:2737/analyze
   [["Сен/сен<v><tv><imp><p2><sg>/сен<prn><pers><p2><sg><nom>","Сен "],["бардың ба/бар<adj><subst><gen>+ма<qst>/бар<v><iv><ifi><p2><sg>+ма<qst>","бардың ба"],["?/?<sent>","?"],["./.<sent>",".\n"]]

The JSON response will consist of a list of lists each of form [analysis with following non-analyzed text*, original input token]. To receive a list of valid analyzer modes, send a request to /listAnalyzers.

To generate surface forms from an analysis, send a POST or GET request to /generate with parameters mode and q set. For example:

   $ curl --data "mode=kaz&q=^сен<v><tv><imp><p2><sg>$+^сен<v><tv><imp><p2><pl>$" http://localhost:2737/generate
   [["сен ","^сен<v><tv><imp><p2><sg>$ "],["сеніңдер","^сен<v><tv><imp><p2><pl>$"]]

The JSON response will consist of a list of lists each of form [generated form with following non-analyzed text*, original lexical unit input]. To receive a list of valid generator modes, send a request to /listGenerators.

* e.g. whitespace, superblanks

SSL

To test with a self-signed signature:

openssl req -new -x509 -keyout server.pem -out server.pem -days 365 -nodes

Then run with --ssl server.pem, and test with https and the -k argument to curl (-k means curl accepts self-signed or even slightly "lying" signatures):

curl -k --data "mode=kaz-tat&q=Сен+бардың+ба?" https://localhost:2737/analyze

If you have a signed signature for e.g. apache, it's likely to be split into two files, one .key and one .crt. You can cat them together into one to use with servlet.py:

cat server.key server.crt > server.keycrt

Now you should be able to use curl without -k for the domain which the certificate is signed for:

curl --data "mode=kaz-tat&q=Сен+бардың+ба?" https://oohlookatmeimencrypted.com:2737/analyze

Remember to open port 2737 to your server.

TODO

• It should be possible to set a time-out for translation threads, so if a translation is taking too long, it gets killed and the queue moves along.
• It should use one lock per pipeline, since we don't need to wait for mk-en just because sme-nob is running.
• http://stackoverflow.com/a/487281/69663 recommends select/polling over threading (http://docs.python.org/3.3/library/socketserver.html for more on the differences) but requires either lots of manually written dispatching code (http://pymotw.com/2/select/) or a framework like Twisted.
• some language pairs still don't work (sme-nob?)
• hfst-proc -g doesn't work with null-flushing (or?)