Skip to content
/ tab2opf Public
forked from apeyser/tab2opf

Remake of tab2opf dictionary builder for kindle

License

Notifications You must be signed in to change notification settings

kiicia/tab2opf

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

27 Commits
 
 
 
 
 
 
 
 

Repository files navigation

tab2opf

Remake of tab2opf dictionary builder for kindle

Script to convert tab delimited dictionary files into opf file to run with kindlegen into a translation lookup dictionary for kindle.

Based on the generally available tab2opf.py by Klokan Petr Přidal (www.klokan.cz) from 2007

The script has been mostly rewritten and extended. The encoding convolutions have been removed, and the code migrated to python3

The input form is: Word(s) \t Definition

By running tab2opf.py path/file.txt in the current directory file.opf and file*.html are created which can then be converted with kindlegen file.opf into file.mobi

--source and --target options define which language to which we are translating.

tab2opf has a -m option to load a module to load getkey and getdef functions and mapping dictionary from that namespace into the current one; if it doesn't find such defined member(s), no error is produced.

getkey converts the term (the Word(s)) into a search key. getdef converts Definition in some arbitrary way. mapping is a dictionary mapping from char -> char to replace some set of characters in the input with characters in the output.

Used and tested is the dictcc.py, which converts a dict.cc german -> english dictionary (http://www.dict.cc/?s=about%3Awordlist&l=e). The keys are the longest word in the Word(s) after removal of prepositional phrases and some pronouns (in getkey). The definitions remap the dict.cc pattern of "definition \t part-of-speech" into (part-of-speech) definiton.

About

Remake of tab2opf dictionary builder for kindle

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%