Merge existing translations from an old translation file to a new one as well as fill any missing translations from translation memory via fuzzy matching.

This functionality used to be part of pot2po and corresponds to “msgmerge” from the gettext package.

pretranslate works on PO and XLIFF files.


pretranslate [options] <input> <output>



is the translation file or directory to be pretranslated


is the translation file or a directory where the pretranslated version will be stored



show program’s version number and exit

-h, --help

show this help message and exit


output a manpage based on the help


show progress as: dots, none, bar, names, verbose


show errorlevel as: none, message, exception, traceback

-i INPUT, --input=INPUT

read from INPUT in pot format

-x EXCLUDE, --exclude=EXCLUDE

exclude names matching EXCLUDE from input paths

-o OUTPUT, --output=OUTPUT

write to OUTPUT in po, pot formats

-t TEMPLATE, --template=TEMPLATE

read old translations from TEMPLATE

-S, --timestamp

skip conversion if the output file has newer timestamp


The file to use as translation memory when fuzzy matching


The minimum similarity for inclusion (default: 75%)


Disable all fuzzy matching


pretranslate -t zu-1.0.1 -tm zu_tm.po zu-2.0.2 zu-2.0.2-translated

Here we are pretranslating the PO or XLIFF files in zu-2.0.2 using the old translations in zu-1.0.1 and fuzzy matches from the zu_tm.po compendium. the result is stored in zu-2.0.2-translate

Unlike pot2po pretranslate will not change anything in the input file except merge translations, no reordering or changes to headers.


It helps to understand when and how pretranslate will merge. The default is to follow msgmerge’s behaviour but we add some extra features with fuzzy matching:

  • If everything matches we carry that across

  • We can resurrect obsolete messages for reuse

  • If we cannot find a match we will first look through the current and obsolete messages and then through any global translation memory

  • Fuzzy matching makes use of the Levenshtein distance algorithm to detect the best matches


Fuzzy matches are usually of good quality. Installation of the python-Levenshtein package will speed up fuzzy matching. Without this a Python based matcher is used which is considerably slower.