This post explores one of the capabilities of the PyICU library, namely its text transformation module.
Specifically, we’ll look at the simplest use case: transliterating text into Latin script.
Say you are given a list of phrases, names, titles, whatever, in a writing system that you’re not familiar with.
You want to be able to differentiate the items, but this is hard when you can’t read what they say. Well, let’s
turn them into Latin characters (which, assuming you’re reading this in English, you are able to read)!
There we go. Even though you probably still can’t pronounce these names correctly, at least they’re hopefully
easier to recognise because they are now in a script that you are more used to reading (unless you’re Greek, of
course).
"Any-Latin; Title" means we want to transliterate from any script to Latin, then convert it to title
case. If that’s too simple, the
ICU documentation has the gory details of all
the supported transforms.
Caveats
As previously aluded to, do not rely on the output as pronunciation guide unless you know what you’re doing. For
example, the Korean character 꽃 is transliterated by ICU as kkoch to keep it reversible; that’s not how
the word is normally romanised, and if you try to pronounce it like that nobody will understand you.
Another issue is that the transliteration of Han characters (shared between Chinese, Japanese, and Korean) uses
Chinese Pinyin, and thus may not resemble the Japanese and Korean romanisations at all. Considering that Japanese
writing makes extensive use of these characters, using ICU to transliterate Japanese texts may be a bad idea
depending on your use case.
>>> tr("日本国")# "Nippon-koku" in Japanese, meaning "Japan"'Rì Běn Guó'
Oops, that could start an Internet war. Use a different library if you need to properly deal with Japanese text.
Another unfortunate thing with ICU is that there are still scripts that it doesn’t support at all. For example, it
can’t transliterate to/from Javanese.
If you have a GtkFontButton, finding out whether the chosen font is monospaced is quite a complicated process. Here
is a complete walk-through.
(By the way, I will be using PyGTK’s Pango documentation because the C version is a mess.)
FontButton.get_font_name returns the font family (a.k.a. “font name”), style, and size; for example,
“Liberation Serif Italic 14”. The first thing we need to do is pick just the family name. We do this by going
through a PangoFontDescription.
Next, check whether the font family describes a monospaced font. Here is where
it gets dodgy. We need an arbitrary PangoContext, which
can be obtained from a GtkWidget using Widget.get_pango_context. We then list all available font
families and find the one with the appropriate name. Call
FontFamily.is_monospace
to finish the job.
(By the way, this is also a good place to show off Python’s
for-else construct.)
context = widget.get_pango_context()# widget can be any GtkWidget.for family in context.list_families():if family.get_name()== family_name:breakelse:# Should not happen.assertFalse
family.is_monospace()# False -- Liberation Serif is proportional.
This post explains a
Python EBML parser that I
wrote. (EBML is Matroska’s binary “markup language”.) It is implemented as
a single-file library and is available under a free software licence.
Background
I’ve been working to implement Matroska (mka, mkv, webm) tag-reading support in Exaile.
Mutagen—the tag library that we use—currently doesn’t have this
feature, so I looked elsewhere.
Choices
Previously I had a working solution using
hachoir-metadata, but it doesn’t really make
sense to depend on another large tagging library when we’re already using Mutagen. To make matters worse, I
accidentally deleted the branch during our recent
Bazaar upgrade problem.
I started shopping around for other possible solutions and found
videoparser, which seemed quite nice and compact. It’s
still a different library, though, and it doesn’t seem to be packaged in Debian.
I was considering just using it anyway for yet another temporary hack when I chanced on
MatroskaParser.pm
(dead link), a Perl library written by “Omion
(on HA)”. It’s only 816 lines of Perl; discounting the README and the
Matroska elements table, we’re looking at less than 450.
Solution
I decided to translate MatroskaParser.pm into Python. Despite the horror stories out there about Perl, this
particular code is written in a style that is extremely readable if you’re somewhat familiar with the language.
Well, I’ve finished the porting: 250 lines of EBML parser written in Python. Parts of MatroskaParser.pm that are
not relevant—mainly the validity checker and the Block parser—have been removed, and the output data structure has
been simplified. The next job is to actually extract tags out of the structure.
Matroska tags
Matroska tags are quite different from MP3 and Vorbis tags, in that they’re not just a flat list of key-value
pairs. Consider the following snippet.
There are two types of tags in this example. The first (target type: 50) explains the album (title:
Light + Shade, artist: Mike Oldfield), while the second (target type: 30) explains the track
(title: Surfing). Translating this structure into tags that Exaile can understand is not hard, just needs
a bit of planning.
By the way, notice that Matroska makes implementing album artists / compilation albums very intuitive: you can have
an artist tag at album level, and another at track level. There are even
other levels specified. As a
further example, because Light + Shade consists of two CDs labelled Light and
Shade respectively, you could use them as the titles at level 40 (between album and track); however, this
is not common practice.
Another tricky part is getting the track length out of the structure. Under /Segment/Info, you’ll find
something like
At first I randomly assumed that the duration was specified in seconds, and got around 171 days as output, which
was obviously wrong. Apparently you need to apply this formula to get the length in seconds:
Length = Duration * TimecodeScale / 10^9
Note that TimecodeScale may be omitted; it is one of the few important elements that have default values
(1,000,000 in its case).
Code
The code is now available in
Exaile’s repository. It’s
licensed under GPL 2+ with the standard Exaile exception, although I will consider relicensing it if there is
interest.
Notice that the last 100-or-so lines make up the Matroska tagging part. Depending on your needs, you may need to
expand the list of elements based on the Matroska specification. There are also 40 lines of code that subclasses
the parser to use GIO to read the files; you may want to remove this chunk of code if it’s not relevant to you.
Future
Matroska read-only tag support will be in Exaile 0.3.2. Maybe one day I’ll add write support and integrate the
whole thing into Mutagen, but don’t count on it. If anyone wants to do it, I’m more than happy to help.
What about WebM?
Funny how I made this post shortly before WebM was announced. Coincidence? Yes, unfortunately; I’m not as cool as
the Mozilla and Opera people, who were let in on Google’s secret.
At this point, the WebM container is mostly just a subset of Matroska (the only incompatibility I’ve noticed is the
change in doctype, from matroska to webm). As far as I know, they use the exact same EBML
structure for tags, so there’s no reason Exaile or this code shouldn’t be able to read tags from a WebM file.