an API involving blocks would need a way to enumerate them, to get the range for a name, and the name for a char/codepoint.python has no built-in information about unicode blocks (which are basically range()s with associated names).yet one puzzle piece is missing: blocks.you’re right, all of this works.iterating over all of unicode simply looked to big a task for me, so i didn’t consider it, but apparently it works well enough.2014-10-04 9:13 GMT+02:00 Chris Angelico <rosuav@gmail.com>:On Sat, Oct 4, 2014 at 4:47 PM, Stephen J. Turnbull <stephen@xemacs.org> wrote:
>>>> names = [unicodedata.name(chr(i)) for i in range(sys.maxunicode+1)]
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "<stdin>", line 1, in <listcomp>
> ValueError: no such name
>
> oops, although you didn't actually claim that would work. :-) (BTW,
> chr(0) has no name. At least it was instantaneous. :-)
Oops, forgot about that. Yet another case where the absence of PEP 463
forces the function to have an additional argument:
names = [unicodedata.name(chr(i), '') for i in range(sys.maxunicode+1)]
Now it works. Sorry for the omission, this is what happens when code
is typed straight into the email without testing :)
> Then
>
>>>> for i in range(sys.maxunicode+1):
> ... try:
> ... names.append(unicodedata.name(chr(i)))
> ... except ValueError:
> ... pass
> ...
I would recommend appending a shim in the ValueError branch, to allow
the indexing to be correct. Which would look something like this:
names = [unicodedata.name(chr(i)) except ValueError: '' for i in
range(sys.maxunicode+1)]
Or, since name() does indeed have a 'default' parameter, the code from above. :)
> takes between 1 and 2 seconds, while
>
>>>> names.index("PILE OF POO")
> 61721
>>>> "PILE OF POO" in names
> True
>
> is instantaneous. Note: 61721 is *much* smaller than 0x1F4A9.
>>> names.index("PILE OF POO")
128169
>>> hex(_).upper()
'0X1F4A9'
And still instantaneous. Of course, a prefix search is a bit slower:
>>> [i for i,s in enumerate(names) if s.startswith("PILE")]
[128169]
Takes about 1s on my aging Windows laptop, where the building of the
list takes about 4s, so it should be quicker on your system.
The big downside, I guess, is the RAM usage.
>>> sys.getsizeof(names)
4892352
>>> sum(sys.getsizeof(n) for n in names)
30698194
That's ~32MB of stuff stored, just to allow these lookups.
ChrisA
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