So my answer is that it was a deeply misconceived change that shouldn't have been made at all, let alone been taken as the cornerstone of a "necessary" break in backward compatibility.
And the ecosystem agrees.
You're not making an argument about backward compatibility here, you're making a strong claim that representing text as a sequence of Unicode code points is fundamentally wrong. I have never heard anyone make this point before, and I am inclined to disagree, but I'm curious what your reasoning is for it.
There are no operations on sequences of Unicode code points that are more correct than an analogous operation on bytes.
(Everyone's favourite example, length, actually becomes less correct—a byte array's length at least corresponds to the amount of space one might have to allocate for it in a particular encoding. A length in codepoints is absolutely meaningless both technically and linguistically. And this is, for what little it's worth, close to the only operation you can do on a string without imposing additional restrictions about its context.)
That’s ridiculous. Uppercasing/lowercasing, slicing, “startswith”, splitting, etc etc.
Your statement is correct if you only care about ascii.
Even then, upper/lower-casing is iffy.
Wow. I wonder how you arrived at this point. You can't, for example, truncate a UTF-8 byte array without the risk of producing a broken string. But this is only the start. Here are two strings, six letters each, one in NFC, the other in NFD, and their byte-length in UTF-8:
"Åström" is 8 bytes in UTF-8
"Åström" is 10 bytes in UTF-8
Normalization is not a real solution unless you restrict yourself to working with well-edited formal prose in common Western languages.
This is not a claim made from ignorance.
Stop treating these cases as equivalent. They're not.
In the end, the only layer at which it really matters whether your byte sequence can be decoded is the font renderer, and just being valid utf-8 isn't good enough for it either.
Ok that explains how we ended up here. I'm considering some other common uses! A search-index for example greatly profits from being able to normalize representations and split words.
You can still best-effort split words! You can do a pretty good job splitting words without ensuring that the words decode in your preferred encoding.
I understand you're arguing about some sort of equivalency between byte-arrays and Unicode strings. Sure there are half-baked ways to do word-splitting on a byte-array. But why do you consider that a viable option? Under what circumstances would you do that?
def keywords(text):
return set(filter(None, re.split("\W+", unicodedata.normalize("NFKC", input_str).lower())))
The way I see it: If the encoding is implicit, you have global state. If it's explicit, you have to pass the encoding. Both is extra state to worry about. When the passed value is a Unicode string, this question doesn't come up.
I realize this sounds like a total cop-out, but when the use-case is destructively best-effort tokenizing an input string using library functions, it doesn't really matter whether your internal encoding is utf-32 or utf-8. I mean, under the hood, normalize still has to map arbitrary-length sequences to arbitrary-length sequences even when working with utf-32 (see: unicodedata.normalize("NFKC", "a\u0301 ffi") == "\xe1 ffi").
So on the happy path, you don't see much of a difference.
The main observable difference is that if you take input without decoding it explicitly, then the always-decode approach has already crashed long before reaching this function, while the assume-the-encoding approach probably spouts gibberish at this point. And sure, there are plenty of plausible scenarios where you'd rather get the crash than subtly broken behaviour. But ... I don't see this reasonably being one of them, considering that you're apparently okay with discarding all \W+.
Having "accents fall off" has gotten people murdered [0]. Accents aren't things peppered in for effect, they turn letters into different letters, spelling different words. Analogously, imagine that a bunch of software accidentally turned every "d" into a "c" because some committee halfway around the world decided "d" should be composed of the "c" and "|" glyphs. That's the kind of text corruption that regularly happens in other languages when dealing with text at the code point layer.
[0] https://languagelog.ldc.upenn.edu/nll/?p=73 . Note that this is Turkish, which has the "dotted i" problem, meaning that this was more than likely a .toupper() gone wrong rather than a truncation issue.
If I have an byte-array, I can do none of these things short of implementing a good chunk of Unicode. If I truncate, I risk ending up with an invalid UTF-8 string. End of story.
Basically, I believe the point here is that a Unicode aware truncation should be done in a Unicode aware truncate method. There is no good reason to parse a string as UTF-8 ahead of time - just keep it as a blob of bytes until you need to do some something "texty" with it. It is the truncate-at-word-boundaries() method that should interpret the bytes as UTF-8 and fail if they are not valid. Why parse it sooner?
Yes, and? You can have an invalid sequence of Unicode code points too, such as an unpaired surrogate (something Python's text model actually abuses to store "invalid Unicode" in a special, non-standard way).
If you truncate at the byte level, you are just truncating "between code points"; it's a closer granularity than at the code point layer, so you can also convert to NFC, truncate on word boundaries, etc. You just need to ignore the parts of the UTF-8 string that are invalid; which isn't difficult, because UTF-8 is self-synchronizing.
In fact, if the software tells you that either of the strings is either 8 or 10 letters wrong, then either way the software is incorrect - those are both obviously 6 letter strings.
Now, does UTF8 help you discover they are 6 letter strings better than other representations? There are certainly text-oriented libraries that can do that, but not those that simply count the UTF8 code points - they must have an understanding of all of Unicode. Even worse, the question "how many letters does this string have" is not generally meaningful - there are plenty of perfectly valid unicode strings for which this question doesn't have a meaningful answer.
However, the question "how many unicode code points does this string have" is almost never of interest. You either care about some notion of unique glyphs, or you care about byte lengths.
What I wanted to get at is that in Unicode, I have a chance to count letters to some useful degree. Why should I consider starting at byte-arrays?
> there are plenty of perfectly valid Unicode strings for which this question doesn't have a meaningful answer.
I don't get it. Why does the existence of degenerate cases invalidate the usefulness of a Unicode lib? If I want to know how many letters are in a string, I can probably get a useful answer from a Unicode lib. Not for all edge-cases, but I can decide on the trade-offs. If I have a byte-array, I start at a lower level.
You do not. You merely happen to get the right answer by coincidence in some cases, same as bytes-that-probably-are(n't)-ASCII. To throw your own words back at you:
"Åström" is 6 code points in Unicode
"Åström" is 8 code points in Unicode