Is there a possibility to combine a couple of Unicode characters so that when gets inserted into text editor it would behave like a single entity? Pretty much like emoji, i.e. 🔤(3 characters combined into one). Ideally if the output behaved like a single character, although from what I learned the only option here is a custom font that would provide such symbols and this is not possible in my case.
For a better context:
I make a plugin for GDocs. I need a special set of numeral symbols - all permutations of 2-3 digits (1, 43, 623 etc.). Up to 3 digits would perfect but 2 are quite ok too. I can't allow user to "break" a sequence, i.e. insert a char in-between digits, or erase one ("12m4" - bad).
The special font would solve my problem - there even is one that looks good, but in GDocs I cannot introduce custom font.
Is there some way to do it? Maybe with the hacky use of non-spacing characters between chars, or maybe some other symbols that could help here but I'm not aware of it?
Certain emoji's that are actually a combination of emoji's result in the incorrect (or at least a count that doesn't match websites like Twitter).
Example problem is pretty straight forward
👩⚖ <- this emoji is a female judge (woman + scale)
The count of this emoji is 1
the utf16 count of this emoji in Swift is 4
let tweet = "👩⚖"
print(tweet.utf16.count)
However, pasting this emoji into Twitter (which is an emoji that Twitter doesn't seem to support you are given the two emoji's. Woman & Scale. Woman is 2 characters and scale is 2 characters when using utf16 count. However, Twitter seems to have a hidden albeit counted invisible character. You will notice this when you try to delete the characters. I'm wondering if there's some way to properly match Twitters count when on mobile. I've seen other websites which, while properly showing the single emoji, are still getting the proper count.
Thanks.
Upgraded Twitter pod and used weighted length for the solution here.
https://developer.twitter.com/en/docs/developer-utilities/twitter-text
For those who end up here with a similar problem, Twitter recommends you show progress rather than exact counts by using permillage.
I found some "funny" characters (e.g. ḓ̵̙͎̖̯̞̜̞̪̠ and •̩̩̩̩̩̩̩̩̩̩) in social media that takes more than one line. First I think it is the bug of Firefox. I tried this in Gedit and LibreOffice Writer, they are all the same. So, what is this actually? Actually I am asking about the character encoding and rendering.
I tried to find the character in GNOME Character Map, they could not be found.
I tried to check the character code of both of them in unicode (probably UTF-8). It seems they takes more than one character. How come one character is more than one character? This is the result by using Python.
Character ḓ̵̙͎̖̯̞̜̞̪̠
u'\u2022\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329
\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329\u0329'
Character •̩̩̩̩̩̩̩̩̩̩
u'\u1e13\u0335\u0319\u034e\u0316\u032f\u031e\u031c\u031e\u032a\u0320\u033c\u031e
\u0320\u034e\u033c\u0353\u034b\u036e\u034c\u0346\u0300\u035c\u0345'
U+0329 is COMBINING VERTICAL LINE BELOW. It is a combining character (and so are all the others in there except U+2022 and U+1E13), meaning that it combines with the previous one. What you see here is merely the result of someone stacking way too many combining characters on the same base.
I'm trying to gather a Unicode list of all the 'o' like shapes in the Hindi character-set. In fact, a list of any characters (in any language) that makes uses of separate characters to indicate an accent would be better.
I intend to use this unicode-list in a RegExp.
I been trying to edit a list of character-ranges by outputting them in an Input TextField, but editing this text causes weird issues (the keyboard-cursor isn't place on the correct character, selections suddenly dissappear / incorrectly warps... in other words... HINDI HELL!)
I've tried this with Notepad++ too, but although it was more responsive, it eventually crapped out on me like it did in the Flash Player textfield. This seems to occur especially while removing the [] block (nulls?) characters. Some of them trigger odd behaviors.
Anyways, all I want is a list of the accents.
An example of a few are in the image below (but I would need ALL accents):
Thanks!
You can find pdf's containing lists of unicode ranges, grouped by language, here: http://unicode.org/charts/
For Hindi, you probably want Devanagari or Devanagari Extended.
Here is the character class for Devanagari combining marks:
[\u901\u902\u903\u93c\u93e\u93f\u940\u941\u942\u943
\u944\u945\u946\u947\u948\u949\u94a\u94b\u94c\u94d
\u951\u952\u953\u954\u962\u963]
This is only the basic Devanagari block (not Devanagari Extended).
If you want the complete set (for all languages), you can do it problematically.
You start from the Unicode date file at ftp://ftp.unicode.org/Public/6.1.0/ucd/UnicodeData.txt, described by TR-44 (http://unicode.org/reports/tr44/#Property_Definitions)
You can use the Canonical_Combining_Class field (see at http://unicode.org/reports/tr44/#Canonical_Combining_Class_Values) to filter the exact characters you want.
Can't be more precise, because "accent" a bit vague :-)
You might even have to also look at General_Category to get the filter right (and exclude certain marks, or symbols, or punctuation).
And a script doing this would definitely be better than trying to mess with text editors.
One of the characteristics of combining characters is that they combine :-)
So you might get all kind of puzzling results (like this: http://www.siao2.com/2006/02/17/533929.aspx :-)
I'm trying to implement a word count function for my app that uses UITextView.
There's a space between two words in English, so it's really easy to count the number of words in an English sentence.
The problem occurs with Chinese and Japanese word counting because usually, there's no any space in the entire sentence.
I checked with three different text editors in iPad that have a word count feature and compare them with MS Words.
For example, here's a series of Japanese characters meaning the world's idea: 世界(the world)の('s)アイデア(idea)
世界のアイデア
1) Pages for iPad and MS Words count each character as one word, so it contains 7 words.
2) iPad text editor P*** counts the entire as one word --> They just used space to separate words.
3) iPad text editor i*** counts them as three words --> I believe they used CFStringTokenizer with kCFStringTokenizerUnitWord because I could get the same result)
I've researched on the Internet, and Pages and MS Words' word counting seems to be correct because each Chinese character has a meaning.
I couldn't find any class that counts the words like Pages or MS Words, and it would be very hard to implement it from scratch because besides Japanese and Chinese, iPad supports a lot of different foreign languages.
I think CFStringTokenizer with kCFStringTokenizerUnitWord is the best option though.
Is there a way to count words in NSString like Pages and MSWords?
Thank you
I recommend keep using CFStringTokenizer. Because it's platform feature, so will be upgraded by platform upgrade. And many people in Apple are working hardly to reflect real cultural difference. Which are hard to know for regular developers.
This is hard because this is not a programming problem essentially. This is a human cultural linguistic problem. You need a human language specialist for each culture. For Japanese, you need Japanese culture specialist. However, I don't think Japanese people needs word count feature seriously, because as I heard, the concept of word itself is not so important in the Japanese culture. You should define concept of word first.
And I can't understand why you want to force concept of word count into the character count. The Kanji word that you instanced. This is equal with counting universe as 2 words by splitting into uni + verse by meaning. Not even a logic. Splitting word by it's meaning is sometimes completely wrong and useless by the definition of word. Because definition of word itself are different by the cultures. In my language Korean, word is just a formal unit, not a meaning unit. The idea that each word is matching to each meaning is right only in roman character cultures.
Just give another feature like character counting for the users in east-asia if you think need it. And counting character in unicode string is so easy with -[NSString length] method.
I'm a Korean speaker, (so maybe out of your case :) and in many cases we count characters instead of words. In fact, I never saw people counting words in my whole life. I laughed at word counting feature on MS word because I guessed nobody would use it. (However now I know it's important in roman character cultures.) I have used word counting feature only once to know it works really :) I believe this is similar in Chinese or Japanese. Maybe Japanese users use the word counting because their basic alphabet is similar with roman characters which have no concept of composition. However they're using Kanji heavily which are completely compositing, character-centric system.
If you make word counting feature works greatly on those languages (which are using by people even does not feel any needs to split sentences into smaller formal units!), it's hard to imagine someone who using it. And without linguistic specialist, the feature should not correct.
This is a really hard problem if your string doesn't contain tokens identifying word breaks (like spaces). One way I know derived from attempting to solve anagrams is this:
At the start of the string you start with one character. Is it a word? It could be a word like "A" but it could also be a part of a word like "AN" or "ANALOG". So the decision about what is a word has to be made considering all of the string. You would consider the next characters to see if you can make another word starting with the first character following the first word you think you might have found. If you decide the word is "A" and you are left with "NALOG" then you will soon find that there are no more words to be found. When you start finding words in the dictionary (see below) then you know you are making the right choices about where to break the words. When you stop finding words you know you have made a wrong choice and you need to backtrack.
A big part of this is having dictionaries sufficient to contain any word you might encounter. The English resource would be TWL06 or SOWPODS or other scrabble dictionaries, containing many obscure words. You need a lot of memory to do this because if you check the words against a simple array containing all of the possible words your program will run incredibly slow. If you parse your dictionary, persist it as a plist and recreate the dictionary your checking will be quick enough but it will require a lot more space on disk and more space in memory. One of these big scrabble dictionaries can expand to about 10MB with the actual words as keys and a simple NSNumber as a placeholder for value - you don't care what the value is, just that the key exists in the dictionary, which tells you that the word is recognised as valid.
If you maintain an array as you count you get to do [array count] in a triumphal manner as you add the last word containing the last characters to it, but you also have an easy way of backtracking. If at some point you stop finding valid words you can pop the lastObject off the array and replace it at the start of the string, then start looking for alternative words. If that fails to get you back on the right track pop another word.
I would proceed by experimentation, looking for a potential three words ahead as you parse the string - when you have identified three potential words, take the first away, store it in the array and look for another word. If you find it is too slow to do it this way and you are getting OK results considering only two words ahead, drop it to two. If you find you are running up too many dead ends with your word division strategy then increase the number of words ahead you consider.
Another way would be to employ natural language rules - for example "A" and "NALOG" might look OK because a consonant follows "A", but "A" and "ARDVARK" would be ruled out because it would be correct for a word beginning in a vowel to follow "AN", not "A". This can get as complicated as you like to make it - I don't know if this gets simpler in Japanese or not but there are certainly common verb endings like "ma su".
(edit: started a bounty, I'd like to know the very best way to do this if my way isn't it.)
If you are using iOS 4, you can do something like
__block int count = 0;
[string enumerateSubstringsInRange:range
options:NSStringEnumerationByWords
usingBlock:^(NSString *word,
NSRange wordRange,
NSRange enclosingRange,
BOOL *stop)
{
count++;
}
];
More information in the NSString class reference.
There is also WWDC 2010 session, number 110, about advanced text handling, that explains this, around minute 10 or so.
I think CFStringTokenizer with kCFStringTokenizerUnitWord is the best option though.
That's right, you have to iterate through text and simply count number of word tokens encontered on the way.
Not a native chinese/japanese speaker, but here's my 2cents.
Each chinese character does have a meaning, but concept of a word is combination of letters/characters to represent an idea, isn't it?
In that sense, there's probably 3 words in "sekai no aidia" (or 2 if you don't count particles like NO/GA/DE/WA, etc). Same as english - "world's idea" is two words, while "idea of world" is 3, and let's forget about the required 'the' hehe.
That given, counting word is not as useful in non-roman language in my opinion, similar to what Eonil mentioned. It's probably better to count number of characters for those languages.. Check around with Chinese/Japanese native speakers and see what they think.
If I were to do it, I would tokenize the string with spaces and particles (at least for japanese, korean) and count tokens. Not sure about chinese..
With Japanese you can create a grammar parser and I think it is the same with Chinese. However, that is easier said than done because natural language tends to have many exceptions, but it is not impossible.
Please note it won't really be efficient since you have to parse each sentence before being able to count the words.
I would recommend the use of a parser compiler rather than building one yourself as well to start at least you can concentrate on doing the grammar than creating the parser yourself. It's not efficient, but it should get the job done.
Also have a fallback algorithm in case your grammar didn't parse the input correctly (perhaps the input really didn't make sense to begin with) you can use the length of the string to make it easier on you.
If you build it, there could be a market opportunity for you to use it as a natural language Domain Specific Language for Japanese/Chinese business rules as well.
Just use the length method:
[#"世界のアイデア" length]; // is 7
That being said, as a Japanese speaker, I think 3 is the right answer.