Question

I keep coming across (rare) cases where NSStrings don’t return equal although they look exactly the same when they are printed in the console. For instance:

[string1 isEqualToString:string2]
> comparing 'angelo debarre' to 'angelo debarre'

keeps returning NO. I’ve tried using NSString’s stringByTrimmingCharactersInSet:[NSCharacterSet whitespaceAndNewlineCharacterSet] but still no luck. I also tried using comparators such as compare: and localizedCaseInsensitiveCompare: but I keep getting the same results. Any idea of something I might be overlooking?

Answer 1

Try decomposing the strings using one of the NSString Unicode normalization functions, like - (NSString *)decomposedStringWithCompatibilityMapping. Compatibility mapping (vs canonical mapping) should be what you want, as it decomposes visually similar character sequences into the same base components. I haven’t explicitly looked up whether a non-breaking space is normalized into a space, though.

EDIT: There are two types of compatibility mapping normalization: decomposed and composed. The composed version is - (NSString *)precomposedStringWithCompatibilityMapping. Not sure which one works better in general, but Unicode Standard Annex #15 (Unicode Normalization Forms) says the following of the KC/KD forms:

Normalization Form KC additionally folds the differences between compatibility-equivalent characters that are inappropriately distinguished in many circumstances. For example, the halfwidth and fullwidth katakana characters will normalize to the same strings, as will Roman numerals and their letter equivalents.

Normalization Forms KC and KD must not be blindly applied to arbitrary text. Because they erase many formatting distinctions, they will prevent round-trip conversion to and from many legacy character sets, and unless supplanted by formatting markup, they may remove distinctions that are important to the semantics of the text. It is best to think of these Normalization Forms as being like uppercase or lowercase mappings: useful in certain contexts for identifying core meanings, but also performing modifications to the text that may not always be appropriate. They can be applied more freely to domains with restricted character sets.