Character Encodings in Java

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Ultimately, computers can store only bytes, that is, 8-bit values which, if unsigned, range from 0x00 to 0xFF Every character must somehow be represented in terms of bytes In the early days of computing the pioneers devised encoding schemes that assigned a particular character to a particular byte For example, using the ASCII encoding, A is represented by 0x41, B by 0x42, and so on In the US and Western Europe the Latin-1 encoding was often used; its characters in the range 0x20 0x7E are the same as the corresponding characters in 7-bit ASCII, with those in the range 0xA0 0xFF used for accented characters and other symbols needed by those using non-English Latin alphabets Many other encodings have been devised over the years, and now there are lots of them in use however, development has ceased for many of them, in favor of Unicode Having all these different encodings has proved very inconvenient, especially when writing internationalized software One solution that has been almost universally adopted is the Unicode encoding Unicode assigns every character to an integer called a code point in Unicode-speak just like the earlier encodings But Unicode is not limited to using one byte per character, and is therefore able to represent every character in every language in a single encod-
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ing, so unlike other encodings, Unicode can handle characters from a mixture of languages, rather than just one But how is Unicode stored Currently, slightly more than 100 000 Unicode characters are de ned, so even using signed numbers, a 32-bit integer is more than adequate to store any Unicode code point So the simplest way to store Unicode characters is as a sequence of 32-bit integers, one integer per character This sounds very convenient since it should produce a one to one mapping of characters to 32-bit integers, which would make indexing to a particular character very fast However, in practice things aren t so simple, since some Unicode characters can be represented by one or by two code points for example, can be represented by the single code point 0xE9 or by two code points, 0x65 and 0x301 (e and a combining acute accent) Nowadays, Unicode is usually stored both on disk and in memory using UTF8, UTF-16, or UTF-32 The rst of these, UTF-8, is backward compatible with 7-bit ASCII since its rst 128 code points are represented by single-byte values that are the same as the 7-bit ASCII character values To represent all the other Unicode characters, UTF-8 uses two, three, or more bytes per character This makes UTF-8 very compact for representing text that is all or mostly English The Gtk library (used by the GNOME windowing system, among others) uses UTF-8, and it seems that UTF-8 is becoming the de facto standard format for storing Unicode text in les for example, UTF-8 is the default format for XML, and many web pages these days use UTF-8 A lot of other software, such as Java, uses UCS-2 (which in modern form is the same as UTF-16) This representation uses two or four bytes per character, with the most common characters represented by two bytes The UTF-32 representation (also called UCS-4) uses four bytes per character Using UTF-16 or UTF-32 for storing Unicode in les or for sending over a network connection has a potential pitfall: If the data is sent as integers then the endianness matters One solution to this is to precede the data with a byte order mark so that readers can adapt accordingly This problem doesn t arise with UTF-8, which is another reason why it is so popular Python represents Unicode using either UCS-2 (UTF-16) format, or UCS-4 (UTF-32) format In fact, when using UCS-2, Python uses a slightly simpli ed version that always uses two bytes per character and so can only represent code points up to 0xFFFF When using UCS-4, Python can represent all the Unicode code points The maximum code point is stored in the read-only sysmaxunicode attribute if its value is 65 535, then Python was compiled to use UCS-2; if larger, then Python is using UCS-4 The strencode() method returns a sequence of bytes actually a bytes object, covered in 7 encoded according to the encoding argument we supply Using this method we can get some insight into the difference between encodings, and why making incorrect encoding assumptions can lead to errors:
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