howto-unicode.pdf

Unicode HOWTO

Release2.7.6

Guido van Rossum

Fred L. Drake, Jr., editor

March 17, 2014

PythonSoftwareFoundation

Email:docs@python.org

Contents

1IntroductiontoUnicode

1.1

History of Character Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1.2

Deﬁnitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1.3

Encodings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

iii

1.4

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2Python2.x’sUnicodeSupport

2.1

The Unicode Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2

Unicode Literals in Python Source Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.3

Unicode Properties

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vii

2.4

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

viii

3ReadingandWritingUnicodeData

viii

3.1

Unicode ﬁlenames

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3.2

Tips for Writing Unicode-aware Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3.3

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4RevisionHistoryandAcknowledgements

Release1.03

This

HOWTO

discusses

Python

2.x’s

support

for

Unicode,

and

explains

various

problems

that

peo-

ple

commonly

encounter

when

trying

work

with

Unicode.

For

the

Python

version,

see

< http://docs.python.org/py3k/howto/unicode.html > .

1 Introduction to Unicode

1.1 History of Character Codes

In 1968, the American Standard Code for Information Interchange, better known by its acronym ASCII, was

standardized. ASCII deﬁned numeric codes for various characters, with the numeric values running from 0 to 127.

For example, the lowercase letter ‘a’ is assigned 97 as its code value.

ASCII was an American-developed standard, so it only deﬁned unaccented characters. There was an ‘e’, but no ‘é’

or ‘Í’. This meant that languages which required accented characters couldn’t be faithfully represented in ASCII.

(Actually the missing accents matter for English, too, which contains words such as ‘naïve’ and ‘café’, and some

publications have house styles which require spellings such as ‘coöperate’.)

For a while people just wrote programs that didn’t display accents. I remember looking at Apple ][ BASIC

programs, published in French-language publications in the mid-1980s, that had lines like these:

PRINT"FICHIERESTCOMPLETE."

PRINT"CARACTERENONACCEPTE."

Those messages should contain accents, and they just look wrong to someone who can read French.

In the 1980s, almost all personal computers were 8-bit, meaning that bytes could hold values ranging from 0 to

255. ASCII codes only went up to 127, so some machines assigned values between 128 and 255 to accented

characters. Different machines had different codes, however, which led to problems exchanging ﬁles. Eventually

various commonly used sets of values for the 128-255 range emerged. Some were true standards, deﬁned by the

International Standards Organization, and some weredefactoconventions that were invented by one company or

another and managed to catch on.

255 characters aren’t very many. For example, you can’t ﬁt both the accented characters used in Western Europe

and the Cyrillic alphabet used for Russian into the 128-255 range because there are more than 127 such characters.

You could write ﬁles using different codes (all your Russian ﬁles in a coding system called KOI8, all your French

ﬁles in a different coding system called Latin1), but what if you wanted to write a French document that quotes

some Russian text? In the 1980s people began to want to solve this problem, and the Unicode standardization

effort began.

Unicode started out using 16-bit characters instead of 8-bit characters. 16 bits means you have 2^16 = 65,536

distinct values available, making it possible to represent many different characters from many different alphabets;

an initial goal was to have Unicode contain the alphabets for every single human language. It turns out that even 16

bits isn’t enough to meet that goal, and the modern Unicode speciﬁcation uses a wider range of codes, 0-1,114,111

(0x10ffff in base-16).

There’s a related ISO standard, ISO 10646. Unicode and ISO 10646 were originally separate efforts, but the

speciﬁcations were merged with the 1.1 revision of Unicode.

(This discussion of Unicode’s history is highly simpliﬁed. I don’t think the average Python programmer needs to

worry about the historical details; consult the Unicode consortium site listed in the References for more informa-

tion.)

1.2 Deﬁnitions

Acharacteris the smallest possible component of a text. ‘A’, ‘B’, ‘C’, etc., are all different characters. So are

‘È’ and ‘Í’. Characters are abstractions, and vary depending on the language or context you’re talking about. For

example, the symbol for ohms ( ) is usually drawn much like the capital letter omega ( ) in the Greek alphabet

(they may even be the same in some fonts), but these are two different characters that have different meanings.

The Unicode standard describes how characters are represented bycodepoints. A code point is an integer value,

usually denoted in base 16. In the standard, a code point is written using the notation U+12ca to mean the

character with value 0x12ca (4810 decimal). The Unicode standard contains a lot of tables listing characters and

their corresponding code points:

0061 ’a’;LATINSMALLLETTERA

0062 ’b’;LATINSMALLLETTERB

0063 ’c’;LATINSMALLLETTERC

...

007B ’{’;LEFTCURLYBRACKET

Strictly, these deﬁnitions imply that it’s meaningless to say ‘this is character U+12ca’. U+12ca is a code point,

which represents some particular character; in this case, it represents the character ‘ETHIOPIC SYLLABLE WI’.

In informal contexts, this distinction between code points and characters will sometimes be forgotten.

A character is represented on a screen or on paper by a set of graphical elements that’s called aglyph. The glyph

for an uppercase A, for example, is two diagonal strokes and a horizontal stroke, though the exact details will

depend on the font being used. Most Python code doesn’t need to worry about glyphs; ﬁguring out the correct

glyph to display is generally the job of a GUI toolkit or a terminal’s font renderer.

1.3 Encodings

To summarize the previous section: a Unicode string is a sequence of code points, which are numbers from 0 to

0x10ffff. This sequence needs to be represented as a set of bytes (meaning, values from 0-255) in memory. The

rules for translating a Unicode string into a sequence of bytes are called anencoding.

The ﬁrst encoding you might think of is an array of 32-bit integers. In this representation, the string “Python”

would look like this:

P y t h o n

0x500000007900000074000000680000006f0000006e000000

01234567891011121314151617181920212223

This representation is straightforward but using it presents a number of problems.

1. It’s not portable; different processors order the bytes differently.

2. It’s very wasteful of space. In most texts, the majority of the code points are less than 127, or less than

255, so a lot of space is occupied by zero bytes. The above string takes 24 bytes compared to the 6 bytes

needed for an ASCII representation. Increased RAM usage doesn’t matter too much (desktop computers

have megabytes of RAM, and strings aren’t usually that large), but expanding our usage of disk and network

bandwidth by a factor of 4 is intolerable.

3. It’s not compatible with existing C functions such as strlen() , so a new family of wide string functions

would need to be used.

4. Many Internet standards are deﬁned in terms of textual data, and can’t handle content with embedded zero

bytes.

Generally people don’t use this encoding, instead choosing other encodings that are more efﬁcient and convenient.

UTF-8 is probably the most commonly supported encoding; it will be discussed below.

Encodings don’t have to handle every possible Unicode character, and most encodings don’t.

For example,

Python’s default encoding is the ‘ascii’ encoding.

The rules for converting a Unicode string into the ASCII

encoding are simple; for each code point:

1. If the code point is < 128, each byte is the same as the value of the code point.

2. If the code point is 128 or greater, the Unicode string can’t be represented in this encoding. (Python raises

a UnicodeEncodeError exception in this case.)

Latin-1, also known as ISO-8859-1, is a similar encoding. Unicode code points 0-255 are identical to the Latin-1

values, so converting to this encoding simply requires converting code points to byte values; if a code point larger

than 255 is encountered, the string can’t be encoded into Latin-1.

Encodings don’t have to be simple one-to-one mappings like Latin-1. Consider IBM’s EBCDIC, which was used

on IBM mainframes. Letter values weren’t in one block: ‘a’ through ‘i’ had values from 129 to 137, but ‘j’ through

‘r’ were 145 through 153. If you wanted to use EBCDIC as an encoding, you’d probably use some sort of lookup

table to perform the conversion, but this is largely an internal detail.

UTF-8 is one of the most commonly used encodings. UTF stands for “Unicode Transformation Format”, and the

‘8’ means that 8-bit numbers are used in the encoding. (There’s also a UTF-16 encoding, but it’s less frequently

used than UTF-8.) UTF-8 uses the following rules:

1. If the code point is <128, it’s represented by the corresponding byte value.

2. If the code point is between 128 and 0x7ff, it’s turned into two byte values between 128 and 255.

3. Code points >0x7ff are turned into three- or four-byte sequences, where each byte of the sequence is between

128 and 255.

UTF-8 has several convenient properties:

1. It can handle any Unicode code point.

2. A Unicode string is turned into a string of bytes containing no embedded zero bytes. This avoids byte-

ordering issues, and means UTF-8 strings can be processed by C functions such as strcpy() and sent

through protocols that can’t handle zero bytes.

3. A string of ASCII text is also valid UTF-8 text.

4. UTF-8 is fairly compact; the majority of code points are turned into two bytes, and values less than 128

occupy only a single byte.

5. If bytes are corrupted or lost, it’s possible to determine the start of the next UTF-8-encoded code point and

resynchronize. It’s also unlikely that random 8-bit data will look like valid UTF-8.

1.4 References

The Unicode Consortium site at < http://www.unicode.org > has character charts, a glossary, and PDF versions

of the Unicode speciﬁcation.

Be prepared for some difﬁcult reading.

< http://www.unicode.org/history/ > is a

chronology of the origin and development of Unicode.

To help understand the standard, Jukka Korpela has written an introductory guide to reading the Unicode character

tables, available at < http://www.cs.tut.ﬁ/~jkorpela/unicode/guide.html > .

Another good introductory article was written by Joel Spolsky < http://www.joelonsoftware.com/articles/Unicode.html > .

If this introduction didn’t make things clear to you, you should try reading this alternate article before continuing.

Wikipedia

entries

are

often

helpful;

see

the

entries

for

“character

encoding”

< http://en.wikipedia.org/wiki/Character_encoding >

and

UTF-8

< http://en.wikipedia.org/wiki/UTF-8 > ,

for

example.

2 Python 2.x’s Unicode Support

Now that you’ve learned the rudiments of Unicode, we can look at Python’s Unicode features.

2.1 The Unicode Type

Unicode strings are expressed as instances of the unicode type, one of Python’s repertoire of built-in types. It

derives from an abstract type called basestring , which is also an ancestor of the str type; you can therefore

check if a value is a string type with isinstance(value,basestring) . Under the hood, Python repre-

sents Unicode strings as either 16- or 32-bit integers, depending on how the Python interpreter was compiled.

The unicode() constructor has the signature unicode(string[,encoding,errors]) . All of its

arguments should be 8-bit strings. The ﬁrst argument is converted to Unicode using the speciﬁed encoding; if you

leave off the encoding argument, the ASCII encoding is used for the conversion, so characters greater than 127

will be treated as errors:

>>> unicode ( ’abcdef’ )

u’abcdef’

>>> s = unicode ( ’abcdef’ )

>>> type (s)

<type’unicode’>

>>> unicode ( ’abcdef’ + chr ( 255 ))

Traceback(mostrecentcalllast):

...

UnicodeDecodeError :’ascii’codeccan’tdecodebyte0xffinposition6:

ordinalnotinrange(128)

The errors argument speciﬁes the response when the input string can’t be converted according to the encoding’s

rules. Legal values for this argument are ‘strict’ (raise a UnicodeDecodeError exception), ‘replace’ (add

U+FFFD, ‘REPLACEMENT CHARACTER’), or ‘ignore’ (just leave the character out of the Unicode result).

The following examples show the differences:

>>> unicode ( ’ \x80 abc’ ,errors = ’strict’ )

Traceback(mostrecentcalllast):

...

UnicodeDecodeError :’ascii’codeccan’tdecodebyte0x80inposition0:

ordinalnotinrange(128)

>>> unicode ( ’ \x80 abc’ ,errors = ’replace’ )

u’\ufffdabc’

>>> unicode ( ’ \x80 abc’ ,errors = ’ignore’ )

u’abc’

Encodings are speciﬁed as strings containing the encoding’s name. Python 2.7 comes with roughly 100 different

encodings; see the Python Library Reference atstandard-encodingsfor a list. Some encodings have multiple

names; for example, ‘latin-1’, ‘iso_8859_1’ and ‘8859’ are all synonyms for the same encoding.

One-character Unicode strings can also be created with the unichr() built-in function, which takes integers

and returns a Unicode string of length 1 that contains the corresponding code point. The reverse operation is the

built-in ord() function that takes a one-character Unicode string and returns the code point value:

>>> unichr ( 40960 )

u’\ua000’

>>> ord ( u’ \ua000 ’ )

40960

Instances of the unicode type have many of the same methods as the 8-bit string type for operations such as

searching and formatting:

>>> s = u’Waseverfeathersolightlyblowntoandfroasthismultitude?’

>>> s . count( ’e’ )

>>> s . find( ’feather’ )

>>> s . find( ’bird’ )

-1

>>> s . replace( ’feather’ , ’sand’ )

u’Waseversandsolightlyblowntoandfroasthismultitude?’

>>> s . upper()

u’WASEVERFEATHERSOLIGHTLYBLOWNTOANDFROASTHISMULTITUDE?’

Note that the arguments to these methods can be Unicode strings or 8-bit strings. 8-bit strings will be converted

to Unicode before carrying out the operation; Python’s default ASCII encoding will be used, so characters greater

than 127 will cause an exception:

>>> s . find( ’Was \x9f ’ )

Traceback(mostrecentcalllast):

...

UnicodeDecodeError :’ascii’codeccan’tdecodebyte0x9finposition3:

ordinalnotinrange(128)

>>> s . find( u’Was \x9f ’ )

-1

Much Python code that operates on strings will therefore work with Unicode strings without requiring any changes

to the code. (Input and output code needs more updating for Unicode; more on this later.)

Another important method is .encode([encoding],[errors=’strict’]) , which returns an 8-bit

string version of the Unicode string, encoded in the requested encoding. The errors parameter is the same

as the parameter of the unicode() constructor, with one additional possibility; as well as ‘strict’, ‘ignore’, and

‘replace’, you can also pass ‘xmlcharrefreplace’ which uses XML’s character references. The following example

shows the different results:

Plik z chomika:

Inne pliki z tego folderu:

Inne foldery tego chomika: