| Python 3.6.5 Documentation > Unicode HOWTO
Unicode HOWTO
*************
Release:
1.12
This HOWTO discusses Python support for Unicode, and explains various
problems that people commonly encounter when trying to work with
Unicode.
Introduction to Unicode
=======================
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. In
the mid-1980s an Apple II BASIC program written by a French speaker
might have lines like these:
PRINT "MISE A JOUR TERMINEE"
PRINT "PARAMETRES ENREGISTRES"
Those messages should contain accents (terminée, paramètre,
enregistrés) 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 Organization for
Standardization, and some were *de facto* conventions 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
128 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 through 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. The
precise historical details aren’t necessary for understanding how to
use Unicode effectively, but if you’re curious, consult the Unicode
consortium site listed in the References or the Wikipedia entry for
Unicode for more information.)
Definitions
-----------
A **character** is 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 (Ω) 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 by
**code points**. 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" (4,810 decimal).
The Unicode standard contains a lot of tables listing characters and
their corresponding code points:
0061 'a'; LATIN SMALL LETTER A
0062 'b'; LATIN SMALL LETTER B
0063 'c'; LATIN SMALL LETTER C
...
007B '{'; LEFT CURLY BRACKET
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 a **glyph**. 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.
Encodings
---------
To summarize the previous section: a Unicode string is a sequence of
code points, which are numbers from 0 through "0x10FFFF" (1,114,111
decimal). This sequence needs to be represented as a set of bytes
(meaning, values from 0 through 255) in memory. The rules for
translating a Unicode string into a sequence of bytes are called an
**encoding**.
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
0x50 00 00 00 79 00 00 00 74 00 00 00 68 00 00 00 6f 00 00 00 6e 00 00 00
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
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 "0x00" 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
gigabytes 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. The rules for converting a Unicode string into
the ASCII encoding, for example, 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 are also a UTF-16 and UTF-32
encodings, but they are 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 >= 128, it’s turned into a sequence of two,
three, or four bytes, 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 sequence 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 commonly used
characters can be represented with one or two bytes.
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.
References
----------
The Unicode Consortium site has character charts, a glossary, and PDF
versions of the Unicode specification. Be prepared for some difficult
reading. A chronology of the origin and development of Unicode is
also available on the site.
To help understand the standard, Jukka Korpela has written an
introductory guide to reading the Unicode character tables.
Another good introductory article was written by Joel Spolsky. 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” and UTF-8, for example.
Python’s Unicode Support
========================
Now that you’ve learned the rudiments of Unicode, we can look at
Python’s Unicode features.
The String Type
---------------
Since Python 3.0, the language features a "str" type that contain
Unicode characters, meaning any string created using ""unicode
rocks!"", "'unicode rocks!'", or the triple-quoted string syntax is
stored as Unicode.
The default encoding for Python source code is UTF-8, so you can
simply include a Unicode character in a string literal:
try:
with open('/tmp/input.txt', 'r') as f:
...
except OSError:
# 'File not found' error message.
print("Fichier non trouvé")
You can use a different encoding from UTF-8 by putting a specially-
formatted comment as the first or second line of the source code:
# -*- coding: <encoding name> -*-
Side note: Python 3 also supports using Unicode characters in
identifiers:
répertoire = "/tmp/records.log"
with open(répertoire, "w") as f:
f.write("test\n")
If you can’t enter a particular character in your editor or want to
keep the source code ASCII-only for some reason, you can also use
escape sequences in string literals. (Depending on your system, you
may see the actual capital-delta glyph instead of a u escape.)
>>> "\N{GREEK CAPITAL LETTER DELTA}" # Using the character name
'\u0394'
>>> "\u0394" # Using a 16-bit hex value
'\u0394'
>>> "\U00000394" # Using a 32-bit hex value
'\u0394'
In addition, one can create a string using the "decode()" method of
"bytes". This method takes an *encoding* argument, such as "UTF-8",
and optionally an *errors* argument.
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'" (use "U+FFFD", "REPLACEMENT CHARACTER"),
"'ignore'" (just leave the character out of the Unicode result), or
"'backslashreplace'" (inserts a "\xNN" escape sequence). The following
examples show the differences:
>>> b'\x80abc'.decode("utf-8", "strict") #doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
...
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0:
invalid start byte
>>> b'\x80abc'.decode("utf-8", "replace")
'\ufffdabc'
>>> b'\x80abc'.decode("utf-8", "backslashreplace")
'\\x80abc'
>>> b'\x80abc'.decode("utf-8", "ignore")
'abc'
Encodings are specified as strings containing the encoding’s name.
Python 3.2 comes with roughly 100 different encodings; see the Python
Library Reference at Standard Encodings for 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 "chr()"
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:
>>> chr(57344)
'\ue000'
>>> ord('\ue000')
57344
Converting to Bytes
-------------------
The opposite method of "bytes.decode()" is "str.encode()", which
returns a "bytes" representation of the Unicode string, encoded in the
requested *encoding*.
The *errors* parameter is the same as the parameter of the "decode()"
method but supports a few more possible handlers. As well as
"'strict'", "'ignore'", and "'replace'" (which in this case inserts a
question mark instead of the unencodable character), there is also
"'xmlcharrefreplace'" (inserts an XML character reference),
"backslashreplace" (inserts a "\uNNNN" escape sequence) and
"namereplace" (inserts a "\N{...}" escape sequence).
The following example shows the different results:
>>> u = chr(40960) + 'abcd' + chr(1972)
>>> u.encode('utf-8')
b'\xea\x80\x80abcd\xde\xb4'
>>> u.encode('ascii') #doctest: +NORMALIZE_WHITESPACE
Traceback (most recent call last):
...
UnicodeEncodeError: 'ascii' codec can't encode character '\ua000' in
position 0: ordinal not in range(128)
>>> u.encode('ascii', 'ignore')
b'abcd'
>>> u.encode('ascii', 'replace')
b'?abcd?'
>>> u.encode('ascii', 'xmlcharrefreplace')
b'ꀀabcd޴'
>>> u.encode('ascii', 'backslashreplace')
b'\\ua000abcd\\u07b4'
>>> u.encode('ascii', 'namereplace')
b'\\N{YI SYLLABLE IT}abcd\\u07b4'
The low-level routines for registering and accessing the available
encodings are found in the "codecs" module. Implementing new
encodings also requires understanding the "codecs" module. However,
the encoding and decoding functions returned by this module are
usually more low-level than is comfortable, and writing new encodings
is a specialized task, so the module won’t be covered in this HOWTO.
Unicode Literals in Python Source Code
--------------------------------------
In Python source code, specific Unicode code points can be written
using the "\u" escape sequence, which is followed by four hex digits
giving the code point. The "\U" escape sequence is similar, but
expects eight hex digits, not four:
>>> s = "a\xac\u1234\u20ac\U00008000"
... # ^^^^ two-digit hex escape
... # ^^^^^^ four-digit Unicode escape
... # ^^^^^^^^^^ eight-digit Unicode escape
>>> [ord(c) for c in s]
[97, 172, 4660, 8364, 32768]
Using escape sequences for code points greater than 127 is fine in
small doses, but becomes an annoyance if you’re using many accented
characters, as you would in a program with messages in French or some
other accent-using language. You can also assemble strings using the
"chr()" built-in function, but this is even more tedious.
Ideally, you’d want to be able to write literals in your language’s
natural encoding. You could then edit Python source code with your
favorite editor which would display the accented characters naturally,
and have the right characters used at runtime.
Python supports writing source code in UTF-8 by default, but you can
use almost any encoding if you declare the encoding being used. This
is done by including a special comment as either the first or second
line of the source file:
#!/usr/bin/env python
# -*- coding: latin-1 -*-
u = 'abcdé'
print(ord(u[-1]))
The syntax is inspired by Emacs’s notation for specifying variables
local to a file. Emacs supports many different variables, but Python
only supports ‘coding’. The "-*-" symbols indicate to Emacs that the
comment is special; they have no significance to Python but are a
convention. Python looks for "coding: name" or "coding=name" in the
comment.
If you don’t include such a comment, the default encoding used will be
UTF-8 as already mentioned. See also **PEP 263** for more
information.
Unicode Properties
------------------
The Unicode specification includes a database of information about
code points. For each defined code point, the information includes the
character’s name, its category, the numeric value if applicable
(Unicode has characters representing the Roman numerals and fractions
such as one-third and four-fifths). There are also properties related
to the code point’s use in bidirectional text and other display-
related properties.
The following program displays some information about several
characters, and prints the numeric value of one particular character:
import unicodedata
u = chr(233) + chr(0x0bf2) + chr(3972) + chr(6000) + chr(13231)
for i, c in enumerate(u):
print(i, '%04x' % ord(c), unicodedata.category(c), end=" ")
print(unicodedata.name(c))
# Get numeric value of second character
print(unicodedata.numeric(u[1]))
When run, this prints:
0 00e9 Ll LATIN SMALL LETTER E WITH ACUTE
1 0bf2 No TAMIL NUMBER ONE THOUSAND
2 0f84 Mn TIBETAN MARK HALANTA
3 1770 Lo TAGBANWA LETTER SA
4 33af So SQUARE RAD OVER S SQUARED
1000.0
The category codes are abbreviations describing the nature of the
character. These are grouped into categories such as “Letter”,
“Number”, “Punctuation”, or “Symbol”, which in turn are broken up into
subcategories. To take the codes from the above output, "'Ll'" means
‘Letter, lowercase’, "'No'" means “Number, other”, "'Mn'" is “Mark,
nonspacing”, and "'So'" is “Symbol, other”. See the General Category
Values section of the Unicode Character Database documentation for a
list of category codes.
Unicode Regular Expressions
---------------------------
The regular expressions supported by the "re" module can be provided
either as bytes or strings. Some of the special character sequences
such as "\d" and "\w" have different meanings depending on whether the
pattern is supplied as bytes or a string. For example, "\d" will
match the characters "[0-9]" in bytes but in strings will match any
character that’s in the "'Nd'" category.
The string in this example has the number 57 written in both Thai and
Arabic numerals:
import re
p = re.compile(r'\d+')
s = "Over \u0e55\u0e57 57 flavours"
m = p.search(s)
print(repr(m.group()))
When executed, "\d+" will match the Thai numerals and print them out.
If you supply the "re.ASCII" flag to "compile()", "\d+" will match the
substring “57” instead.
Similarly, "\w" matches a wide variety of Unicode characters but only
"[a-zA-Z0-9_]" in bytes or if "re.ASCII" is supplied, and "\s" will
match either Unicode whitespace characters or "[ \t\n\r\f\v]".
References
----------
Some good alternative discussions of Python’s Unicode support are:
* Processing Text Files in Python 3, by Nick Coghlan.
* Pragmatic Unicode, a PyCon 2012 presentation by Ned Batchelder.
The "str" type is described in the Python library reference at Text
Sequence Type — str.
The documentation for the "unicodedata" module.
The documentation for the "codecs" module.
Marc-André Lemburg gave a presentation titled “Python and Unicode”
(PDF slides) at EuroPython 2002. The slides are an excellent overview
of the design of Python 2’s Unicode features (where the Unicode string
type is called "unicode" and literals start with "u").
Reading and Writing Unicode Data
================================
Once you’ve written some code that works with Unicode data, the next
problem is input/output. How do you get Unicode strings into your
program, and how do you convert Unicode into a form suitable for
storage or transmission?
It’s possible that you may not need to do anything depending on your
input sources and output destinations; you should check whether the
libraries used in your application support Unicode natively. XML
parsers often return Unicode data, for example. Many relational
databases also support Unicode-valued columns and can return Unicode
values from an SQL query.
Unicode data is usually converted to a particular encoding before it
gets written to disk or sent over a socket. It’s possible to do all
the work yourself: open a file, read an 8-bit bytes object from it,
and convert the bytes with "bytes.decode(encoding)". However, the
manual approach is not recommended.
One problem is the multi-byte nature of encodings; one Unicode
character can be represented by several bytes. If you want to read
the file in arbitrary-sized chunks (say, 1024 or 4096 bytes), you need
to write error-handling code to catch the case where only part of the
bytes encoding a single Unicode character are read at the end of a
chunk. One solution would be to read the entire file into memory and
then perform the decoding, but that prevents you from working with
files that are extremely large; if you need to read a 2 GiB file, you
need 2 GiB of RAM. (More, really, since for at least a moment you’d
need to have both the encoded string and its Unicode version in
memory.)
The solution would be to use the low-level decoding interface to catch
the case of partial coding sequences. The work of implementing this
has already been done for you: the built-in "open()" function can
return a file-like object that assumes the file’s contents are in a
specified encoding and accepts Unicode parameters for methods such as
"read()" and "write()". This works through "open()"’s *encoding* and
*errors* parameters which are interpreted just like those in
"str.encode()" and "bytes.decode()".
Reading Unicode from a file is therefore simple:
with open('unicode.txt', encoding='utf-8') as f:
for line in f:
print(repr(line))
It’s also possible to open files in update mode, allowing both reading
and writing:
with open('test', encoding='utf-8', mode='w+') as f:
f.write('\u4500 blah blah blah\n')
f.seek(0)
print(repr(f.readline()[:1]))
The Unicode character "U+FEFF" is used as a byte-order mark (BOM), and
is often written as the first character of a file in order to assist
with autodetection of the file’s byte ordering. Some encodings, such
as UTF-16, expect a BOM to be present at the start of a file; when
such an encoding is used, the BOM will be automatically written as the
first character and will be silently dropped when the file is read.
There are variants of these encodings, such as ‘utf-16-le’ and
‘utf-16-be’ for little-endian and big-endian encodings, that specify
one particular byte ordering and don’t skip the BOM.
In some areas, it is also convention to use a “BOM” at the start of
UTF-8 encoded files; the name is misleading since UTF-8 is not byte-
order dependent. The mark simply announces that the file is encoded in
UTF-8. Use the ‘utf-8-sig’ codec to automatically skip the mark if
present for reading such files.
Unicode filenames
-----------------
Most of the operating systems in common use today support filenames
that contain arbitrary Unicode characters. Usually this is
implemented by converting the Unicode string into some encoding that
varies depending on the system. For example, Mac OS X uses UTF-8
while Windows uses a configurable encoding; on Windows, Python uses
the name “mbcs” to refer to whatever the currently configured encoding
is. On Unix systems, there will only be a filesystem encoding if
you’ve set the "LANG" or "LC_CTYPE" environment variables; if you
haven’t, the default encoding is UTF-8.
The "sys.getfilesystemencoding()" function returns the encoding to use
on your current system, in case you want to do the encoding manually,
but there’s not much reason to bother. When opening a file for
reading or writing, you can usually just provide the Unicode string as
the filename, and it will be automatically converted to the right
encoding for you:
filename = 'filename\u4500abc'
with open(filename, 'w') as f:
f.write('blah\n')
Functions in the "os" module such as "os.stat()" will also accept
Unicode filenames.
The "os.listdir()" function returns filenames and raises an issue:
should it return the Unicode version of filenames, or should it return
bytes containing the encoded versions? "os.listdir()" will do both,
depending on whether you provided the directory path as bytes or a
Unicode string. If you pass a Unicode string as the path, filenames
will be decoded using the filesystem’s encoding and a list of Unicode
strings will be returned, while passing a byte path will return the
filenames as bytes. For example, assuming the default filesystem
encoding is UTF-8, running the following program:
fn = 'filename\u4500abc'
f = open(fn, 'w')
f.close()
import os
print(os.listdir(b'.'))
print(os.listdir('.'))
will produce the following output:
amk:~$ python t.py
[b'filename\xe4\x94\x80abc', ...]
['filename\u4500abc', ...]
The first list contains UTF-8-encoded filenames, and the second list
contains the Unicode versions.
Note that on most occasions, the Unicode APIs should be used. The
bytes APIs should only be used on systems where undecodable file names
can be present, i.e. Unix systems.
Tips for Writing Unicode-aware Programs
---------------------------------------
This section provides some suggestions on writing software that deals
with Unicode.
The most important tip is:
Software should only work with Unicode strings internally, decoding
the input data as soon as possible and encoding the output only at
the end.
If you attempt to write processing functions that accept both Unicode
and byte strings, you will find your program vulnerable to bugs
wherever you combine the two different kinds of strings. There is no
automatic encoding or decoding: if you do e.g. "str + bytes", a
"TypeError" will be raised.
When using data coming from a web browser or some other untrusted
source, a common technique is to check for illegal characters in a
string before using the string in a generated command line or storing
it in a database. If you’re doing this, be careful to check the
decoded string, not the encoded bytes data; some encodings may have
interesting properties, such as not being bijective or not being fully
ASCII-compatible. This is especially true if the input data also
specifies the encoding, since the attacker can then choose a clever
way to hide malicious text in the encoded bytestream.
Converting Between File Encodings
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The "StreamRecoder" class can transparently convert between encodings,
taking a stream that returns data in encoding #1 and behaving like a
stream returning data in encoding #2.
For example, if you have an input file *f* that’s in Latin-1, you can
wrap it with a "StreamRecoder" to return bytes encoded in UTF-8:
new_f = codecs.StreamRecoder(f,
# en/decoder: used by read() to encode its results and
# by write() to decode its input.
codecs.getencoder('utf-8'), codecs.getdecoder('utf-8'),
# reader/writer: used to read and write to the stream.
codecs.getreader('latin-1'), codecs.getwriter('latin-1') )
Files in an Unknown Encoding
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
What can you do if you need to make a change to a file, but don’t know
the file’s encoding? If you know the encoding is ASCII-compatible and
only want to examine or modify the ASCII parts, you can open the file
with the "surrogateescape" error handler:
with open(fname, 'r', encoding="ascii", errors="surrogateescape") as f:
data = f.read()
# make changes to the string 'data'
with open(fname + '.new', 'w',
encoding="ascii", errors="surrogateescape") as f:
f.write(data)
The "surrogateescape" error handler will decode any non-ASCII bytes as
code points in the Unicode Private Use Area ranging from U+DC80 to
U+DCFF. These private code points will then be turned back into the
same bytes when the "surrogateescape" error handler is used when
encoding the data and writing it back out.
References
----------
One section of Mastering Python 3 Input/Output, a PyCon 2010 talk by
David Beazley, discusses text processing and binary data handling.
The PDF slides for Marc-André Lemburg’s presentation “Writing Unicode-
aware Applications in Python” discuss questions of character encodings
as well as how to internationalize and localize an application. These
slides cover Python 2.x only.
The Guts of Unicode in Python is a PyCon 2013 talk by Benjamin
Peterson that discusses the internal Unicode representation in Python
3.3.
Acknowledgements
================
The initial draft of this document was written by Andrew Kuchling. It
has since been revised further by Alexander Belopolsky, Georg Brandl,
Andrew Kuchling, and Ezio Melotti.
Thanks to the following people who have noted errors or offered
suggestions on this article: Éric Araujo, Nicholas Bastin, Nick
Coghlan, Marius Gedminas, Kent Johnson, Ken Krugler, Marc-André
Lemburg, Martin von Löwis, Terry J. Reedy, Chad Whitacre.
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