This is /home/pdm/install/Python-2.1/Doc/tut/python-tut.info, produced by makeinfo version 4.0 from tut.texi. April 15, 2001 2.1  File: python-tut.info, Node: Top, Next: Front Matter, Prev: (dir), Up: (dir) Python Tutorial *************** * Menu: * Front Matter:: * Whetting Your Appetite:: * Using the Python Interpreter:: * An Informal Introduction to Python:: * More Control Flow Tools:: * Data Structures:: * Modules:: * Input and Output:: * Errors and Exceptions:: * Classes:: * What Now?:: * Interactive Input Editing and History Substitution:: * Module Index:: * Class-Exception-Object Index:: * Function-Method-Variable Index:: * Miscellaneous Index::  File: python-tut.info, Node: Front Matter, Next: Whetting Your Appetite, Prev: Top, Up: Top Front Matter ************ Copyright (C) 2001 Python Software Foundation. All rights reserved. Copyright (C) 2000 BeOpen.com. All rights reserved. Copyright (C) 1995-2000 Corporation for National Research Initiatives. All rights reserved. Copyright (C) 1991-1995 Stichting Mathematisch Centrum. All rights reserved. *BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1* 1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the Individual or Organization ("Licensee") accessing and otherwise using this software in source or binary form and its associated documentation ("the Software"). 2. Subject to the terms and conditions of this BeOpen Python License Agreement, BeOpen hereby grants Licensee a non-exclusive, royalty-free, world-wide license to reproduce, analyze, test, perform and/or display publicly, prepare derivative works, distribute, and otherwise use the Software alone or in any derivative version, provided, however, that the BeOpen Python License is retained in the Software, alone or in any derivative version prepared by Licensee. 3. BeOpen is making the Software available to Licensee on an "AS IS" basis. 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This Agreement may also be obtained from a proxy server on the Internet using the following URL: . *CWI PERMISSIONS STATEMENT AND DISCLAIMER* Copyright (C) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam, The Netherlands. All rights reserved. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of Stichting Mathematisch Centrum or CWI not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python's elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python web site, , and can be freely distributed. The same site also contains distributions of and pointers to many free third party Python modules, programs and tools, and additional documentation. The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). Python is also suitable as an extension language for customizable applications. This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well. For a description of standard objects and modules, see the document. The gives a more formal definition of the language. To write extensions in C or C++, read and . There are also several books covering Python in depth. This tutorial does not attempt to be comprehensive and cover every single feature, or even every commonly used feature. Instead, it introduces many of Python's most noteworthy features, and will give you a good idea of the language's flavor and style. After reading it, you will be able to read and write Python modules and programs, and you will be ready to learn more about the various Python library modules described in the .  File: python-tut.info, Node: Whetting Your Appetite, Next: Using the Python Interpreter, Prev: Front Matter, Up: Top Whetting Your Appetite ********************** If you ever wrote a large shell script, you probably know this feeling: you'd love to add yet another feature, but it's already so slow, and so big, and so complicated; or the feature involves a system call or other function that is only accessible from C ...Usually the problem at hand isn't serious enough to warrant rewriting the script in C; perhaps the problem requires variable-length strings or other data types (like sorted lists of file names) that are easy in the shell but lots of work to implement in C, or perhaps you're not sufficiently familiar with C. Another situation: perhaps you have to work with several C libraries, and the usual C write/compile/test/re-compile cycle is too slow. You need to develop software more quickly. Possibly perhaps you've written a program that could use an extension language, and you don't want to design a language, write and debug an interpreter for it, then tie it into your application. In such cases, Python may be just the language for you. Python is simple to use, but it is a real programming language, offering much more structure and support for large programs than the shell has. On the other hand, it also offers much more error checking than C, and, being a _very-high-level language_, it has high-level data types built in, such as flexible arrays and dictionaries that would cost you days to implement efficiently in C. Because of its more general data types Python is applicable to a much larger problem domain than _Awk_ or even _Perl_, yet many things are at least as easy in Python as in those languages. Python allows you to split up your program in modules that can be reused in other Python programs. It comes with a large collection of standard modules that you can use as the basis of your programs -- or as examples to start learning to program in Python. There are also built-in modules that provide things like file I/O, system calls, sockets, and even interfaces to GUI toolkits like Tk. Python is an interpreted language, which can save you considerable time during program development because no compilation and linking is necessary. The interpreter can be used interactively, which makes it easy to experiment with features of the language, to write throw-away programs, or to test functions during bottom-up program development. It is also a handy desk calculator. Python allows writing very compact and readable programs. Programs written in Python are typically much shorter than equivalent C or C++ programs, for several reasons: * the high-level data types allow you to express complex operations in a single statement; * statement grouping is done by indentation instead of begin/end brackets; * no variable or argument declarations are necessary. Python is _extensible_: if you know how to program in C it is easy to add a new built-in function or module to the interpreter, either to perform critical operations at maximum speed, or to link Python programs to libraries that may only be available in binary form (such as a vendor-specific graphics library). Once you are really hooked, you can link the Python interpreter into an application written in C and use it as an extension or command language for that application. By the way, the language is named after the BBC show "Monty Python's Flying Circus" and has nothing to do with nasty reptiles. Making references to Monty Python skits in documentation is not only allowed, it is encouraged! * Menu: * Where From Here::  File: python-tut.info, Node: Where From Here, Prev: Whetting Your Appetite, Up: Whetting Your Appetite Where From Here =============== Now that you are all excited about Python, you'll want to examine it in some more detail. Since the best way to learn a language is using it, you are invited here to do so. In the next chapter, the mechanics of using the interpreter are explained. This is rather mundane information, but essential for trying out the examples shown later. The rest of the tutorial introduces various features of the Python language and system through examples, beginning with simple expressions, statements and data types, through functions and modules, and finally touching upon advanced concepts like exceptions and user-defined classes.  File: python-tut.info, Node: Using the Python Interpreter, Next: An Informal Introduction to Python, Prev: Whetting Your Appetite, Up: Top Using the Python Interpreter **************************** * Menu: * Invoking the Interpreter:: * Interpreter and Its Environment::  File: python-tut.info, Node: Invoking the Interpreter, Next: Interpreter and Its Environment, Prev: Using the Python Interpreter, Up: Using the Python Interpreter Invoking the Interpreter ======================== The Python interpreter is usually installed as `/usr/local/bin/python' on those machines where it is available; putting `/usr/local/bin' in your UNIX shell's search path makes it possible to start it by typing the command python to the shell. Since the choice of the directory where the interpreter lives is an installation option, other places are possible; check with your local Python guru or system administrator. (E.g., `/usr/local/python' is a popular alternative location.) Typing an end-of-file character ( on UNIX, on DOS or Windows) at the primary prompt causes the interpreter to exit with a zero exit status. If that doesn't work, you can exit the interpreter by typing the following commands: `import sys; sys.exit()'. The interpreter's line-editing features usually aren't very sophisticated. On UNIX, whoever installed the interpreter may have enabled support for the GNU readline library, which adds more elaborate interactive editing and history features. Perhaps the quickest check to see whether command line editing is supported is typing Control-P to the first Python prompt you get. If it beeps, you have command line editing; see Appendix *Note Interactive Input Editing and History Substitution:: for an introduction to the keys. If nothing appears to happen, or if `^P' is echoed, command line editing isn't available; you'll only be able to use backspace to remove characters from the current line. The interpreter operates somewhat like the UNIX shell: when called with standard input connected to a tty device, it reads and executes commands interactively; when called with a file name argument or with a file as standard input, it reads and executes a _script_ from that file. A third way of starting the interpreter is ``python' `-c' COMMAND [arg] ...', which executes the statement(s) in COMMAND, analogous to the shell's `-c' option. Since Python statements often contain spaces or other characters that are special to the shell, it is best to quote COMMAND in its entirety with double quotes. Note that there is a difference between `python file' and `python `>'>~'); for continuation lines it prompts with the _secondary prompt_, by default three dots (`...~'). The interpreter prints a welcome message stating its version number and a copyright notice before printing the first prompt, e.g.: python Python 1.5.2b2 (#1, Feb 28 1999, 00:02:06) [GCC 2.8.1] on sunos5 Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam >>> Continuation lines are needed when entering a multi-line construct. As an example, take a look at this `if' statement: >>> the_world_is_flat = 1 >>> if the_world_is_flat: ... print "Be careful not to fall off!" ... Be careful not to fall off!  File: python-tut.info, Node: Interpreter and Its Environment, Prev: Invoking the Interpreter, Up: Using the Python Interpreter The Interpreter and Its Environment =================================== * Menu: * Error Handling:: * Executable Python Scripts:: * Interactive Startup File::  File: python-tut.info, Node: Error Handling, Next: Executable Python Scripts, Prev: Interpreter and Its Environment, Up: Interpreter and Its Environment Error Handling -------------- When an error occurs, the interpreter prints an error message and a stack trace. In interactive mode, it then returns to the primary prompt; when input came from a file, it exits with a nonzero exit status after printing the stack trace. (Exceptions handled by an `except' clause in a `try' statement are not errors in this context.) Some errors are unconditionally fatal and cause an exit with a nonzero exit; this applies to internal inconsistencies and some cases of running out of memory. All error messages are written to the standard error stream; normal output from the executed commands is written to standard output. Typing the interrupt character (usually Control-C or DEL) to the primary or secondary prompt cancels the input and returns to the primary prompt.(1) Typing an interrupt while a command is executing raises the `KeyboardInterrupt' exception, which may be handled by a `try' statement. ---------- Footnotes ---------- (1) A problem with the GNU Readline package may prevent this.  File: python-tut.info, Node: Executable Python Scripts, Next: Interactive Startup File, Prev: Error Handling, Up: Interpreter and Its Environment Executable Python Scripts ------------------------- On BSD'ish UNIX systems, Python scripts can be made directly executable, like shell scripts, by putting the line #! /usr/bin/env python (assuming that the interpreter is on the user's `PATH') at the beginning of the script and giving the file an executable mode. The `#!' must be the first two characters of the file. Note that the hash, or pound, character, `#', is used to start a comment in Python.  File: python-tut.info, Node: Interactive Startup File, Prev: Executable Python Scripts, Up: Interpreter and Its Environment The Interactive Startup File ---------------------------- When you use Python interactively, it is frequently handy to have some standard commands executed every time the interpreter is started. You can do this by setting an environment variable named `PYTHONSTARTUP' to the name of a file containing your start-up commands. This is similar to the `.profile' feature of the UNIX shells. This file is only read in interactive sessions, not when Python reads commands from a script, and not when `/dev/tty' is given as the explicit source of commands (which otherwise behaves like an interactive session). It is executed in the same namespace where interactive commands are executed, so that objects that it defines or imports can be used without qualification in the interactive session. You can also change the prompts `sys.ps1' and `sys.ps2' in this file. If you want to read an additional start-up file from the current directory, you can program this in the global start-up file, e.g. `if os.path.isfile('.pythonrc.py'): execfile('.pythonrc.py')'. If you want to use the startup file in a script, you must do this explicitly in the script: import os filename = os.environ.get('PYTHONSTARTUP') if filename and os.path.isfile(filename): execfile(filename)  File: python-tut.info, Node: An Informal Introduction to Python, Next: More Control Flow Tools, Prev: Using the Python Interpreter, Up: Top An Informal Introduction to Python ********************************** In the following examples, input and output are distinguished by the presence or absence of prompts (`>`>'>~' and `...~'): to repeat the example, you must type everything after the prompt, when the prompt appears; lines that do not begin with a prompt are output from the interpreter. Note that a secondary prompt on a line by itself in an example means you must type a blank line; this is used to end a multi-line command. Many of the examples in this manual, even those entered at the interactive prompt, include comments. Comments in Python start with the hash character, `#', and extend to the end of the physical line. A comment may appear at the start of a line or following whitespace or code, but not within a string literal. A hash character within a string literal is just a hash character. Some examples: # this is the first comment SPAM = 1 # and this is the second comment # ... and now a third! STRING = "# This is not a comment." * Menu: * Using Python as a Calculator:: * First Steps Towards Programming::  File: python-tut.info, Node: Using Python as a Calculator, Next: First Steps Towards Programming, Prev: An Informal Introduction to Python, Up: An Informal Introduction to Python Using Python as a Calculator ============================ Let's try some simple Python commands. Start the interpreter and wait for the primary prompt, `>`>'>~'. (It shouldn't take long.) * Menu: * Numbers:: * Strings:: * Unicode Strings:: * Lists::  File: python-tut.info, Node: Numbers, Next: Strings, Prev: Using Python as a Calculator, Up: Using Python as a Calculator Numbers ------- The interpreter acts as a simple calculator: you can type an expression at it and it will write the value. Expression syntax is straightforward: the operators `+', `-', `*' and `/' work just like in most other languages (for example, Pascal or C); parentheses can be used for grouping. For example: >>> 2+2 4 >>> # This is a comment ... 2+2 4 >>> 2+2 # and a comment on the same line as code 4 >>> (50-5*6)/4 5 >>> # Integer division returns the floor: ... 7/3 2 >>> 7/-3 -3 Like in C, the equal sign (`=') is used to assign a value to a variable. The value of an assignment is not written: >>> width = 20 >>> height = 5*9 >>> width * height 900 A value can be assigned to several variables simultaneously: >>> x = y = z = 0 # Zero x, y and z >>> x 0 >>> y 0 >>> z 0 There is full support for floating point; operators with mixed type operands convert the integer operand to floating point: >>> 4 * 2.5 / 3.3 3.0303030303 >>> 7.0 / 2 3.5 Complex numbers are also supported; imaginary numbers are written with a suffix of `j' or `J'. Complex numbers with a nonzero real component are written as `(REAL+IMAGj)', or can be created with the `complex(REAL, IMAG)' function. >>> 1j * 1J (-1+0j) >>> 1j * complex(0,1) (-1+0j) >>> 3+1j*3 (3+3j) >>> (3+1j)*3 (9+3j) >>> (1+2j)/(1+1j) (1.5+0.5j) Complex numbers are always represented as two floating point numbers, the real and imaginary part. To extract these parts from a complex number Z, use `Z.real' and `Z.imag'. >>> a=1.5+0.5j >>> a.real 1.5 >>> a.imag 0.5 The conversion functions to floating point and integer (`float()', `int()' and `long()') don't work for complex numbers -- there is no one correct way to convert a complex number to a real number. Use `abs(Z)' to get its magnitude (as a float) or `z.real' to get its real part. >>> a=1.5+0.5j >>> float(a) Traceback (most recent call last): File "", line 1, in ? TypeError: can't convert complex to float; use e.g. abs(z) >>> a.real 1.5 >>> abs(a) 1.58113883008 In interactive mode, the last printed expression is assigned to the variable `_'. This means that when you are using Python as a desk calculator, it is somewhat easier to continue calculations, for example: >>> tax = 17.5 / 100 >>> price = 3.50 >>> price * tax 0.61249999999999993 >>> price + _ 4.1124999999999998 >>> round(_, 2) 4.1100000000000003 This variable should be treated as read-only by the user. Don't explicitly assign a value to it -- you would create an independent local variable with the same name masking the built-in variable with its magic behavior.  File: python-tut.info, Node: Strings, Next: Unicode Strings, Prev: Numbers, Up: Using Python as a Calculator Strings ------- Besides numbers, Python can also manipulate strings, which can be expressed in several ways. They can be enclosed in single quotes or double quotes: >>> 'spam eggs' 'spam eggs' >>> 'doesn\'t' "doesn't" >>> "doesn't" "doesn't" >>> '"Yes," he said.' '"Yes," he said.' >>> "\"Yes,\" he said." '"Yes," he said.' >>> '"Isn\'t," she said.' '"Isn\'t," she said.' String literals can span multiple lines in several ways. Newlines can be escaped with backslashes, e.g.: hello = "This is a rather long string containing\n\ several lines of text just as you would do in C.\n\ Note that whitespace at the beginning of the line is\ significant.\n" print hello which would print the following: This is a rather long string containing several lines of text just as you would do in C. Note that whitespace at the beginning of the line is significant. Or, strings can be surrounded in a pair of matching triple-quotes: `"""' or `''''. End of lines do not need to be escaped when using triple-quotes, but they will be included in the string. print """ Usage: thingy [OPTIONS] -h Display this usage message -H hostname Hostname to connect to """ produces the following output: Usage: thingy [OPTIONS] -h Display this usage message -H hostname Hostname to connect to The interpreter prints the result of string operations in the same way as they are typed for input: inside quotes, and with quotes and other funny characters escaped by backslashes, to show the precise value. The string is enclosed in double quotes if the string contains a single quote and no double quotes, else it's enclosed in single quotes. (The `print' statement, described later, can be used to write strings without quotes or escapes.) Strings can be concatenated (glued together) with the `+' operator, and repeated with `*': >>> word = 'Help' + 'A' >>> word 'HelpA' >>> '<' + word*5 + '>' '' Two string literals next to each other are automatically concatenated; the first line above could also have been written `word = 'Help' 'A''; this only works with two literals, not with arbitrary string expressions: >>> import string >>> 'str' 'ing' # <- This is ok 'string' >>> string.strip('str') + 'ing' # <- This is ok 'string' >>> string.strip('str') 'ing' # <- This is invalid File "", line 1 string.strip('str') 'ing' ^ SyntaxError: invalid syntax Strings can be subscripted (indexed); like in C, the first character of a string has subscript (index) 0. There is no separate character type; a character is simply a string of size one. Like in Icon, substrings can be specified with the _slice notation_: two indices separated by a colon. >>> word[4] 'A' >>> word[0:2] 'He' >>> word[2:4] 'lp' Unlike a C string, Python strings cannot be changed. Assigning to an indexed position in the string results in an error: >>> word[0] = 'x' Traceback (most recent call last): File "", line 1, in ? TypeError: object doesn't support item assignment >>> word[:1] = 'Splat' Traceback (most recent call last): File "", line 1, in ? TypeError: object doesn't support slice assignment However, creating a new string with the combined content is easy and efficient: >>> 'x' + word[1:] 'xelpA' >>> 'Splat' + word[4] 'SplatA' Slice indices have useful defaults; an omitted first index defaults to zero, an omitted second index defaults to the size of the string being sliced. >>> word[:2] # The first two characters 'He' >>> word[2:] # All but the first two characters 'lpA' Here's a useful invariant of slice operations: `s[:i] + s[i:]' equals `s'. >>> word[:2] + word[2:] 'HelpA' >>> word[:3] + word[3:] 'HelpA' Degenerate slice indices are handled gracefully: an index that is too large is replaced by the string size, an upper bound smaller than the lower bound returns an empty string. >>> word[1:100] 'elpA' >>> word[10:] '' >>> word[2:1] '' Indices may be negative numbers, to start counting from the right. For example: >>> word[-1] # The last character 'A' >>> word[-2] # The last-but-one character 'p' >>> word[-2:] # The last two characters 'pA' >>> word[:-2] # All but the last two characters 'Hel' But note that -0 is really the same as 0, so it does not count from the right! >>> word[-0] # (since -0 equals 0) 'H' Out-of-range negative slice indices are truncated, but don't try this for single-element (non-slice) indices: >>> word[-100:] 'HelpA' >>> word[-10] # error Traceback (most recent call last): File "", line 1 IndexError: string index out of range The best way to remember how slices work is to think of the indices as pointing _between_ characters, with the left edge of the first character numbered 0. Then the right edge of the last character of a string of N characters has index N, for example: +---+---+---+---+---+ | H | e | l | p | A | +---+---+---+---+---+ 0 1 2 3 4 5 -5 -4 -3 -2 -1 The first row of numbers gives the position of the indices 0...5 in the string; the second row gives the corresponding negative indices. The slice from I to J consists of all characters between the edges labeled I and J, respectively. For non-negative indices, the length of a slice is the difference of the indices, if both are within bounds, e.g., the length of `word[1:3]' is 2. The built-in function `len()' returns the length of a string: >>> s = 'supercalifragilisticexpialidocious' >>> len(s) 34  File: python-tut.info, Node: Unicode Strings, Next: Lists, Prev: Strings, Up: Using Python as a Calculator Unicode Strings --------------- This section was written by Marc-Andre Lemburg . Starting with Python 2.0 a new data type for storing text data is available to the programmer: the Unicode object. It can be used to store and manipulate Unicode data (see ) and integrates well with the existing string objects providing auto-conversions where necessary. Unicode has the advantage of providing one ordinal for every character in every script used in modern and ancient texts. Previously, there were only 256 possible ordinals for script characters and texts were typically bound to a code page which mapped the ordinals to script characters. This lead to very much confusion especially with respect to internationalization (usually written as `i18n' -- `i' + 18 characters + `n') of software. Unicode solves these problems by defining one code page for all scripts. Creating Unicode strings in Python is just as simple as creating normal strings: >>> u'Hello World !' u'Hello World !' The small `u' in front of the quote indicates that an Unicode string is supposed to be created. If you want to include special characters in the string, you can do so by using the Python _Unicode-Escape_ encoding. The following example shows how: >>> u'Hello\u0020World !' u'Hello World !' The escape sequence `\u0020' indicates to insert the Unicode character with the ordinal value 0x0020 (the space character) at the given position. Other characters are interpreted by using their respective ordinal values directly as Unicode ordinals. If you have literal strings in the standard Latin-1 encoding that is used in many Western countries, you will find it convenient that the lower 256 characters of Unicode are the same as the 256 characters of Latin-1. For experts, there is also a raw mode just like the one for normal strings. You have to prefix the opening quote with 'ur' to have Python use the _Raw-Unicode-Escape_ encoding. It will only apply the above `\uXXXX' conversion if there is an uneven number of backslashes in front of the small 'u'. >>> ur'Hello\u0020World !' u'Hello World !' >>> ur'Hello\\u0020World !' u'Hello\\\\u0020World !' The raw mode is most useful when you have to enter lots of backslashes e.g. in regular expressions. Apart from these standard encodings, Python provides a whole set of other ways of creating Unicode strings on the basis of a known encoding. The built-in function `unicode()' provides access to all registered Unicode codecs (COders and DECoders). Some of the more well known encodings which these codecs can convert are _Latin-1_, _ASCII_, _UTF-8_, and _UTF-16_. The latter two are variable-length encodings that store each Unicode character in one or more bytes. The default encoding is normally set to ASCII, which passes through characters in the range 0 to 127 and rejects any other characters with an error. When a Unicode string is printed, written to a file, or converted with `str()', conversion takes place using this default encoding. >>> u"abc" u'abc' >>> str(u"abc") 'abc' >>> u"äöü" u'\xe4\xf6\xfc' >>> str(u"äöü") Traceback (most recent call last): File "", line 1, in ? UnicodeError: ASCII encoding error: ordinal not in range(128) To convert a Unicode string into an 8-bit string using a specific encoding, Unicode objects provide an `encode()' method that takes one argument, the name of the encoding. Lowercase names for encodings are preferred. >>> u"äöü".encode('utf-8') '\xc3\xa4\xc3\xb6\xc3\xbc' If you have data in a specific encoding and want to produce a corresponding Unicode string from it, you can use the `unicode()' function with the encoding name as the second argument. >>> unicode('\xc3\xa4\xc3\xb6\xc3\xbc', 'utf-8') u'\xe4\xf6\xfc'  File: python-tut.info, Node: Lists, Prev: Unicode Strings, Up: Using Python as a Calculator Lists ----- Python knows a number of _compound_ data types, used to group together other values. The most versatile is the _list_, which can be written as a list of comma-separated values (items) between square brackets. List items need not all have the same type. >>> a = ['spam', 'eggs', 100, 1234] >>> a ['spam', 'eggs', 100, 1234] Like string indices, list indices start at 0, and lists can be sliced, concatenated and so on: >>> a[0] 'spam' >>> a[3] 1234 >>> a[-2] 100 >>> a[1:-1] ['eggs', 100] >>> a[:2] + ['bacon', 2*2] ['spam', 'eggs', 'bacon', 4] >>> 3*a[:3] + ['Boe!'] ['spam', 'eggs', 100, 'spam', 'eggs', 100, 'spam', 'eggs', 100, 'Boe!'] Unlike strings, which are _immutable_, it is possible to change individual elements of a list: >>> a ['spam', 'eggs', 100, 1234] >>> a[2] = a[2] + 23 >>> a ['spam', 'eggs', 123, 1234] Assignment to slices is also possible, and this can even change the size of the list: >>> # Replace some items: ... a[0:2] = [1, 12] >>> a [1, 12, 123, 1234] >>> # Remove some: ... a[0:2] = [] >>> a [123, 1234] >>> # Insert some: ... a[1:1] = ['bletch', 'xyzzy'] >>> a [123, 'bletch', 'xyzzy', 1234] >>> a[:0] = a # Insert (a copy of) itself at the beginning >>> a [123, 'bletch', 'xyzzy', 1234, 123, 'bletch', 'xyzzy', 1234] The built-in function `len()' also applies to lists: >>> len(a) 8 It is possible to nest lists (create lists containing other lists), for example: >>> q = [2, 3] >>> p = [1, q, 4] >>> len(p) 3 >>> p[1] [2, 3] >>> p[1][0] 2 >>> p[1].append('xtra') # See section 5.1 >>> p [1, [2, 3, 'xtra'], 4] >>> q [2, 3, 'xtra'] Note that in the last example, `p[1]' and `q' really refer to the same object! We'll come back to _object semantics_ later.  File: python-tut.info, Node: First Steps Towards Programming, Prev: Using Python as a Calculator, Up: An Informal Introduction to Python First Steps Towards Programming =============================== Of course, we can use Python for more complicated tasks than adding two and two together. For instance, we can write an initial sub-sequence of the _Fibonacci_ series as follows: >>> # Fibonacci series: ... # the sum of two elements defines the next ... a, b = 0, 1 >>> while b < 10: ... print b ... a, b = b, a+b ... 1 1 2 3 5 8 This example introduces several new features. * The first line contains a _multiple assignment_: the variables `a' and `b' simultaneously get the new values 0 and 1. On the last line this is used again, demonstrating that the expressions on the right-hand side are all evaluated first before any of the assignments take place. The right-hand side expressions are evaluated from the left to the right. * The `while' loop executes as long as the condition (here: `b < 10') remains true. In Python, like in C, any non-zero integer value is true; zero is false. The condition may also be a string or list value, in fact any sequence; anything with a non-zero length is true, empty sequences are false. The test used in the example is a simple comparison. The standard comparison operators are written the same as in C: `<' (less than), `>' (greater than), `==' (equal to), `<=' (less than or equal to), `>=' (greater than or equal to) and `!=' (not equal to). * The _body_ of the loop is _indented_: indentation is Python's way of grouping statements. Python does not (yet!) provide an intelligent input line editing facility, so you have to type a tab or space(s) for each indented line. In practice you will prepare more complicated input for Python with a text editor; most text editors have an auto-indent facility. When a compound statement is entered interactively, it must be followed by a blank line to indicate completion (since the parser cannot guess when you have typed the last line). Note that each line within a basic block must be indented by the same amount. * The `print' statement writes the value of the expression(s) it is given. It differs from just writing the expression you want to write (as we did earlier in the calculator examples) in the way it handles multiple expressions and strings. Strings are printed without quotes, and a space is inserted between items, so you can format things nicely, like this: >>> i = 256*256 >>> print 'The value of i is', i The value of i is 65536 A trailing comma avoids the newline after the output: >>> a, b = 0, 1 >>> while b < 1000: ... print b, ... a, b = b, a+b ... 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 Note that the interpreter inserts a newline before it prints the next prompt if the last line was not completed.  File: python-tut.info, Node: More Control Flow Tools, Next: Data Structures, Prev: An Informal Introduction to Python, Up: Top More Control Flow Tools *********************** Besides the `while' statement just introduced, Python knows the usual control flow statements known from other languages, with some twists. * Menu: * if Statements:: * for Statements:: * range Function:: * break and continue Statements:: * pass Statements:: * Defining Functions:: * More on Defining Functions::  File: python-tut.info, Node: if Statements, Next: for Statements, Prev: More Control Flow Tools, Up: More Control Flow Tools `if' Statements =============== Perhaps the most well-known statement type is the `if' statement. For example: >>> x = int(raw_input("Please enter a number: ")) >>> if x < 0: ... x = 0 ... print 'Negative changed to zero' ... elif x == 0: ... print 'Zero' ... elif x == 1: ... print 'Single' ... else: ... print 'More' ... There can be zero or more `elif' parts, and the `else' part is optional. The keyword ``elif'' is short for `else if', and is useful to avoid excessive indentation. An `if' ... `elif' ... `elif' ... sequence is a substitute for the `switch' or `case' statements found in other languages.  File: python-tut.info, Node: for Statements, Next: range Function, Prev: if Statements, Up: More Control Flow Tools `for' Statements ================ The `for' statement in Python differs a bit from what you may be used to in C or Pascal. Rather than always iterating over an arithmetic progression of numbers (like in Pascal), or giving the user the ability to define both the iteration step and halting condition (as C), Python's `for' statement iterates over the items of any sequence (e.g., a list or a string), in the order that they appear in the sequence. For example (no pun intended): >>> # Measure some strings: ... a = ['cat', 'window', 'defenestrate'] >>> for x in a: ... print x, len(x) ... cat 3 window 6 defenestrate 12 It is not safe to modify the sequence being iterated over in the loop (this can only happen for mutable sequence types, i.e., lists). If you need to modify the list you are iterating over, e.g., duplicate selected items, you must iterate over a copy. The slice notation makes this particularly convenient: >>> for x in a[:]: # make a slice copy of the entire list ... if len(x) > 6: a.insert(0, x) ... >>> a ['defenestrate', 'cat', 'window', 'defenestrate']  File: python-tut.info, Node: range Function, Next: break and continue Statements, Prev: for Statements, Up: More Control Flow Tools The `range()' Function ====================== If you do need to iterate over a sequence of numbers, the built-in function `range()' comes in handy. It generates lists containing arithmetic progressions, e.g.: >>> range(10) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] The given end point is never part of the generated list; `range(10)' generates a list of 10 values, exactly the legal indices for items of a sequence of length 10. It is possible to let the range start at another number, or to specify a different increment (even negative; sometimes this is called the `step'): >>> range(5, 10) [5, 6, 7, 8, 9] >>> range(0, 10, 3) [0, 3, 6, 9] >>> range(-10, -100, -30) [-10, -40, -70] To iterate over the indices of a sequence, combine `range()' and `len()' as follows: >>> a = ['Mary', 'had', 'a', 'little', 'lamb'] >>> for i in range(len(a)): ... print i, a[i] ... 0 Mary 1 had 2 a 3 little 4 lamb  File: python-tut.info, Node: break and continue Statements, Next: pass Statements, Prev: range Function, Up: More Control Flow Tools `break' and `continue' Statements, and `else' Clauses on Loops ============================================================== The `break' statement, like in C, breaks out of the smallest enclosing `for' or `while' loop. The `continue' statement, also borrowed from C, continues with the next iteration of the loop. Loop statements may have an `else' clause; it is executed when the loop terminates through exhaustion of the list (with `for') or when the condition becomes false (with `while'), but not when the loop is terminated by a `break' statement. This is exemplified by the following loop, which searches for prime numbers: >>> for n in range(2, 10): ... for x in range(2, n): ... if n % x == 0: ... print n, 'equals', x, '*', n/x ... break ... else: ... print n, 'is a prime number' ... 2 is a prime number 3 is a prime number 4 equals 2 * 2 5 is a prime number 6 equals 2 * 3 7 is a prime number 8 equals 2 * 4 9 equals 3 * 3  File: python-tut.info, Node: pass Statements, Next: Defining Functions, Prev: break and continue Statements, Up: More Control Flow Tools `pass' Statements ================= The `pass' statement does nothing. It can be used when a statement is required syntactically but the program requires no action. For example: >>> while 1: ... pass # Busy-wait for keyboard interrupt ...