mirror of https://github.com/python/cpython
3059 lines
104 KiB
TeX
3059 lines
104 KiB
TeX
\documentstyle[twoside,11pt,myformat]{report}
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\title{Python Tutorial}
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\author{
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Guido van Rossum \\
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Dept. CST, CWI, P.O. Box 94079 \\
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1090 GB Amsterdam, The Netherlands \\
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E-mail: {\tt guido@cwi.nl}
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}
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\date{14 Jul 1994 \\ Release 1.0.3} % XXX update before release!
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\begin{document}
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\pagenumbering{roman}
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\maketitle
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\begin{abstract}
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\noindent
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Python is a simple, yet powerful programming language that bridges the
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gap between C and shell programming, and is thus ideally suited for
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``throw-away programming''
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and rapid prototyping. Its syntax is put
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together from constructs borrowed from a variety of other languages;
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most prominent are influences from ABC, C, Modula-3 and Icon.
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The Python interpreter is easily extended with new functions and data
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types implemented in C. Python is also suitable as an extension
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language for highly customizable C applications such as editors or
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window managers.
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Python is available for various operating systems, amongst which
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several flavors of {\UNIX}, Amoeba, the Apple Macintosh O.S.,
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and MS-DOS.
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This tutorial introduces the reader informally to the basic concepts
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and features of the Python language and system. It helps to have a
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Python interpreter handy for hands-on experience, but as the examples
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are self-contained, the tutorial can be read off-line as well.
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For a description of standard objects and modules, see the {\em Python
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Library Reference} document. The {\em Python Reference Manual} gives
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a more formal definition of the language.
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\end{abstract}
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\pagebreak
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{
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\parskip = 0mm
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\tableofcontents
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}
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\pagebreak
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\pagenumbering{arabic}
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\chapter{Whetting Your Appetite}
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If you ever wrote a large shell script, you probably know this
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feeling: you'd love to add yet another feature, but it's already so
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slow, and so big, and so complicated; or the feature involves a system
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call or other function that is only accessible from C \ldots Usually
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the problem at hand isn't serious enough to warrant rewriting the
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script in C; perhaps because the problem requires variable-length
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strings or other data types (like sorted lists of file names) that are
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easy in the shell but lots of work to implement in C; or perhaps just
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because you're not sufficiently familiar with C.
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In such cases, Python may be just the language for you. Python is
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simple to use, but it is a real programming language, offering much
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more structure and support for large programs than the shell has. On
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the other hand, it also offers much more error checking than C, and,
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being a {\em very-high-level language}, it has high-level data types
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built in, such as flexible arrays and dictionaries that would cost you
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days to implement efficiently in C. Because of its more general data
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types Python is applicable to a much larger problem domain than {\em
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Awk} or even {\em Perl}, yet many things are at least as easy in
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Python as in those languages.
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Python allows you to split up your program in modules that can be
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reused in other Python programs. It comes with a large collection of
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standard modules that you can use as the basis of your programs --- or
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as examples to start learning to program in Python. There are also
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built-in modules that provide things like file I/O, system calls,
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sockets, and even a generic interface to window systems (STDWIN).
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Python is an interpreted language, which can save you considerable time
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during program development because no compilation and linking is
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necessary. The interpreter can be used interactively, which makes it
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easy to experiment with features of the language, to write throw-away
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programs, or to test functions during bottom-up program development.
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It is also a handy desk calculator.
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Python allows writing very compact and readable programs. Programs
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written in Python are typically much shorter than equivalent C
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programs, for several reasons:
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\begin{itemize}
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\item
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the high-level data types allow you to express complex operations in a
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single statement;
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\item
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statement grouping is done by indentation instead of begin/end
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brackets;
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\item
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no variable or argument declarations are necessary.
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\end{itemize}
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Python is {\em extensible}: if you know how to program in C it is easy
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to add a new built-in
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function or
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module to the interpreter, either to
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perform critical operations at maximum speed, or to link Python
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programs to libraries that may only be available in binary form (such
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as a vendor-specific graphics library). Once you are really hooked,
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you can link the Python interpreter into an application written in C
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and use it as an extension or command language for that application.
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By the way, the language is named after the BBC show ``Monty
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Python's Flying Circus'' and has nothing to do with nasty reptiles...
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\section{Where From Here}
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Now that you are all excited about Python, you'll want to examine it
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in some more detail. Since the best way to learn a language is
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using it, you are invited here to do so.
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In the next chapter, the mechanics of using the interpreter are
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explained. This is rather mundane information, but essential for
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trying out the examples shown later.
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The rest of the tutorial introduces various features of the Python
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language and system though examples, beginning with simple
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expressions, statements and data types, through functions and modules,
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and finally touching upon advanced concepts like exceptions
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and user-defined classes.
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When you're through with the tutorial (or just getting bored), you
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should read the Library Reference, which gives complete (though terse)
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reference material about built-in and standard types, functions and
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modules that can save you a lot of time when writing Python programs.
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\chapter{Using the Python Interpreter}
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\section{Invoking the Interpreter}
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The Python interpreter is usually installed as {\tt /usr/local/bin/python}
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on those machines where it is available; putting {\tt /usr/local/bin} in
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your {\UNIX} shell's search path makes it possible to start it by
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typing the command
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\bcode\begin{verbatim}
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python
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\end{verbatim}\ecode
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%
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to the shell. Since the choice of the directory where the interpreter
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lives is an installation option, other places are possible; check with
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your local Python guru or system administrator. (E.g., {\tt
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/usr/local/python} is a popular alternative location.)
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The interpreter operates somewhat like the {\UNIX} shell: when called
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with standard input connected to a tty device, it reads and executes
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commands interactively; when called with a file name argument or with
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a file as standard input, it reads and executes a {\em script} from
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that file.
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A third way of starting the interpreter is
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``{\tt python -c command [arg] ...}'', which
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executes the statement(s) in {\tt command}, analogous to the shell's
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{\tt -c} option. Since Python statements often contain spaces or other
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characters that are special to the shell, it is best to quote {\tt
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command} in its entirety with double quotes.
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Note that there is a difference between ``{\tt python file}'' and
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``{\tt python $<$file}''. In the latter case, input requests from the
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program, such as calls to {\tt input()} and {\tt raw_input()}, are
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satisfied from {\em file}. Since this file has already been read
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until the end by the parser before the program starts executing, the
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program will encounter EOF immediately. In the former case (which is
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usually what you want) they are satisfied from whatever file or device
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is connected to standard input of the Python interpreter.
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When a script file is used, it is sometimes useful to be able to run
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the script and enter interactive mode afterwards. This can be done by
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passing {\tt -i} before the script. (This does not work if the script
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is read from standard input, for the same reason as explained in the
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previous paragraph.)
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\subsection{Argument Passing}
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When known to the interpreter, the script name and additional
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arguments thereafter are passed to the script in the variable {\tt
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sys.argv}, which is a list of strings. Its length is at least one;
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when no script and no arguments are given, {\tt sys.argv[0]} is an
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empty string. When the script name is given as {\tt '-'} (meaning
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standard input), {\tt sys.argv[0]} is set to {\tt '-'}. When {\tt -c
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command} is used, {\tt sys.argv[0]} is set to {\tt '-c'}. Options
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found after {\tt -c command} are not consumed by the Python
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interpreter's option processing but left in {\tt sys.argv} for the
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command to handle.
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\subsection{Interactive Mode}
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When commands are read from a tty, the interpreter is said to be in
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{\em interactive\ mode}. In this mode it prompts for the next command
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with the {\em primary\ prompt}, usually three greater-than signs ({\tt
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>>>}); for continuation lines it prompts with the {\em secondary\
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prompt}, by default three dots ({\tt ...}). Typing an EOF (Control-D)
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at the primary prompt causes the interpreter to exit with a zero exit
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status.
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The interpreter prints a welcome message stating its version number
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and a copyright notice before printing the first prompt, e.g.:
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\bcode\begin{verbatim}
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python
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Python 1.0.3 (Jul 14 1994)
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Copyright 1991-1994 Stichting Mathematisch Centrum, Amsterdam
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>>>
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\end{verbatim}\ecode
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\section{The Interpreter and its Environment}
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\subsection{Error Handling}
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When an error occurs, the interpreter prints an error
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message and a stack trace. In interactive mode, it then returns to
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the primary prompt; when input came from a file, it exits with a
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nonzero exit status after printing
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the stack trace. (Exceptions handled by an {\tt except} clause in a
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{\tt try} statement are not errors in this context.) Some errors are
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unconditionally fatal and cause an exit with a nonzero exit; this
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applies to internal inconsistencies and some cases of running out of
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memory. All error messages are written to the standard error stream;
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normal output from the executed commands is written to standard
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output.
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Typing the interrupt character (usually Control-C or DEL) to the
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primary or secondary prompt cancels the input and returns to the
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primary prompt.%
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\footnote{
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A problem with the GNU Readline package may prevent this.
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}
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Typing an interrupt while a command is executing raises the {\tt
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KeyboardInterrupt} exception, which may be handled by a {\tt try}
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statement.
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\subsection{The Module Search Path}
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When a module named {\tt foo} is imported, the interpreter searches
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for a file named {\tt foo.py} in the list of directories specified by
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the environment variable {\tt PYTHONPATH}. It has the same syntax as
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the {\UNIX} shell variable {\tt PATH}, i.e., a list of colon-separated
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directory names. When {\tt PYTHONPATH} is not set, or when the file
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is not found there, the search continues in an installation-dependent
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default path, usually {\tt .:/usr/local/lib/python}.
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Actually, modules are searched in the list of directories given by the
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variable {\tt sys.path} which is initialized from {\tt PYTHONPATH} and
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the installation-dependent default. This allows Python programs that
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know what they're doing to modify or replace the module search path.
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See the section on Standard Modules later.
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\subsection{``Compiled'' Python files}
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As an important speed-up of the start-up time for short programs that
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use a lot of standard modules, if a file called {\tt foo.pyc} exists
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in the directory where {\tt foo.py} is found, this is assumed to
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contain an already-``compiled'' version of the module {\tt foo}. The
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modification time of the version of {\tt foo.py} used to create {\tt
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foo.pyc} is recorded in {\tt foo.pyc}, and the file is ignored if
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these don't match.
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Whenever {\tt foo.py} is successfully compiled, an attempt is made to
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write the compiled version to {\tt foo.pyc}. It is not an error if
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this attempt fails; if for any reason the file is not written
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completely, the resulting {\tt foo.pyc} file will be recognized as
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invalid and thus ignored later.
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\subsection{Executable Python scripts}
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On BSD'ish {\UNIX} systems, Python scripts can be made directly
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executable, like shell scripts, by putting the line
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\bcode\begin{verbatim}
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#! /usr/local/bin/python
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\end{verbatim}\ecode
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%
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(assuming that's the name of the interpreter) at the beginning of the
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script and giving the file an executable mode. The {\tt \#!} must be
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the first two characters of the file.
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\subsection{The Interactive Startup File}
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When you use Python interactively, it is frequently handy to have some
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standard commands executed every time the interpreter is started. You
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can do this by setting an environment variable named {\tt
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PYTHONSTARTUP} to the name of a file containing your start-up
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commands. This is similar to the {\tt .profile} feature of the UNIX
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shells.
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This file is only read in interactive sessions, not when Python reads
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commands from a script, and not when {\tt /dev/tty} is given as the
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explicit source of commands (which otherwise behaves like an
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interactive session). It is executed in the same name space where
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interactive commands are executed, so that objects that it defines or
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imports can be used without qualification in the interactive session.
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You can also change the prompts {\tt sys.ps1} and {\tt sys.ps2} in
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this file.
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If you want to read an additional start-up file from the current
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directory, you can program this in the global start-up file, e.g.
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\verb\execfile('.pythonrc')\. If you want to use the startup file
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in a script, you must write this explicitly in the script, e.g.
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\verb\import os;\ \verb\execfile(os.environ['PYTHONSTARTUP'])\.
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\section{Interactive Input Editing and History Substitution}
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Some versions of the Python interpreter support editing of the current
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input line and history substitution, similar to facilities found in
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the Korn shell and the GNU Bash shell. This is implemented using the
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{\em GNU\ Readline} library, which supports Emacs-style and vi-style
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editing. This library has its own documentation which I won't
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duplicate here; however, the basics are easily explained.
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Perhaps the quickest check to see whether command line editing is
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supported is typing Control-P to the first Python prompt you get. If
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it beeps, you have command line editing. If nothing appears to
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happen, or if \verb/^P/ is echoed, you can skip the rest of this
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section.
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\subsection{Line Editing}
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If supported, input line editing is active whenever the interpreter
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prints a primary or secondary prompt. The current line can be edited
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using the conventional Emacs control characters. The most important
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of these are: C-A (Control-A) moves the cursor to the beginning of the
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line, C-E to the end, C-B moves it one position to the left, C-F to
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the right. Backspace erases the character to the left of the cursor,
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C-D the character to its right. C-K kills (erases) the rest of the
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line to the right of the cursor, C-Y yanks back the last killed
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string. C-underscore undoes the last change you made; it can be
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repeated for cumulative effect.
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\subsection{History Substitution}
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History substitution works as follows. All non-empty input lines
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issued are saved in a history buffer, and when a new prompt is given
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you are positioned on a new line at the bottom of this buffer. C-P
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moves one line up (back) in the history buffer, C-N moves one down.
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Any line in the history buffer can be edited; an asterisk appears in
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front of the prompt to mark a line as modified. Pressing the Return
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key passes the current line to the interpreter. C-R starts an
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incremental reverse search; C-S starts a forward search.
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\subsection{Key Bindings}
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The key bindings and some other parameters of the Readline library can
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be customized by placing commands in an initialization file called
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{\tt \$HOME/.inputrc}. Key bindings have the form
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\bcode\begin{verbatim}
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key-name: function-name
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\end{verbatim}\ecode
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%
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or
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\bcode\begin{verbatim}
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"string": function-name
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\end{verbatim}\ecode
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%
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and options can be set with
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\bcode\begin{verbatim}
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set option-name value
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\end{verbatim}\ecode
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%
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For example:
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\bcode\begin{verbatim}
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# I prefer vi-style editing:
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set editing-mode vi
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# Edit using a single line:
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set horizontal-scroll-mode On
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# Rebind some keys:
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Meta-h: backward-kill-word
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"\C-u": universal-argument
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"\C-x\C-r": re-read-init-file
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\end{verbatim}\ecode
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%
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Note that the default binding for TAB in Python is to insert a TAB
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instead of Readline's default filename completion function. If you
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insist, you can override this by putting
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\bcode\begin{verbatim}
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TAB: complete
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\end{verbatim}\ecode
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%
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in your {\tt \$HOME/.inputrc}. (Of course, this makes it hard to type
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indented continuation lines...)
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\subsection{Commentary}
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This facility is an enormous step forward compared to previous
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versions of the interpreter; however, some wishes are left: It would
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be nice if the proper indentation were suggested on continuation lines
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(the parser knows if an indent token is required next). The
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completion mechanism might use the interpreter's symbol table. A
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command to check (or even suggest) matching parentheses, quotes etc.
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would also be useful.
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\chapter{An Informal Introduction to Python}
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In the following examples, input and output are distinguished by the
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presence or absence of prompts ({\tt >>>} and {\tt ...}): to repeat
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the example, you must type everything after the prompt, when the
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prompt appears; lines that do not begin with a prompt are output from
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the interpreter.%
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\footnote{
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I'd prefer to use different fonts to distinguish input
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from output, but the amount of LaTeX hacking that would require
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is currently beyond my ability.
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}
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Note that a secondary prompt on a line by itself in an example means
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you must type a blank line; this is used to end a multi-line command.
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\section{Using Python as a Calculator}
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Let's try some simple Python commands. Start the interpreter and wait
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for the primary prompt, {\tt >>>}. (It shouldn't take long.)
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\subsection{Numbers}
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The interpreter acts as a simple calculator: you can type an
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expression at it and it will write the value. Expression syntax is
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straightforward: the operators {\tt +}, {\tt -}, {\tt *} and {\tt /}
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work just like in most other languages (e.g., Pascal or C); parentheses
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can be used for grouping. For example:
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\bcode\begin{verbatim}
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>>> 2+2
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4
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>>> # This is a comment
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... 2+2
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4
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>>> 2+2 # and a comment on the same line as code
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4
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>>> (50-5*6)/4
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5
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>>> # Integer division returns the floor:
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... 7/3
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2
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>>> 7/-3
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-3
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>>>
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\end{verbatim}\ecode
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%
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Like in C, the equal sign ({\tt =}) is used to assign a value to a
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variable. The value of an assignment is not written:
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\bcode\begin{verbatim}
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>>> width = 20
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>>> height = 5*9
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>>> width * height
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900
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>>>
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\end{verbatim}\ecode
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%
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A value can be assigned to several variables simultaneously:
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\bcode\begin{verbatim}
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>>> x = y = z = 0 # Zero x, y and z
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>>> x
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0
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>>> y
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0
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>>> z
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0
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>>>
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\end{verbatim}\ecode
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%
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There is full support for floating point; operators with mixed type
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operands convert the integer operand to floating point:
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\bcode\begin{verbatim}
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>>> 4 * 2.5 / 3.3
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3.0303030303
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>>> 7.0 / 2
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3.5
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>>>
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\end{verbatim}\ecode
|
|
|
|
\subsection{Strings}
|
|
|
|
Besides numbers, Python can also manipulate strings, enclosed in
|
|
single quotes or double quotes:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 'foo bar'
|
|
'foo bar'
|
|
>>> '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.'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Strings are written 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 {\tt print} statement, described later,
|
|
can be used to write strings without quotes or escapes.)
|
|
|
|
Strings can be concatenated (glued together) with the {\tt +}
|
|
operator, and repeated with {\tt *}:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word = 'Help' + 'A'
|
|
>>> word
|
|
'HelpA'
|
|
>>> '<' + word*5 + '>'
|
|
'<HelpAHelpAHelpAHelpAHelpA>'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
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 {\em
|
|
slice} notation: two indices separated by a colon.
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[4]
|
|
'A'
|
|
>>> word[0:2]
|
|
'He'
|
|
>>> word[2:4]
|
|
'lp'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
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.
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[:2] # The first two characters
|
|
'He'
|
|
>>> word[2:] # All but the first two characters
|
|
'lpA'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Here's a useful invariant of slice operations: \verb\s[:i] + s[i:]\
|
|
equals \verb\s\.
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[:2] + word[2:]
|
|
'HelpA'
|
|
>>> word[:3] + word[3:]
|
|
'HelpA'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
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.
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[1:100]
|
|
'elpA'
|
|
>>> word[10:]
|
|
''
|
|
>>> word[2:1]
|
|
''
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Indices may be negative numbers, to start counting from the right.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
But note that -0 is really the same as 0, so it does not count from
|
|
the right!
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[-0] # (since -0 equals 0)
|
|
'H'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Out-of-range negative slice indices are truncated, but don't try this
|
|
for single-element (non-slice) indices:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> word[-100:]
|
|
'HelpA'
|
|
>>> word[-10] # error
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
IndexError: string index out of range
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The best way to remember how slices work is to think of the indices as
|
|
pointing {\em between} characters, with the left edge of the first
|
|
character numbered 0. Then the right edge of the last character of a
|
|
string of {\tt n} characters has index {\tt n}, for example:
|
|
|
|
\bcode\begin{verbatim}
|
|
+---+---+---+---+---+
|
|
| H | e | l | p | A |
|
|
+---+---+---+---+---+
|
|
0 1 2 3 4 5
|
|
-5 -4 -3 -2 -1
|
|
\end{verbatim}\ecode
|
|
%
|
|
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 \verb\i\ to \verb\j\ consists of all characters between
|
|
the edges labeled \verb\i\ and \verb\j\, respectively.
|
|
|
|
For nonnegative indices, the length of a slice is the difference of
|
|
the indices, if both are within bounds, e.g., the length of
|
|
\verb\word[1:3]\ is 2.
|
|
|
|
The built-in function {\tt len()} returns the length of a string:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> s = 'supercalifragilisticexpialidocious'
|
|
>>> len(s)
|
|
34
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsection{Lists}
|
|
|
|
Python knows a number of {\em compound} data types, used to group
|
|
together other values. The most versatile is the {\em 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.
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a = ['foo', 'bar', 100, 1234]
|
|
>>> a
|
|
['foo', 'bar', 100, 1234]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Like string indices, list indices start at 0, and lists can be sliced,
|
|
concatenated and so on:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a[0]
|
|
'foo'
|
|
>>> a[3]
|
|
1234
|
|
>>> a[-2]
|
|
100
|
|
>>> a[1:-1]
|
|
['bar', 100]
|
|
>>> a[:2] + ['bletch', 2*2]
|
|
['foo', 'bar', 'bletch', 4]
|
|
>>> 3*a[:3] + ['Boe!']
|
|
['foo', 'bar', 100, 'foo', 'bar', 100, 'foo', 'bar', 100, 'Boe!']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Unlike strings, which are {\em immutable}, it is possible to change
|
|
individual elements of a list:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a
|
|
['foo', 'bar', 100, 1234]
|
|
>>> a[2] = a[2] + 23
|
|
>>> a
|
|
['foo', 'bar', 123, 1234]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Assignment to slices is also possible, and this can even change the size
|
|
of the list:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> # 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]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The built-in function {\tt len()} also applies to lists:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> len(a)
|
|
8
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
It is possible to nest lists (create lists containing other lists),
|
|
for example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Note that in the last example, {\tt p[1]} and {\tt q} really refer to
|
|
the same object! We'll come back to {\em object semantics} later.
|
|
|
|
\section{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
|
|
subsequence of the {\em Fibonacci} series as follows:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> # 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
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This example introduces several new features.
|
|
|
|
\begin{itemize}
|
|
|
|
\item
|
|
The first line contains a {\em multiple assignment}: the variables
|
|
{\tt a} and {\tt 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.
|
|
|
|
\item
|
|
The {\tt while} loop executes as long as the condition (here: {\tt b <
|
|
100}) 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: {\tt <}, {\tt >}, {\tt ==}, {\tt <=}, {\tt >=} and {\tt !=}.
|
|
|
|
\item
|
|
The {\em body} of the loop is {\em 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).
|
|
|
|
\item
|
|
The {\tt 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 written without quotes,
|
|
and a space is inserted between items, so you can format things nicely,
|
|
like this:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> i = 256*256
|
|
>>> print 'The value of i is', i
|
|
The value of i is 65536
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
A trailing comma avoids the newline after the output:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Note that the interpreter inserts a newline before it prints the next
|
|
prompt if the last line was not completed.
|
|
|
|
\end{itemize}
|
|
|
|
|
|
\chapter{More Control Flow Tools}
|
|
|
|
Besides the {\tt while} statement just introduced, Python knows the
|
|
usual control flow statements known from other languages, with some
|
|
twists.
|
|
|
|
\section{If Statements}
|
|
|
|
Perhaps the most well-known statement type is the {\tt if} statement.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> if x < 0:
|
|
... x = 0
|
|
... print 'Negative changed to zero'
|
|
... elif x == 0:
|
|
... print 'Zero'
|
|
... elif x == 1:
|
|
... print 'Single'
|
|
... else:
|
|
... print 'More'
|
|
...
|
|
\end{verbatim}\ecode
|
|
%
|
|
There can be zero or more {\tt elif} parts, and the {\tt else} part is
|
|
optional. The keyword `{\tt elif}' is short for `{\tt else if}', and is
|
|
useful to avoid excessive indentation. An {\tt if...elif...elif...}
|
|
sequence is a substitute for the {\em switch} or {\em case} statements
|
|
found in other languages.
|
|
|
|
\section{For Statements}
|
|
|
|
The {\tt 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 leaving the user
|
|
completely free in the iteration test and step (as C), Python's {\tt
|
|
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):
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> # Measure some strings:
|
|
... a = ['cat', 'window', 'defenestrate']
|
|
>>> for x in a:
|
|
... print x, len(x)
|
|
...
|
|
cat 3
|
|
window 6
|
|
defenestrate 12
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
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:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{The {\tt range()} Function}
|
|
|
|
If you do need to iterate over a sequence of numbers, the built-in
|
|
function {\tt range()} comes in handy. It generates lists containing
|
|
arithmetic progressions, e.g.:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> range(10)
|
|
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The given end point is never part of the generated list; {\tt 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):
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> range(5, 10)
|
|
[5, 6, 7, 8, 9]
|
|
>>> range(0, 10, 3)
|
|
[0, 3, 6, 9]
|
|
>>> range(-10, -100, -30)
|
|
[-10, -40, -70]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
To iterate over the indices of a sequence, combine {\tt range()} and
|
|
{\tt len()} as follows:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{Break and Continue Statements, and Else Clauses on Loops}
|
|
|
|
The {\tt break} statement, like in C, breaks out of the smallest
|
|
enclosing {\tt for} or {\tt while} loop.
|
|
|
|
The {\tt continue} statement, also borrowed from C, continues with the
|
|
next iteration of the loop.
|
|
|
|
Loop statements may have an {\tt else} clause; it is executed when the
|
|
loop terminates through exhaustion of the list (with {\tt for}) or when
|
|
the condition becomes false (with {\tt while}), but not when the loop is
|
|
terminated by a {\tt break} statement. This is exemplified by the
|
|
following loop, which searches for a list item of value 0:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> 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
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{Pass Statements}
|
|
|
|
The {\tt pass} statement does nothing.
|
|
It can be used when a statement is required syntactically but the
|
|
program requires no action.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> while 1:
|
|
... pass # Busy-wait for keyboard interrupt
|
|
...
|
|
\end{verbatim}\ecode
|
|
|
|
\section{Defining Functions}
|
|
|
|
We can create a function that writes the Fibonacci series to an
|
|
arbitrary boundary:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> def fib(n): # write Fibonacci series up to n
|
|
... a, b = 0, 1
|
|
... while b <= n:
|
|
... print b,
|
|
... a, b = b, a+b
|
|
...
|
|
>>> # Now call the function we just defined:
|
|
... fib(2000)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The keyword {\tt def} introduces a function {\em definition}. It must
|
|
be followed by the function name and the parenthesized list of formal
|
|
parameters. The statements that form the body of the function starts at
|
|
the next line, indented by a tab stop.
|
|
|
|
The {\em execution} of a function introduces a new symbol table used
|
|
for the local variables of the function. More precisely, all variable
|
|
assignments in a function store the value in the local symbol table;
|
|
whereas
|
|
variable references first look in the local symbol table, then
|
|
in the global symbol table, and then in the table of built-in names.
|
|
Thus,
|
|
global variables cannot be directly assigned to from within a
|
|
function (unless named in a {\tt global} statement), although
|
|
they may be referenced.
|
|
|
|
The actual parameters (arguments) to a function call are introduced in
|
|
the local symbol table of the called function when it is called; thus,
|
|
arguments are passed using {\em call\ by\ value}.%
|
|
\footnote{
|
|
Actually, {\em call by object reference} would be a better
|
|
description, since if a mutable object is passed, the caller
|
|
will see any changes the callee makes to it (e.g., items
|
|
inserted into a list).
|
|
}
|
|
When a function calls another function, a new local symbol table is
|
|
created for that call.
|
|
|
|
A function definition introduces the function name in the
|
|
current
|
|
symbol table. The value
|
|
of the function name
|
|
has a type that is recognized by the interpreter as a user-defined
|
|
function. This value can be assigned to another name which can then
|
|
also be used as a function. This serves as a general renaming
|
|
mechanism:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> fib
|
|
<function object at 10042ed0>
|
|
>>> f = fib
|
|
>>> f(100)
|
|
1 1 2 3 5 8 13 21 34 55 89
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
You might object that {\tt fib} is not a function but a procedure. In
|
|
Python, like in C, procedures are just functions that don't return a
|
|
value. In fact, technically speaking, procedures do return a value,
|
|
albeit a rather boring one. This value is called {\tt None} (it's a
|
|
built-in name). Writing the value {\tt None} is normally suppressed by
|
|
the interpreter if it would be the only value written. You can see it
|
|
if you really want to:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> print fib(0)
|
|
None
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
It is simple to write a function that returns a list of the numbers of
|
|
the Fibonacci series, instead of printing it:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> def fib2(n): # return Fibonacci series up to n
|
|
... result = []
|
|
... a, b = 0, 1
|
|
... while b <= n:
|
|
... result.append(b) # see below
|
|
... a, b = b, a+b
|
|
... return result
|
|
...
|
|
>>> f100 = fib2(100) # call it
|
|
>>> f100 # write the result
|
|
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This example, as usual, demonstrates some new Python features:
|
|
|
|
\begin{itemize}
|
|
|
|
\item
|
|
The {\tt return} statement returns with a value from a function. {\tt
|
|
return} without an expression argument is used to return from the middle
|
|
of a procedure (falling off the end also returns from a procedure), in
|
|
which case the {\tt None} value is returned.
|
|
|
|
\item
|
|
The statement {\tt result.append(b)} calls a {\em method} of the list
|
|
object {\tt result}. A method is a function that `belongs' to an
|
|
object and is named {\tt obj.methodname}, where {\tt obj} is some
|
|
object (this may be an expression), and {\tt methodname} is the name
|
|
of a method that is defined by the object's type. Different types
|
|
define different methods. Methods of different types may have the
|
|
same name without causing ambiguity. (It is possible to define your
|
|
own object types and methods, using {\em classes}, as discussed later
|
|
in this tutorial.)
|
|
The method {\tt append} shown in the example, is defined for
|
|
list objects; it adds a new element at the end of the list. In this
|
|
example
|
|
it is equivalent to {\tt result = result + [b]}, but more efficient.
|
|
|
|
\end{itemize}
|
|
|
|
|
|
\chapter{Odds and Ends}
|
|
|
|
This chapter describes some things you've learned about already in
|
|
more detail, and adds some new things as well.
|
|
|
|
\section{More on Lists}
|
|
|
|
The list data type has some more methods. Here are all of the methods
|
|
of lists objects:
|
|
|
|
\begin{description}
|
|
|
|
\item[{\tt insert(i, x)}]
|
|
Insert an item at a given position. The first argument is the index of
|
|
the element before which to insert, so {\tt a.insert(0, x)} inserts at
|
|
the front of the list, and {\tt a.insert(len(a), x)} is equivalent to
|
|
{\tt a.append(x)}.
|
|
|
|
\item[{\tt append(x)}]
|
|
Equivalent to {\tt a.insert(len(a), x)}.
|
|
|
|
\item[{\tt index(x)}]
|
|
Return the index in the list of the first item whose value is {\tt x}.
|
|
It is an error if there is no such item.
|
|
|
|
\item[{\tt remove(x)}]
|
|
Remove the first item from the list whose value is {\tt x}.
|
|
It is an error if there is no such item.
|
|
|
|
\item[{\tt sort()}]
|
|
Sort the items of the list, in place.
|
|
|
|
\item[{\tt reverse()}]
|
|
Reverse the elements of the list, in place.
|
|
|
|
\item[{\tt count(x)}]
|
|
Return the number of times {\tt x} appears in the list.
|
|
|
|
\end{description}
|
|
|
|
An example that uses all list methods:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a = [66.6, 333, 333, 1, 1234.5]
|
|
>>> print a.count(333), a.count(66.6), a.count('x')
|
|
2 1 0
|
|
>>> a.insert(2, -1)
|
|
>>> a.append(333)
|
|
>>> a
|
|
[66.6, 333, -1, 333, 1, 1234.5, 333]
|
|
>>> a.index(333)
|
|
1
|
|
>>> a.remove(333)
|
|
>>> a
|
|
[66.6, -1, 333, 1, 1234.5, 333]
|
|
>>> a.reverse()
|
|
>>> a
|
|
[333, 1234.5, 1, 333, -1, 66.6]
|
|
>>> a.sort()
|
|
>>> a
|
|
[-1, 1, 66.6, 333, 333, 1234.5]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{The {\tt del} statement}
|
|
|
|
There is a way to remove an item from a list given its index instead
|
|
of its value: the {\tt del} statement. This can also be used to
|
|
remove slices from a list (which we did earlier by assignment of an
|
|
empty list to the slice). For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a
|
|
[-1, 1, 66.6, 333, 333, 1234.5]
|
|
>>> del a[0]
|
|
>>> a
|
|
[1, 66.6, 333, 333, 1234.5]
|
|
>>> del a[2:4]
|
|
>>> a
|
|
[1, 66.6, 1234.5]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
{\tt del} can also be used to delete entire variables:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> del a
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Referencing the name {\tt a} hereafter is an error (at least until
|
|
another value is assigned to it). We'll find other uses for {\tt del}
|
|
later.
|
|
|
|
\section{Tuples and Sequences}
|
|
|
|
We saw that lists and strings have many common properties, e.g.,
|
|
indexing and slicing operations. They are two examples of {\em
|
|
sequence} data types. Since Python is an evolving language, other
|
|
sequence data types may be added. There is also another standard
|
|
sequence data type: the {\em tuple}.
|
|
|
|
A tuple consists of a number of values separated by commas, for
|
|
instance:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> t = 12345, 54321, 'hello!'
|
|
>>> t[0]
|
|
12345
|
|
>>> t
|
|
(12345, 54321, 'hello!')
|
|
>>> # Tuples may be nested:
|
|
... u = t, (1, 2, 3, 4, 5)
|
|
>>> u
|
|
((12345, 54321, 'hello!'), (1, 2, 3, 4, 5))
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
As you see, on output tuples are alway enclosed in parentheses, so
|
|
that nested tuples are interpreted correctly; they may be input with
|
|
or without surrounding parentheses, although often parentheses are
|
|
necessary anyway (if the tuple is part of a larger expression).
|
|
|
|
Tuples have many uses, e.g., (x, y) coordinate pairs, employee records
|
|
from a database, etc. Tuples, like strings, are immutable: it is not
|
|
possible to assign to the individual items of a tuple (you can
|
|
simulate much of the same effect with slicing and concatenation,
|
|
though).
|
|
|
|
A special problem is the construction of tuples containing 0 or 1
|
|
items: the syntax has some extra quirks to accommodate these. Empty
|
|
tuples are constructed by an empty pair of parentheses; a tuple with
|
|
one item is constructed by following a value with a comma
|
|
(it is not sufficient to enclose a single value in parentheses).
|
|
Ugly, but effective. For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> empty = ()
|
|
>>> singleton = 'hello', # <-- note trailing comma
|
|
>>> len(empty)
|
|
0
|
|
>>> len(singleton)
|
|
1
|
|
>>> singleton
|
|
('hello',)
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The statement {\tt t = 12345, 54321, 'hello!'} is an example of {\em
|
|
tuple packing}: the values {\tt 12345}, {\tt 54321} and {\tt 'hello!'}
|
|
are packed together in a tuple. The reverse operation is also
|
|
possible, e.g.:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> x, y, z = t
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This is called, appropriately enough, {\em tuple unpacking}. Tuple
|
|
unpacking requires that the list of variables on the left has the same
|
|
number of elements as the length of the tuple. Note that multiple
|
|
assignment is really just a combination of tuple packing and tuple
|
|
unpacking!
|
|
|
|
Occasionally, the corresponding operation on lists is useful: {\em list
|
|
unpacking}. This is supported by enclosing the list of variables in
|
|
square brackets:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a = ['foo', 'bar', 100, 1234]
|
|
>>> [a1, a2, a3, a4] = a
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{Dictionaries}
|
|
|
|
Another useful data type built into Python is the {\em dictionary}.
|
|
Dictionaries are sometimes found in other languages as ``associative
|
|
memories'' or ``associative arrays''. Unlike sequences, which are
|
|
indexed by a range of numbers, dictionaries are indexed by {\em keys},
|
|
which are strings (the use of non-string values as keys
|
|
is supported, but beyond the scope of this tutorial).
|
|
It is best to think of a dictionary as an unordered set of
|
|
{\em key:value} pairs, with the requirement that the keys are unique
|
|
(within one dictionary).
|
|
A pair of braces creates an empty dictionary: \verb/{}/.
|
|
Placing a comma-separated list of key:value pairs within the
|
|
braces adds initial key:value pairs to the dictionary; this is also the
|
|
way dictionaries are written on output.
|
|
|
|
The main operations on a dictionary are storing a value with some key
|
|
and extracting the value given the key. It is also possible to delete
|
|
a key:value pair
|
|
with {\tt del}.
|
|
If you store using a key that is already in use, the old value
|
|
associated with that key is forgotten. It is an error to extract a
|
|
value using a non-existent key.
|
|
|
|
The {\tt keys()} method of a dictionary object returns a list of all the
|
|
keys used in the dictionary, in random order (if you want it sorted,
|
|
just apply the {\tt sort()} method to the list of keys). To check
|
|
whether a single key is in the dictionary, use the \verb/has_key()/
|
|
method of the dictionary.
|
|
|
|
Here is a small example using a dictionary:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> tel = {'jack': 4098, 'sape': 4139}
|
|
>>> tel['guido'] = 4127
|
|
>>> tel
|
|
{'sape': 4139, 'guido': 4127, 'jack': 4098}
|
|
>>> tel['jack']
|
|
4098
|
|
>>> del tel['sape']
|
|
>>> tel['irv'] = 4127
|
|
>>> tel
|
|
{'guido': 4127, 'irv': 4127, 'jack': 4098}
|
|
>>> tel.keys()
|
|
['guido', 'irv', 'jack']
|
|
>>> tel.has_key('guido')
|
|
1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{More on Conditions}
|
|
|
|
The conditions used in {\tt while} and {\tt if} statements above can
|
|
contain other operators besides comparisons.
|
|
|
|
The comparison operators {\tt in} and {\tt not in} check whether a value
|
|
occurs (does not occur) in a sequence. The operators {\tt is} and {\tt
|
|
is not} compare whether two objects are really the same object; this
|
|
only matters for mutable objects like lists. All comparison operators
|
|
have the same priority, which is lower than that of all numerical
|
|
operators.
|
|
|
|
Comparisons can be chained: e.g., {\tt a < b = c} tests whether {\tt a}
|
|
is less than {\tt b} and moreover {\tt b} equals {\tt c}.
|
|
|
|
Comparisons may be combined by the Boolean operators {\tt and} and {\tt
|
|
or}, and the outcome of a comparison (or of any other Boolean
|
|
expression) may be negated with {\tt not}. These all have lower
|
|
priorities than comparison operators again; between them, {\tt not} has
|
|
the highest priority, and {\tt or} the lowest, so that
|
|
{\tt A and not B or C} is equivalent to {\tt (A and (not B)) or C}. Of
|
|
course, parentheses can be used to express the desired composition.
|
|
|
|
The Boolean operators {\tt and} and {\tt or} are so-called {\em
|
|
shortcut} operators: their arguments are evaluated from left to right,
|
|
and evaluation stops as soon as the outcome is determined. E.g., if
|
|
{\tt A} and {\tt C} are true but {\tt B} is false, {\tt A and B and C}
|
|
does not evaluate the expression C. In general, the return value of a
|
|
shortcut operator, when used as a general value and not as a Boolean, is
|
|
the last evaluated argument.
|
|
|
|
It is possible to assign the result of a comparison or other Boolean
|
|
expression to a variable. For example,
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
|
|
>>> non_null = string1 or string2 or string3
|
|
>>> non_null
|
|
'Trondheim'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Note that in Python, unlike C, assignment cannot occur inside expressions.
|
|
|
|
\section{Comparing Sequences and Other Types}
|
|
|
|
Sequence objects may be compared to other objects with the same
|
|
sequence type. The comparison uses {\em lexicographical} ordering:
|
|
first the first two items are compared, and if they differ this
|
|
determines the outcome of the comparison; if they are equal, the next
|
|
two items are compared, and so on, until either sequence is exhausted.
|
|
If two items to be compared are themselves sequences of the same type,
|
|
the lexicographical comparison is carried out recursively. If all
|
|
items of two sequences compare equal, the sequences are considered
|
|
equal. If one sequence is an initial subsequence of the other, the
|
|
shorted sequence is the smaller one. Lexicographical ordering for
|
|
strings uses the ASCII ordering for individual characters. Some
|
|
examples of comparisons between sequences with the same types:
|
|
|
|
\bcode\begin{verbatim}
|
|
(1, 2, 3) < (1, 2, 4)
|
|
[1, 2, 3] < [1, 2, 4]
|
|
'ABC' < 'C' < 'Pascal' < 'Python'
|
|
(1, 2, 3, 4) < (1, 2, 4)
|
|
(1, 2) < (1, 2, -1)
|
|
(1, 2, 3) = (1.0, 2.0, 3.0)
|
|
(1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4)
|
|
\end{verbatim}\ecode
|
|
%
|
|
Note that comparing objects of different types is legal. The outcome
|
|
is deterministic but arbitrary: the types are ordered by their name.
|
|
Thus, a list is always smaller than a string, a string is always
|
|
smaller than a tuple, etc. Mixed numeric types are compared according
|
|
to their numeric value, so 0 equals 0.0, etc.%
|
|
\footnote{
|
|
The rules for comparing objects of different types should
|
|
not be relied upon; they may change in a future version of
|
|
the language.
|
|
}
|
|
|
|
|
|
\chapter{Modules}
|
|
|
|
If you quit from the Python interpreter and enter it again, the
|
|
definitions you have made (functions and variables) are lost.
|
|
Therefore, if you want to write a somewhat longer program, you are
|
|
better off using a text editor to prepare the input for the interpreter
|
|
and run it with that file as input instead. This is known as creating a
|
|
{\em script}. As your program gets longer, you may want to split it
|
|
into several files for easier maintenance. You may also want to use a
|
|
handy function that you've written in several programs without copying
|
|
its definition into each program.
|
|
|
|
To support this, Python has a way to put definitions in a file and use
|
|
them in a script or in an interactive instance of the interpreter.
|
|
Such a file is called a {\em module}; definitions from a module can be
|
|
{\em imported} into other modules or into the {\em main} module (the
|
|
collection of variables that you have access to in a script
|
|
executed at the top level
|
|
and in calculator mode).
|
|
|
|
A module is a file containing Python definitions and statements. The
|
|
file name is the module name with the suffix {\tt .py} appended. Within
|
|
a module, the module's name (as a string) is available as the value of
|
|
the global variable {\tt __name__}. For instance, use your favorite text
|
|
editor to create a file called {\tt fibo.py} in the current directory
|
|
with the following contents:
|
|
|
|
\bcode\begin{verbatim}
|
|
# Fibonacci numbers module
|
|
|
|
def fib(n): # write Fibonacci series up to n
|
|
a, b = 0, 1
|
|
while b <= n:
|
|
print b,
|
|
a, b = b, a+b
|
|
|
|
def fib2(n): # return Fibonacci series up to n
|
|
result = []
|
|
a, b = 0, 1
|
|
while b <= n:
|
|
result.append(b)
|
|
a, b = b, a+b
|
|
return result
|
|
\end{verbatim}\ecode
|
|
%
|
|
Now enter the Python interpreter and import this module with the
|
|
following command:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import fibo
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This does not enter the names of the functions defined in
|
|
{\tt fibo}
|
|
directly in the current symbol table; it only enters the module name
|
|
{\tt fibo}
|
|
there.
|
|
Using the module name you can access the functions:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> fibo.fib(1000)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
>>> fibo.fib2(100)
|
|
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
|
|
>>> fibo.__name__
|
|
'fibo'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
If you intend to use a function often you can assign it to a local name:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> fib = fibo.fib
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{More on Modules}
|
|
|
|
A module can contain executable statements as well as function
|
|
definitions.
|
|
These statements are intended to initialize the module.
|
|
They are executed only the
|
|
{\em first}
|
|
time the module is imported somewhere.%
|
|
\footnote{
|
|
In fact function definitions are also `statements' that are
|
|
`executed'; the execution enters the function name in the
|
|
module's global symbol table.
|
|
}
|
|
|
|
Each module has its own private symbol table, which is used as the
|
|
global symbol table by all functions defined in the module.
|
|
Thus, the author of a module can use global variables in the module
|
|
without worrying about accidental clashes with a user's global
|
|
variables.
|
|
On the other hand, if you know what you are doing you can touch a
|
|
module's global variables with the same notation used to refer to its
|
|
functions,
|
|
{\tt modname.itemname}.
|
|
|
|
Modules can import other modules.
|
|
It is customary but not required to place all
|
|
{\tt import}
|
|
statements at the beginning of a module (or script, for that matter).
|
|
The imported module names are placed in the importing module's global
|
|
symbol table.
|
|
|
|
There is a variant of the
|
|
{\tt import}
|
|
statement that imports names from a module directly into the importing
|
|
module's symbol table.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> from fibo import fib, fib2
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This does not introduce the module name from which the imports are taken
|
|
in the local symbol table (so in the example, {\tt fibo} is not
|
|
defined).
|
|
|
|
There is even a variant to import all names that a module defines:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> from fibo import *
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
This imports all names except those beginning with an underscore
|
|
({\tt _}).
|
|
|
|
\section{Standard Modules}
|
|
|
|
Python comes with a library of standard modules, described in a separate
|
|
document (Python Library Reference). Some modules are built into the
|
|
interpreter; these provide access to operations that are not part of the
|
|
core of the language but are nevertheless built in, either for
|
|
efficiency or to provide access to operating system primitives such as
|
|
system calls. The set of such modules is a configuration option; e.g.,
|
|
the {\tt amoeba} module is only provided on systems that somehow support
|
|
Amoeba primitives. One particular module deserves some attention: {\tt
|
|
sys}, which is built into every Python interpreter. The variables {\tt
|
|
sys.ps1} and {\tt sys.ps2} define the strings used as primary and
|
|
secondary prompts:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.ps1
|
|
'>>> '
|
|
>>> sys.ps2
|
|
'... '
|
|
>>> sys.ps1 = 'C> '
|
|
C> print 'Yuck!'
|
|
Yuck!
|
|
C>
|
|
\end{verbatim}\ecode
|
|
%
|
|
These two variables are only defined if the interpreter is in
|
|
interactive mode.
|
|
|
|
The variable
|
|
{\tt sys.path}
|
|
is a list of strings that determine the interpreter's search path for
|
|
modules.
|
|
It is initialized to a default path taken from the environment variable
|
|
{\tt PYTHONPATH},
|
|
or from a built-in default if
|
|
{\tt PYTHONPATH}
|
|
is not set.
|
|
You can modify it using standard list operations, e.g.:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.path.append('/ufs/guido/lib/python')
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{The {\tt dir()} function}
|
|
|
|
The built-in function {\tt dir} is used to find out which names a module
|
|
defines. It returns a sorted list of strings:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import fibo, sys
|
|
>>> dir(fibo)
|
|
['__name__', 'fib', 'fib2']
|
|
>>> dir(sys)
|
|
['__name__', 'argv', 'builtin_module_names', 'copyright', 'exit',
|
|
'maxint', 'modules', 'path', 'ps1', 'ps2', 'setprofile', 'settrace',
|
|
'stderr', 'stdin', 'stdout', 'version']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Without arguments, {\tt dir()} lists the names you have defined currently:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> a = [1, 2, 3, 4, 5]
|
|
>>> import fibo, sys
|
|
>>> fib = fibo.fib
|
|
>>> dir()
|
|
['__name__', 'a', 'fib', 'fibo', 'sys']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Note that it lists all types of names: variables, modules, functions, etc.
|
|
|
|
{\tt dir()} does not list the names of built-in functions and variables.
|
|
If you want a list of those, they are defined in the standard module
|
|
{\tt __builtin__}:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import __builtin__
|
|
>>> dir(__builtin__)
|
|
['AccessError', 'AttributeError', 'ConflictError', 'EOFError', 'IOError',
|
|
'ImportError', 'IndexError', 'KeyError', 'KeyboardInterrupt',
|
|
'MemoryError', 'NameError', 'None', 'OverflowError', 'RuntimeError',
|
|
'SyntaxError', 'SystemError', 'SystemExit', 'TypeError', 'ValueError',
|
|
'ZeroDivisionError', '__name__', 'abs', 'apply', 'chr', 'cmp', 'coerce',
|
|
'compile', 'dir', 'divmod', 'eval', 'execfile', 'filter', 'float',
|
|
'getattr', 'hasattr', 'hash', 'hex', 'id', 'input', 'int', 'len', 'long',
|
|
'map', 'max', 'min', 'oct', 'open', 'ord', 'pow', 'range', 'raw_input',
|
|
'reduce', 'reload', 'repr', 'round', 'setattr', 'str', 'type', 'xrange']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
|
|
\chapter{Output Formatting}
|
|
|
|
So far we've encountered two ways of writing values: {\em expression
|
|
statements} and the {\tt print} statement. (A third way is using the
|
|
{\tt write} method of file objects; the standard output file can be
|
|
referenced as {\tt sys.stdout}. See the Library Reference for more
|
|
information on this.)
|
|
|
|
Often you'll want more control over the formatting of your output than
|
|
simply printing space-separated values. The key to nice formatting in
|
|
Python is to do all the string handling yourself; using string slicing
|
|
and concatenation operations you can create any lay-out you can imagine.
|
|
The standard module {\tt string} contains some useful operations for
|
|
padding strings to a given column width; these will be discussed shortly.
|
|
Finally, the \code{\%} operator (modulo) with a string left argument
|
|
interprets this string as a C sprintf format string to be applied to the
|
|
right argument, and returns the string resulting from this formatting
|
|
operation.
|
|
|
|
One question remains, of course: how do you convert values to strings?
|
|
Luckily, Python has a way to convert any value to a string: just write
|
|
the value between reverse quotes (\verb/``/). Some examples:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> x = 10 * 3.14
|
|
>>> y = 200*200
|
|
>>> s = 'The value of x is ' + `x` + ', and y is ' + `y` + '...'
|
|
>>> print s
|
|
The value of x is 31.4, and y is 40000...
|
|
>>> # Reverse quotes work on other types besides numbers:
|
|
... p = [x, y]
|
|
>>> ps = `p`
|
|
>>> ps
|
|
'[31.4, 40000]'
|
|
>>> # Converting a string adds string quotes and backslashes:
|
|
... hello = 'hello, world\n'
|
|
>>> hellos = `hello`
|
|
>>> print hellos
|
|
'hello, world\012'
|
|
>>> # The argument of reverse quotes may be a tuple:
|
|
... `x, y, ('foo', 'bar')`
|
|
"(31.4, 40000, ('foo', 'bar'))"
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Here are two ways to write a table of squares and cubes:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> import string
|
|
>>> for x in range(1, 11):
|
|
... print string.rjust(`x`, 2), string.rjust(`x*x`, 3),
|
|
... # Note trailing comma on previous line
|
|
... print string.rjust(`x*x*x`, 4)
|
|
...
|
|
1 1 1
|
|
2 4 8
|
|
3 9 27
|
|
4 16 64
|
|
5 25 125
|
|
6 36 216
|
|
7 49 343
|
|
8 64 512
|
|
9 81 729
|
|
10 100 1000
|
|
>>> for x in range(1,11):
|
|
... print '%2d %3d %4d' % (x, x*x, x*x*x)
|
|
...
|
|
1 1 1
|
|
2 4 8
|
|
3 9 27
|
|
4 16 64
|
|
5 25 125
|
|
6 36 216
|
|
7 49 343
|
|
8 64 512
|
|
9 81 729
|
|
10 100 1000
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
(Note that one space between each column was added by the way {\tt print}
|
|
works: it always adds spaces between its arguments.)
|
|
|
|
This example demonstrates the function {\tt string.rjust()}, which
|
|
right-justifies a string in a field of a given width by padding it with
|
|
spaces on the left. There are similar functions {\tt string.ljust()}
|
|
and {\tt string.center()}. These functions do not write anything, they
|
|
just return a new string. If the input string is too long, they don't
|
|
truncate it, but return it unchanged; this will mess up your column
|
|
lay-out but that's usually better than the alternative, which would be
|
|
lying about a value. (If you really want truncation you can always add
|
|
a slice operation, as in {\tt string.ljust(x,~n)[0:n]}.)
|
|
|
|
There is another function, {\tt string.zfill}, which pads a numeric
|
|
string on the left with zeros. It understands about plus and minus
|
|
signs:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> string.zfill('12', 5)
|
|
'00012'
|
|
>>> string.zfill('-3.14', 7)
|
|
'-003.14'
|
|
>>> string.zfill('3.14159265359', 5)
|
|
'3.14159265359'
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
|
|
\chapter{Errors and Exceptions}
|
|
|
|
Until now error messages haven't been more than mentioned, but if you
|
|
have tried out the examples you have probably seen some. There are
|
|
(at least) two distinguishable kinds of errors: {\em syntax\ errors}
|
|
and {\em exceptions}.
|
|
|
|
\section{Syntax Errors}
|
|
|
|
Syntax errors, also known as parsing errors, are perhaps the most common
|
|
kind of complaint you get while you are still learning Python:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> while 1 print 'Hello world'
|
|
File "<stdin>", line 1
|
|
while 1 print 'Hello world'
|
|
^
|
|
SyntaxError: invalid syntax
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The parser repeats the offending line and displays a little `arrow'
|
|
pointing at the earliest point in the line where the error was detected.
|
|
The error is caused by (or at least detected at) the token
|
|
{\em preceding}
|
|
the arrow: in the example, the error is detected at the keyword
|
|
{\tt print}, since a colon ({\tt :}) is missing before it.
|
|
File name and line number are printed so you know where to look in case
|
|
the input came from a script.
|
|
|
|
\section{Exceptions}
|
|
|
|
Even if a statement or expression is syntactically correct, it may
|
|
cause an error when an attempt is made to execute it.
|
|
Errors detected during execution are called {\em exceptions} and are
|
|
not unconditionally fatal: you will soon learn how to handle them in
|
|
Python programs. Most exceptions are not handled by programs,
|
|
however, and result in error messages as shown here:
|
|
|
|
\bcode\small\begin{verbatim}
|
|
>>> 10 * (1/0)
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
ZeroDivisionError: integer division or modulo
|
|
>>> 4 + foo*3
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
NameError: foo
|
|
>>> '2' + 2
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
TypeError: illegal argument type for built-in operation
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The last line of the error message indicates what happened.
|
|
Exceptions come in different types, and the type is printed as part of
|
|
the message: the types in the example are
|
|
{\tt ZeroDivisionError},
|
|
{\tt NameError}
|
|
and
|
|
{\tt TypeError}.
|
|
The string printed as the exception type is the name of the built-in
|
|
name for the exception that occurred. This is true for all built-in
|
|
exceptions, but need not be true for user-defined exceptions (although
|
|
it is a useful convention).
|
|
Standard exception names are built-in identifiers (not reserved
|
|
keywords).
|
|
|
|
The rest of the line is a detail whose interpretation depends on the
|
|
exception type; its meaning is dependent on the exception type.
|
|
|
|
The preceding part of the error message shows the context where the
|
|
exception happened, in the form of a stack backtrace.
|
|
In general it contains a stack backtrace listing source lines; however,
|
|
it will not display lines read from standard input.
|
|
|
|
The Python library reference manual lists the built-in exceptions and
|
|
their meanings.
|
|
|
|
\section{Handling Exceptions}
|
|
|
|
It is possible to write programs that handle selected exceptions.
|
|
Look at the following example, which prints a table of inverses of
|
|
some floating point numbers:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> numbers = [0.3333, 2.5, 0, 10]
|
|
>>> for x in numbers:
|
|
... print x,
|
|
... try:
|
|
... print 1.0 / x
|
|
... except ZeroDivisionError:
|
|
... print '*** has no inverse ***'
|
|
...
|
|
0.3333 3.00030003
|
|
2.5 0.4
|
|
0 *** has no inverse ***
|
|
10 0.1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The {\tt try} statement works as follows.
|
|
\begin{itemize}
|
|
\item
|
|
First, the
|
|
{\em try\ clause}
|
|
(the statement(s) between the {\tt try} and {\tt except} keywords) is
|
|
executed.
|
|
\item
|
|
If no exception occurs, the
|
|
{\em except\ clause}
|
|
is skipped and execution of the {\tt try} statement is finished.
|
|
\item
|
|
If an exception occurs during execution of the try clause,
|
|
the rest of the clause is skipped. Then if
|
|
its type matches the exception named after the {\tt except} keyword,
|
|
the rest of the try clause is skipped, the except clause is executed,
|
|
and then execution continues after the {\tt try} statement.
|
|
\item
|
|
If an exception occurs which does not match the exception named in the
|
|
except clause, it is passed on to outer try statements; if no handler is
|
|
found, it is an
|
|
{\em unhandled\ exception}
|
|
and execution stops with a message as shown above.
|
|
\end{itemize}
|
|
A {\tt try} statement may have more than one except clause, to specify
|
|
handlers for different exceptions.
|
|
At most one handler will be executed.
|
|
Handlers only handle exceptions that occur in the corresponding try
|
|
clause, not in other handlers of the same {\tt try} statement.
|
|
An except clause may name multiple exceptions as a parenthesized list,
|
|
e.g.:
|
|
|
|
\bcode\begin{verbatim}
|
|
... except (RuntimeError, TypeError, NameError):
|
|
... pass
|
|
\end{verbatim}\ecode
|
|
%
|
|
The last except clause may omit the exception name(s), to serve as a
|
|
wildcard.
|
|
Use this with extreme caution, since it is easy to mask a real
|
|
programming error in this way!
|
|
|
|
When an exception occurs, it may have an associated value, also known as
|
|
the exceptions's
|
|
{\em argument}.
|
|
The presence and type of the argument depend on the exception type.
|
|
For exception types which have an argument, the except clause may
|
|
specify a variable after the exception name (or list) to receive the
|
|
argument's value, as follows:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> try:
|
|
... foo()
|
|
... except NameError, x:
|
|
... print 'name', x, 'undefined'
|
|
...
|
|
name foo undefined
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
If an exception has an argument, it is printed as the last part
|
|
(`detail') of the message for unhandled exceptions.
|
|
|
|
Exception handlers don't just handle exceptions if they occur
|
|
immediately in the try clause, but also if they occur inside functions
|
|
that are called (even indirectly) in the try clause.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> def this_fails():
|
|
... x = 1/0
|
|
...
|
|
>>> try:
|
|
... this_fails()
|
|
... except ZeroDivisionError, detail:
|
|
... print 'Handling run-time error:', detail
|
|
...
|
|
Handling run-time error: integer division or modulo
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\section{Raising Exceptions}
|
|
|
|
The {\tt raise} statement allows the programmer to force a specified
|
|
exception to occur.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> raise NameError, 'HiThere'
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
NameError: HiThere
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
The first argument to {\tt raise} names the exception to be raised.
|
|
The optional second argument specifies the exception's argument.
|
|
|
|
\section{User-defined Exceptions}
|
|
|
|
Programs may name their own exceptions by assigning a string to a
|
|
variable.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> my_exc = 'my_exc'
|
|
>>> try:
|
|
... raise my_exc, 2*2
|
|
... except my_exc, val:
|
|
... print 'My exception occurred, value:', val
|
|
...
|
|
My exception occurred, value: 4
|
|
>>> raise my_exc, 1
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
my_exc: 1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Many standard modules use this to report errors that may occur in
|
|
functions they define.
|
|
|
|
\section{Defining Clean-up Actions}
|
|
|
|
The {\tt try} statement has another optional clause which is intended to
|
|
define clean-up actions that must be executed under all circumstances.
|
|
For example:
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> try:
|
|
... raise KeyboardInterrupt
|
|
... finally:
|
|
... print 'Goodbye, world!'
|
|
...
|
|
Goodbye, world!
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 2
|
|
KeyboardInterrupt
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
A {\tt finally} clause is executed whether or not an exception has
|
|
occurred in the {\tt try} clause. When an exception has occurred, it
|
|
is re-raised after the {\tt finally} clause is executed. The
|
|
{\tt finally} clause is also executed ``on the way out'' when the
|
|
{\tt try} statement is left via a {\tt break} or {\tt return}
|
|
statement.
|
|
|
|
A {\tt try} statement must either have one or more {\tt except}
|
|
clauses or one {\tt finally} clause, but not both.
|
|
|
|
|
|
\chapter{Classes}
|
|
|
|
Python's class mechanism adds classes to the language with a minimum
|
|
of new syntax and semantics. It is a mixture of the class mechanisms
|
|
found in C++ and Modula-3. As is true for modules, classes in Python
|
|
do not put an absolute barrier between definition and user, but rather
|
|
rely on the politeness of the user not to ``break into the
|
|
definition.'' The most important features of classes are retained
|
|
with full power, however: the class inheritance mechanism allows
|
|
multiple base classes, a derived class can override any methods of its
|
|
base class(es), a method can call the method of a base class with the
|
|
same name. Objects can contain an arbitrary amount of private data.
|
|
|
|
In C++ terminology, all class members (including the data members) are
|
|
{\em public}, and all member functions are {\em virtual}. There are
|
|
no special constructors or destructors. As in Modula-3, there are no
|
|
shorthands for referencing the object's members from its methods: the
|
|
method function is declared with an explicit first argument
|
|
representing the object, which is provided implicitly by the call. As
|
|
in Smalltalk, classes themselves are objects, albeit in the wider
|
|
sense of the word: in Python, all data types are objects. This
|
|
provides semantics for importing and renaming. But, just like in C++
|
|
or Modula-3, built-in types cannot be used as base classes for
|
|
extension by the user. Also, like in C++ but unlike in Modula-3, most
|
|
built-in operators with special syntax (arithmetic operators,
|
|
subscripting etc.) can be redefined for class members.
|
|
|
|
|
|
\section{A word about terminology}
|
|
|
|
Lacking universally accepted terminology to talk about classes, I'll
|
|
make occasional use of Smalltalk and C++ terms. (I'd use Modula-3
|
|
terms, since its object-oriented semantics are closer to those of
|
|
Python than C++, but I expect that few readers have heard of it...)
|
|
|
|
I also have to warn you that there's a terminological pitfall for
|
|
object-oriented readers: the word ``object'' in Python does not
|
|
necessarily mean a class instance. Like C++ and Modula-3, and unlike
|
|
Smalltalk, not all types in Python are classes: the basic built-in
|
|
types like integers and lists aren't, and even somewhat more exotic
|
|
types like files aren't. However, {\em all} Python types share a little
|
|
bit of common semantics that is best described by using the word
|
|
object.
|
|
|
|
Objects have individuality, and multiple names (in multiple scopes)
|
|
can be bound to the same object. This is known as aliasing in other
|
|
languages. This is usually not appreciated on a first glance at
|
|
Python, and can be safely ignored when dealing with immutable basic
|
|
types (numbers, strings, tuples). However, aliasing has an
|
|
(intended!) effect on the semantics of Python code involving mutable
|
|
objects such as lists, dictionaries, and most types representing
|
|
entities outside the program (files, windows, etc.). This is usually
|
|
used to the benefit of the program, since aliases behave like pointers
|
|
in some respects. For example, passing an object is cheap since only
|
|
a pointer is passed by the implementation; and if a function modifies
|
|
an object passed as an argument, the caller will see the change --- this
|
|
obviates the need for two different argument passing mechanisms as in
|
|
Pascal.
|
|
|
|
|
|
\section{Python scopes and name spaces}
|
|
|
|
Before introducing classes, I first have to tell you something about
|
|
Python's scope rules. Class definitions play some neat tricks with
|
|
name spaces, and you need to know how scopes and name spaces work to
|
|
fully understand what's going on. Incidentally, knowledge about this
|
|
subject is useful for any advanced Python programmer.
|
|
|
|
Let's begin with some definitions.
|
|
|
|
A {\em name space} is a mapping from names to objects. Most name
|
|
spaces are currently implemented as Python dictionaries, but that's
|
|
normally not noticeable in any way (except for performance), and it
|
|
may change in the future. Examples of name spaces are: the set of
|
|
built-in names (functions such as \verb\abs()\, and built-in exception
|
|
names); the global names in a module; and the local names in a
|
|
function invocation. In a sense the set of attributes of an object
|
|
also form a name space. The important things to know about name
|
|
spaces is that there is absolutely no relation between names in
|
|
different name spaces; for instance, two different modules may both
|
|
define a function ``maximize'' without confusion --- users of the
|
|
modules must prefix it with the module name.
|
|
|
|
By the way, I use the word {\em attribute} for any name following a
|
|
dot --- for example, in the expression \verb\z.real\, \verb\real\ is
|
|
an attribute of the object \verb\z\. Strictly speaking, references to
|
|
names in modules are attribute references: in the expression
|
|
\verb\modname.funcname\, \verb\modname\ is a module object and
|
|
\verb\funcname\ is an attribute of it. In this case there happens to
|
|
be a straightforward mapping between the module's attributes and the
|
|
global names defined in the module: they share the same name space!%
|
|
\footnote{
|
|
Except for one thing. Module objects have a secret read-only
|
|
attribute called {\tt __dict__} which returns the dictionary
|
|
used to implement the module's name space; the name
|
|
{\tt __dict__} is an attribute but not a global name.
|
|
Obviously, using this violates the abstraction of name space
|
|
implementation, and should be restricted to things like
|
|
post-mortem debuggers...
|
|
}
|
|
|
|
Attributes may be read-only or writable. In the latter case,
|
|
assignment to attributes is possible. Module attributes are writable:
|
|
you can write \verb\modname.the_answer = 42\. Writable attributes may
|
|
also be deleted with the del statement, e.g.
|
|
\verb\del modname.the_answer\.
|
|
|
|
Name spaces are created at different moments and have different
|
|
lifetimes. The name space containing the built-in names is created
|
|
when the Python interpreter starts up, and is never deleted. The
|
|
global name space for a module is created when the module definition
|
|
is read in; normally, module name spaces also last until the
|
|
interpreter quits. The statements executed by the top-level
|
|
invocation of the interpreter, either read from a script file or
|
|
interactively, are considered part of a module called \verb\__main__\,
|
|
so they have their own global name space. (The built-in names
|
|
actually also live in a module; this is called \verb\__builtin__\.)
|
|
|
|
The local name space for a function is created when the function is
|
|
called, and deleted when the function returns or raises an exception
|
|
that is not handled within the function. (Actually, forgetting would
|
|
be a better way to describe what actually happens.) Of course,
|
|
recursive invocations each have their own local name space.
|
|
|
|
A {\em scope} is a textual region of a Python program where a name space
|
|
is directly accessible. ``Directly accessible'' here means that an
|
|
unqualified reference to a name attempts to find the name in the name
|
|
space.
|
|
|
|
Although scopes are determined statically, they are used dynamically.
|
|
At any time during execution, exactly three nested scopes are in use
|
|
(i.e., exactly three name spaces are directly accessible): the
|
|
innermost scope, which is searched first, contains the local names,
|
|
the middle scope, searched next, contains the current module's global
|
|
names, and the outermost scope (searched last) is the name space
|
|
containing built-in names.
|
|
|
|
Usually, the local scope references the local names of the (textually)
|
|
current function. Outside functions, the the local scope references
|
|
the same name space as the global scope: the module's name space.
|
|
Class definitions place yet another name space in the local scope.
|
|
|
|
It is important to realize that scopes are determined textually: the
|
|
global scope of a function defined in a module is that module's name
|
|
space, no matter from where or by what alias the function is called.
|
|
On the other hand, the actual search for names is done dynamically, at
|
|
run time --- however, the the language definition is evolving towards
|
|
static name resolution, at ``compile'' time, so don't rely on dynamic
|
|
name resolution! (In fact, local variables are already determined
|
|
statically.)
|
|
|
|
A special quirk of Python is that assignments always go into the
|
|
innermost scope. Assignments do not copy data --- they just
|
|
bind names to objects. The same is true for deletions: the statement
|
|
\verb\del x\ removes the binding of x from the name space referenced by the
|
|
local scope. In fact, all operations that introduce new names use the
|
|
local scope: in particular, import statements and function definitions
|
|
bind the module or function name in the local scope. (The
|
|
\verb\global\ statement can be used to indicate that particular
|
|
variables live in the global scope.)
|
|
|
|
|
|
\section{A first look at classes}
|
|
|
|
Classes introduce a little bit of new syntax, three new object types,
|
|
and some new semantics.
|
|
|
|
|
|
\subsection{Class definition syntax}
|
|
|
|
The simplest form of class definition looks like this:
|
|
|
|
\begin{verbatim}
|
|
class ClassName:
|
|
<statement-1>
|
|
.
|
|
.
|
|
.
|
|
<statement-N>
|
|
\end{verbatim}
|
|
|
|
Class definitions, like function definitions (\verb\def\ statements)
|
|
must be executed before they have any effect. (You could conceivably
|
|
place a class definition in a branch of an \verb\if\ statement, or
|
|
inside a function.)
|
|
|
|
In practice, the statements inside a class definition will usually be
|
|
function definitions, but other statements are allowed, and sometimes
|
|
useful --- we'll come back to this later. The function definitions
|
|
inside a class normally have a peculiar form of argument list,
|
|
dictated by the calling conventions for methods --- again, this is
|
|
explained later.
|
|
|
|
When a class definition is entered, a new name space is created, and
|
|
used as the local scope --- thus, all assignments to local variables
|
|
go into this new name space. In particular, function definitions bind
|
|
the name of the new function here.
|
|
|
|
When a class definition is left normally (via the end), a {\em class
|
|
object} is created. This is basically a wrapper around the contents
|
|
of the name space created by the class definition; we'll learn more
|
|
about class objects in the next section. The original local scope
|
|
(the one in effect just before the class definitions was entered) is
|
|
reinstated, and the class object is bound here to class name given in
|
|
the class definition header (ClassName in the example).
|
|
|
|
|
|
\subsection{Class objects}
|
|
|
|
Class objects support two kinds of operations: attribute references
|
|
and instantiation.
|
|
|
|
{\em Attribute references} use the standard syntax used for all
|
|
attribute references in Python: \verb\obj.name\. Valid attribute
|
|
names are all the names that were in the class's name space when the
|
|
class object was created. So, if the class definition looked like
|
|
this:
|
|
|
|
\begin{verbatim}
|
|
class MyClass:
|
|
i = 12345
|
|
def f(x):
|
|
return 'hello world'
|
|
\end{verbatim}
|
|
|
|
then \verb\MyClass.i\ and \verb\MyClass.f\ are valid attribute
|
|
references, returning an integer and a function object, respectively.
|
|
Class attributes can also be assigned to, so you can change the
|
|
value of \verb\MyClass.i\ by assignment.
|
|
|
|
Class {\em instantiation} uses function notation. Just pretend that
|
|
the class object is a parameterless function that returns a new
|
|
instance of the class. For example, (assuming the above class):
|
|
|
|
\begin{verbatim}
|
|
x = MyClass()
|
|
\end{verbatim}
|
|
|
|
creates a new {\em instance} of the class and assigns this object to
|
|
the local variable \verb\x\.
|
|
|
|
|
|
\subsection{Instance objects}
|
|
|
|
Now what can we do with instance objects? The only operations
|
|
understood by instance objects are attribute references. There are
|
|
two kinds of valid attribute names.
|
|
|
|
The first I'll call {\em data attributes}. These correspond to
|
|
``instance variables'' in Smalltalk, and to ``data members'' in C++.
|
|
Data attributes need not be declared; like local variables, they
|
|
spring into existence when they are first assigned to. For example,
|
|
if \verb\x\ in the instance of \verb\MyClass\ created above, the
|
|
following piece of code will print the value 16, without leaving a
|
|
trace:
|
|
|
|
\begin{verbatim}
|
|
x.counter = 1
|
|
while x.counter < 10:
|
|
x.counter = x.counter * 2
|
|
print x.counter
|
|
del x.counter
|
|
\end{verbatim}
|
|
|
|
The second kind of attribute references understood by instance objects
|
|
are {\em methods}. A method is a function that ``belongs to'' an
|
|
object. (In Python, the term method is not unique to class instances:
|
|
other object types can have methods as well, e.g., list objects have
|
|
methods called append, insert, remove, sort, and so on. However,
|
|
below, we'll use the term method exclusively to mean methods of class
|
|
instance objects, unless explicitly stated otherwise.)
|
|
|
|
Valid method names of an instance object depend on its class. By
|
|
definition, all attributes of a class that are (user-defined) function
|
|
objects define corresponding methods of its instances. So in our
|
|
example, \verb\x.f\ is a valid method reference, since
|
|
\verb\MyClass.f\ is a function, but \verb\x.i\ is not, since
|
|
\verb\MyClass.i\ is not. But \verb\x.f\ is not the
|
|
same thing as \verb\MyClass.f\ --- it is a {\em method object}, not a
|
|
function object.
|
|
|
|
|
|
\subsection{Method objects}
|
|
|
|
Usually, a method is called immediately, e.g.:
|
|
|
|
\begin{verbatim}
|
|
x.f()
|
|
\end{verbatim}
|
|
|
|
In our example, this will return the string \verb\'hello world'\.
|
|
However, it is not necessary to call a method right away: \verb\x.f\
|
|
is a method object, and can be stored away and called at a later
|
|
moment, for example:
|
|
|
|
\begin{verbatim}
|
|
xf = x.f
|
|
while 1:
|
|
print xf()
|
|
\end{verbatim}
|
|
|
|
will continue to print \verb\hello world\ until the end of time.
|
|
|
|
What exactly happens when a method is called? You may have noticed
|
|
that \verb\x.f()\ was called without an argument above, even though
|
|
the function definition for \verb\f\ specified an argument. What
|
|
happened to the argument? Surely Python raises an exception when a
|
|
function that requires an argument is called without any --- even if
|
|
the argument isn't actually used...
|
|
|
|
Actually, you may have guessed the answer: the special thing about
|
|
methods is that the object is passed as the first argument of the
|
|
function. In our example, the call \verb\x.f()\ is exactly equivalent
|
|
to \verb\MyClass.f(x)\. In general, calling a method with a list of
|
|
{\em n} arguments is equivalent to calling the corresponding function
|
|
with an argument list that is created by inserting the method's object
|
|
before the first argument.
|
|
|
|
If you still don't understand how methods work, a look at the
|
|
implementation can perhaps clarify matters. When an instance
|
|
attribute is referenced that isn't a data attribute, its class is
|
|
searched. If the name denotes a valid class attribute that is a
|
|
function object, a method object is created by packing (pointers to)
|
|
the instance object and the function object just found together in an
|
|
abstract object: this is the method object. When the method object is
|
|
called with an argument list, it is unpacked again, a new argument
|
|
list is constructed from the instance object and the original argument
|
|
list, and the function object is called with this new argument list.
|
|
|
|
|
|
\section{Random remarks}
|
|
|
|
|
|
[These should perhaps be placed more carefully...]
|
|
|
|
|
|
Data attributes override method attributes with the same name; to
|
|
avoid accidental name conflicts, which may cause hard-to-find bugs in
|
|
large programs, it is wise to use some kind of convention that
|
|
minimizes the chance of conflicts, e.g., capitalize method names,
|
|
prefix data attribute names with a small unique string (perhaps just
|
|
an underscore), or use verbs for methods and nouns for data attributes.
|
|
|
|
|
|
Data attributes may be referenced by methods as well as by ordinary
|
|
users (``clients'') of an object. In other words, classes are not
|
|
usable to implement pure abstract data types. In fact, nothing in
|
|
Python makes it possible to enforce data hiding --- it is all based
|
|
upon convention. (On the other hand, the Python implementation,
|
|
written in C, can completely hide implementation details and control
|
|
access to an object if necessary; this can be used by extensions to
|
|
Python written in C.)
|
|
|
|
|
|
Clients should use data attributes with care --- clients may mess up
|
|
invariants maintained by the methods by stamping on their data
|
|
attributes. Note that clients may add data attributes of their own to
|
|
an instance object without affecting the validity of the methods, as
|
|
long as name conflicts are avoided --- again, a naming convention can
|
|
save a lot of headaches here.
|
|
|
|
|
|
There is no shorthand for referencing data attributes (or other
|
|
methods!) from within methods. I find that this actually increases
|
|
the readability of methods: there is no chance of confusing local
|
|
variables and instance variables when glancing through a method.
|
|
|
|
|
|
Conventionally, the first argument of methods is often called
|
|
\verb\self\. This is nothing more than a convention: the name
|
|
\verb\self\ has absolutely no special meaning to Python. (Note,
|
|
however, that by not following the convention your code may be less
|
|
readable by other Python programmers, and it is also conceivable that
|
|
a {\em class browser} program be written which relies upon such a
|
|
convention.)
|
|
|
|
|
|
Any function object that is a class attribute defines a method for
|
|
instances of that class. It is not necessary that the function
|
|
definition is textually enclosed in the class definition: assigning a
|
|
function object to a local variable in the class is also ok. For
|
|
example:
|
|
|
|
\begin{verbatim}
|
|
# Function defined outside the class
|
|
def f1(self, x, y):
|
|
return min(x, x+y)
|
|
|
|
class C:
|
|
f = f1
|
|
def g(self):
|
|
return 'hello world'
|
|
h = g
|
|
\end{verbatim}
|
|
|
|
Now \verb\f\, \verb\g\ and \verb\h\ are all attributes of class
|
|
\verb\C\ that refer to function objects, and consequently they are all
|
|
methods of instances of \verb\C\ --- \verb\h\ being exactly equivalent
|
|
to \verb\g\. Note that this practice usually only serves to confuse
|
|
the reader of a program.
|
|
|
|
|
|
Methods may call other methods by using method attributes of the
|
|
\verb\self\ argument, e.g.:
|
|
|
|
\begin{verbatim}
|
|
class Bag:
|
|
def empty(self):
|
|
self.data = []
|
|
def add(self, x):
|
|
self.data.append(x)
|
|
def addtwice(self, x):
|
|
self.add(x)
|
|
self.add(x)
|
|
\end{verbatim}
|
|
|
|
|
|
The instantiation operation (``calling'' a class object) creates an
|
|
empty object. Many classes like to create objects in a known initial
|
|
state. In early versions of Python, there was no special syntax to
|
|
enforce this (see below), but a convention was widely used:
|
|
add a method named \verb\init\ to the class,
|
|
which initializes the instance (by assigning to some important data
|
|
attributes) and returns the instance itself. For example, class
|
|
\verb\Bag\ above could have the following method:
|
|
|
|
\begin{verbatim}
|
|
def init(self):
|
|
self.empty()
|
|
return self
|
|
\end{verbatim}
|
|
|
|
The client can then create and initialize an instance in one
|
|
statement, as follows:
|
|
|
|
\begin{verbatim}
|
|
x = Bag().init()
|
|
\end{verbatim}
|
|
|
|
In later versions of Python, a special method named \verb\__init__\ may be
|
|
defined instead:
|
|
|
|
\begin{verbatim}
|
|
def __init__(self):
|
|
self.empty()
|
|
\end{verbatim}
|
|
|
|
When a class defines an \verb\__init__\ method, class instantiation
|
|
automatically invokes \verb\__init__\ for the newly-created class
|
|
instance. So in the \verb\Bag\ example, a new and initialized instance
|
|
can be obtained by:
|
|
|
|
\begin{verbatim}
|
|
x = Bag()
|
|
\end{verbatim}
|
|
|
|
Of course, the \verb\__init__\ method may have arguments for greater
|
|
flexibility. In that case, arguments given to the class instantiation
|
|
operator are passed on to \verb\__init__\. For example,
|
|
|
|
\bcode\begin{verbatim}
|
|
>>> class Complex:
|
|
... def __init__(self, realpart, imagpart):
|
|
... self.r = realpart
|
|
... self.i = imagpart
|
|
...
|
|
>>> x = Complex(3.0,-4.5)
|
|
>>> x.r, x.i
|
|
(3.0, -4.5)
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
%
|
|
Methods may reference global names in the same way as ordinary
|
|
functions. The global scope associated with a method is the module
|
|
containing the class definition. (The class itself is never used as a
|
|
global scope!) While one rarely encounters a good reason for using
|
|
global data in a method, there are many legitimate uses of the global
|
|
scope: for one thing, functions and modules imported into the global
|
|
scope can be used by methods, as well as functions and classes defined
|
|
in it. Usually, the class containing the method is itself defined in
|
|
this global scope, and in the next section we'll find some good
|
|
reasons why a method would want to reference its own class!
|
|
|
|
|
|
\section{Inheritance}
|
|
|
|
Of course, a language feature would not be worthy of the name ``class''
|
|
without supporting inheritance. The syntax for a derived class
|
|
definition looks as follows:
|
|
|
|
\begin{verbatim}
|
|
class DerivedClassName(BaseClassName):
|
|
<statement-1>
|
|
.
|
|
.
|
|
.
|
|
<statement-N>
|
|
\end{verbatim}
|
|
|
|
The name \verb\BaseClassName\ must be defined in a scope containing
|
|
the derived class definition. Instead of a base class name, an
|
|
expression is also allowed. This is useful when the base class is
|
|
defined in another module, e.g.,
|
|
|
|
\begin{verbatim}
|
|
class DerivedClassName(modname.BaseClassName):
|
|
\end{verbatim}
|
|
|
|
Execution of a derived class definition proceeds the same as for a
|
|
base class. When the class object is constructed, the base class is
|
|
remembered. This is used for resolving attribute references: if a
|
|
requested attribute is not found in the class, it is searched in the
|
|
base class. This rule is applied recursively if the base class itself
|
|
is derived from some other class.
|
|
|
|
There's nothing special about instantiation of derived classes:
|
|
\verb\DerivedClassName()\ creates a new instance of the class. Method
|
|
references are resolved as follows: the corresponding class attribute
|
|
is searched, descending down the chain of base classes if necessary,
|
|
and the method reference is valid if this yields a function object.
|
|
|
|
Derived classes may override methods of their base classes. Because
|
|
methods have no special privileges when calling other methods of the
|
|
same object, a method of a base class that calls another method
|
|
defined in the same base class, may in fact end up calling a method of
|
|
a derived class that overrides it. (For C++ programmers: all methods
|
|
in Python are ``virtual functions''.)
|
|
|
|
An overriding method in a derived class may in fact want to extend
|
|
rather than simply replace the base class method of the same name.
|
|
There is a simple way to call the base class method directly: just
|
|
call \verb\BaseClassName.methodname(self, arguments)\. This is
|
|
occasionally useful to clients as well. (Note that this only works if
|
|
the base class is defined or imported directly in the global scope.)
|
|
|
|
|
|
\subsection{Multiple inheritance}
|
|
|
|
Python supports a limited form of multiple inheritance as well. A
|
|
class definition with multiple base classes looks as follows:
|
|
|
|
\begin{verbatim}
|
|
class DerivedClassName(Base1, Base2, Base3):
|
|
<statement-1>
|
|
.
|
|
.
|
|
.
|
|
<statement-N>
|
|
\end{verbatim}
|
|
|
|
The only rule necessary to explain the semantics is the resolution
|
|
rule used for class attribute references. This is depth-first,
|
|
left-to-right. Thus, if an attribute is not found in
|
|
\verb\DerivedClassName\, it is searched in \verb\Base1\, then
|
|
(recursively) in the base classes of \verb\Base1\, and only if it is
|
|
not found there, it is searched in \verb\Base2\, and so on.
|
|
|
|
(To some people breadth first---searching \verb\Base2\ and
|
|
\verb\Base3\ before the base classes of \verb\Base1\---looks more
|
|
natural. However, this would require you to know whether a particular
|
|
attribute of \verb\Base1\ is actually defined in \verb\Base1\ or in
|
|
one of its base classes before you can figure out the consequences of
|
|
a name conflict with an attribute of \verb\Base2\. The depth-first
|
|
rule makes no differences between direct and inherited attributes of
|
|
\verb\Base1\.)
|
|
|
|
It is clear that indiscriminate use of multiple inheritance is a
|
|
maintenance nightmare, given the reliance in Python on conventions to
|
|
avoid accidental name conflicts. A well-known problem with multiple
|
|
inheritance is a class derived from two classes that happen to have a
|
|
common base class. While it is easy enough to figure out what happens
|
|
in this case (the instance will have a single copy of ``instance
|
|
variables'' or data attributes used by the common base class), it is
|
|
not clear that these semantics are in any way useful.
|
|
|
|
|
|
\section{Odds and ends}
|
|
|
|
Sometimes it is useful to have a data type similar to the Pascal
|
|
``record'' or C ``struct'', bundling together a couple of named data
|
|
items. An empty class definition will do nicely, e.g.:
|
|
|
|
\begin{verbatim}
|
|
class Employee:
|
|
pass
|
|
|
|
john = Employee() # Create an empty employee record
|
|
|
|
# Fill the fields of the record
|
|
john.name = 'John Doe'
|
|
john.dept = 'computer lab'
|
|
john.salary = 1000
|
|
\end{verbatim}
|
|
|
|
|
|
A piece of Python code that expects a particular abstract data type
|
|
can often be passed a class that emulates the methods of that data
|
|
type instead. For instance, if you have a function that formats some
|
|
data from a file object, you can define a class with methods
|
|
\verb\read()\ and \verb\readline()\ that gets the data from a string
|
|
buffer instead, and pass it as an argument. (Unfortunately, this
|
|
technique has its limitations: a class can't define operations that
|
|
are accessed by special syntax such as sequence subscripting or
|
|
arithmetic operators, and assigning such a ``pseudo-file'' to
|
|
\verb\sys.stdin\ will not cause the interpreter to read further input
|
|
from it.)
|
|
|
|
|
|
Instance method objects have attributes, too: \verb\m.im_self\ is the
|
|
object of which the method is an instance, and \verb\m.im_func\ is the
|
|
function object corresponding to the method.
|
|
|
|
|
|
\chapter{Recent Additions}
|
|
|
|
Python is an evolving language. Since this tutorial was last
|
|
thoroughly revised, several new features have been added to the
|
|
language. While ideally I should revise the tutorial to incorporate
|
|
them in the mainline of the text, lack of time currently requires me
|
|
to a more modest approach. In this chapter I will briefly list the
|
|
most important improvements to the language and how you can use them
|
|
to your benefit.
|
|
|
|
\section{The Last Printed Expression}
|
|
|
|
In interactive mode, the last printed expression is assigned to the
|
|
variable \code\_\. This means that when you are using Python as a
|
|
desk calculator, it is somewhat easier to continue calculations, for
|
|
example:
|
|
|
|
\begin{verbatim}
|
|
>>> tax = 17.5 / 100
|
|
>>> price = 3.50
|
|
>>> price * tax
|
|
0.6125
|
|
>>> price + _
|
|
4.1125
|
|
>>> round(_, 2)
|
|
4.11
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
\section{String Literals}
|
|
|
|
\subsection{Double Quotes}
|
|
|
|
Python can now also use double quotes to surround string literals,
|
|
e.g. \verb\"this doesn't hurt a bit"\.
|
|
|
|
\subsection{Continuation Of String Literals}
|
|
|
|
String literals can span multiple lines by escaping newlines with
|
|
backslashes, e.g.
|
|
|
|
\begin{verbatim}
|
|
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
|
|
\end{verbatim}
|
|
|
|
which would print the following:
|
|
\begin{verbatim}
|
|
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.
|
|
\end{verbatim}
|
|
|
|
\subsection{Triple-quoted strings}
|
|
|
|
In some cases, when you need to include really long strings (e.g.
|
|
containing several paragraphs of informational text), it is annoying
|
|
that you have to terminate each line with \verb@\n\@, especially if
|
|
you would like to reformat the text occasionally with a powerful text
|
|
editor like Emacs. For such situations, ``triple-quoted'' strings can
|
|
be used, e.g.
|
|
|
|
\begin{verbatim}
|
|
hello = """
|
|
|
|
This string is bounded by triple double quotes (3 times ").
|
|
Newlines in the string are retained, though \
|
|
it is still possible\nto use all normal escape sequences.
|
|
|
|
Whitespace at the beginning of a line is
|
|
significant. If you need to include three opening quotes
|
|
you have to escape at least one of them, e.g. \""".
|
|
|
|
This string ends in a newline.
|
|
"""
|
|
\end{verbatim}
|
|
|
|
Note that there is no semantic difference between strings quoted with
|
|
single quotes (\verb/'/) or double quotes (\verb\"\).
|
|
|
|
\subsection{String Literal Juxtaposition}
|
|
|
|
One final twist: you can juxtapose multiple string literals. Two or
|
|
more adjacent string literals (but not arbitrary expressions!)
|
|
separated only by whitespace will be concatenated (without intervening
|
|
whitespace) into a single string object at compile time. This makes
|
|
it possible to continue a long string on the next line without
|
|
sacrificing indentation or performance, unlike the use of the string
|
|
concatenation operator \verb\+\ or the continuation of the literal
|
|
itself on the next line (since leading whitespace is significant
|
|
inside all types of string literals). Note that this feature, like
|
|
all string features except triple-quoted strings, is borrowed from
|
|
Standard C.
|
|
|
|
\section{The Formatting Operator}
|
|
|
|
\subsection{Basic Usage}
|
|
|
|
The chapter on output formatting is really out of date: there is now
|
|
an almost complete interface to C-style printf formats. This is done
|
|
by overloading the modulo operator (\verb\%\) for a left operand
|
|
which is a string, e.g.
|
|
|
|
\begin{verbatim}
|
|
>>> import math
|
|
>>> print 'The value of PI is approximately %5.3f.' % math.pi
|
|
The value of PI is approximately 3.142.
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
If there is more than one format in the string you pass a tuple as
|
|
right operand, e.g.
|
|
|
|
\begin{verbatim}
|
|
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
|
|
>>> for name, phone in table.items():
|
|
... print '%-10s ==> %10d' % (name, phone)
|
|
...
|
|
Jack ==> 4098
|
|
Dcab ==> 8637678
|
|
Sjoerd ==> 4127
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
Most formats work exactly as in C and require that you pass the proper
|
|
type (however, if you don't you get an exception, not a core dump).
|
|
The \verb\%s\ format is more relaxed: if the corresponding argument is
|
|
not a string object, it is converted to string using the \verb\str()\
|
|
built-in function. Using \verb\*\ to pass the width or precision in
|
|
as a separate (integer) argument is supported. The C formats
|
|
\verb\%n\ and \verb\%p\ are not supported.
|
|
|
|
\subsection{Referencing Variables By Name}
|
|
|
|
If you have a really long format string that you don't want to split
|
|
up, it would be nice if you could reference the variables to be
|
|
formatted by name instead of by position. This can be done by using
|
|
an extension of C formats using the form \verb\%(name)format\, e.g.
|
|
|
|
\begin{verbatim}
|
|
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
|
|
>>> print 'Jack: %(Jack)d; Sjoerd: %(Sjoerd)d; Dcab: %(Dcab)d' % table
|
|
Jack: 4098; Sjoerd: 4127; Dcab: 8637678
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
This is particularly useful in combination with the new built-in
|
|
\verb\vars()\ function, which returns a dictionary containing all
|
|
local variables.
|
|
|
|
\section{Optional Function Arguments}
|
|
|
|
It is now possible to define functions with a variable number of
|
|
arguments. There are two forms, which can be combined.
|
|
|
|
\subsection{Default Argument Values}
|
|
|
|
The most useful form is to specify a default value for one or more
|
|
arguments. This creates a function that can be called with fewer
|
|
arguments than it is defined, e.g.
|
|
|
|
\begin{verbatim}
|
|
def ask_ok(prompt, retries = 4, complaint = 'Yes or no, please!'):
|
|
while 1:
|
|
ok = raw_input(prompt)
|
|
if ok in ('y', 'ye', 'yes'): return 1
|
|
if ok in ('n', 'no', 'nop', 'nope'): return 0
|
|
retries = retries - 1
|
|
if retries < 0: raise IOError, 'refusenik user'
|
|
print complaint
|
|
\end{verbatim}
|
|
|
|
This function can be called either like this:
|
|
\verb\ask_ok('Do you really want to quit?')\ or like this:
|
|
\verb\ask_ok('OK to overwrite the file?', 2)\.
|
|
|
|
The default values are evaluated at the point of function definition
|
|
in the {\em defining} scope, so that e.g.
|
|
|
|
\begin{verbatim}
|
|
i = 5
|
|
def f(arg = i): print arg
|
|
i = 6
|
|
f()
|
|
\end{verbatim}
|
|
|
|
will print \verb\5\.
|
|
|
|
\subsection{Arbitrary Argument Lists}
|
|
|
|
It is also possible to specify that a function can be called with an
|
|
arbitrary number of arguments. These arguments will be wrapped up in
|
|
a tuple. Before the variable number of arguments, zero or more normal
|
|
arguments may occur, e.g.
|
|
|
|
\begin{verbatim}
|
|
def fprintf(file, format, *args):
|
|
file.write(format % args)
|
|
\end{verbatim}
|
|
|
|
This feature may be combined with the previous, e.g.
|
|
|
|
\begin{verbatim}
|
|
def but_is_it_useful(required, optional = None, *remains):
|
|
print "I don't know"
|
|
\end{verbatim}
|
|
|
|
\section{Lambda And Functional Programming Tools}
|
|
|
|
\subsection{Lambda Forms}
|
|
|
|
On popular demand, a few features commonly found in functional
|
|
programming languages and Lisp have been added to Python. With the
|
|
\verb\lambda\ keyword, small anonymous functions can be created.
|
|
Here's a function that returns the sum of its two arguments:
|
|
\verb\lambda a, b: a+b\. Lambda forms can be used wherever function
|
|
objects are required. They are syntactically restricted to a single
|
|
expression. Semantically, they are just syntactic sugar for a normal
|
|
function definition. Like nested function definitions, lambda forms
|
|
cannot reference variables from the containing scope, but this can be
|
|
overcome through the judicious use of default argument values, e.g.
|
|
|
|
\begin{verbatim}
|
|
def make_incrementor(n):
|
|
return lambda(x, incr=n): x+incr
|
|
\end{verbatim}
|
|
|
|
\subsection{Map, Reduce and Filter}
|
|
|
|
Three new built-in functions on sequences are good candidate to pass
|
|
lambda forms.
|
|
|
|
\subsubsection{Map.}
|
|
|
|
\verb\map(function, sequence)\ calls \verb\function(item)\ for each of
|
|
the sequence's items and returns a list of the return values. For
|
|
example, to compute some cubes:
|
|
|
|
\begin{verbatim}
|
|
>>> map(lambda x: x*x*x, range(1, 11))
|
|
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
More than one sequence may be passed; the function must then have as
|
|
many arguments as there are sequences and is called with the
|
|
corresponding item from each sequence (or \verb\None\ if some sequence
|
|
is shorter than another). If \verb\None\ is passed for the function,
|
|
a function returning its argument(s) is substituted.
|
|
|
|
Combining these two special cases, we see that
|
|
\verb\map(None, list1, list2)\ is a convenient way of turning a pair
|
|
of lists into a list of pairs. For example:
|
|
|
|
\begin{verbatim}
|
|
>>> seq = range(8)
|
|
>>> map(None, seq, map(lambda x: x*x, seq))
|
|
[(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25), (6, 36), (7, 49)]
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
\subsubsection{Filter.}
|
|
|
|
\verb\filter(function, sequence)\ returns a sequence (of the same
|
|
type, if possible) consisting of those items from the sequence for
|
|
which \verb\function(item)\ is true. For example, to compute some
|
|
primes:
|
|
|
|
\begin{verbatim}
|
|
>>> filter(lambda x: x%2 != 0 and x%3 != 0, range(2, 25))
|
|
[5, 7, 11, 13, 17, 19, 23]
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
\subsubsection{Reduce.}
|
|
|
|
\verb\reduce(function, sequence)\ returns a single value constructed
|
|
by calling the (binary) function on the first two items of the
|
|
sequence, then on the result and the next item, and so on. For
|
|
example, to compute the sum of the numbers 1 through 10:
|
|
|
|
\begin{verbatim}
|
|
>>> reduce(lambda x, y: x+y, range(1, 11))
|
|
55
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
If there's only one item in the sequence, its value is returned; if
|
|
the sequence is empty, an exception is raised.
|
|
|
|
A third argument can be passed to indicate the starting value. In this
|
|
case the starting value is returned for an empty sequence, and the
|
|
function is first applied to the starting value and the first sequence
|
|
item, then to the result and the next item, and so on. For example,
|
|
|
|
\begin{verbatim}
|
|
>>> def sum(seq):
|
|
... return reduce(lambda x, y: x+y, seq, 0)
|
|
...
|
|
>>> sum(range(1, 11))
|
|
55
|
|
>>> sum([])
|
|
0
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
\section{Continuation Lines Without Backslashes}
|
|
|
|
While the general mechanism for continuation of a source line on the
|
|
next physical line remains to place a backslash on the end of the
|
|
line, expressions inside matched parentheses (or square brackets, or
|
|
curly braces) can now also be continued without using a backslash.
|
|
This is particularly useful for calls to functions with many
|
|
arguments, and for initializations of large tables.
|
|
|
|
For example:
|
|
|
|
\begin{verbatim}
|
|
month_names = ['Januari', 'Februari', 'Maart',
|
|
'April', 'Mei', 'Juni',
|
|
'Juli', 'Augustus', 'September',
|
|
'Oktober', 'November', 'December']
|
|
\end{verbatim}
|
|
|
|
and
|
|
|
|
\begin{verbatim}
|
|
CopyInternalHyperLinks(self.context.hyperlinks,
|
|
copy.context.hyperlinks,
|
|
uidremap)
|
|
\end{verbatim}
|
|
|
|
\section{Regular Expressions}
|
|
|
|
While C's printf-style output formats, transformed into Python, are
|
|
adequate for most output formatting jobs, C's scanf-style input
|
|
formats are not very powerful. Instead of scanf-style input, Python
|
|
offers Emacs-style regular expressions as a powerful input and
|
|
scanning mechanism. Read the corresponding section in the Library
|
|
Reference for a full description.
|
|
|
|
\section{Generalized Dictionaries}
|
|
|
|
The keys of dictionaries are no longer restricted to strings -- they
|
|
can be numbers, tuples, or (certain) class instances. (Lists and
|
|
dictionaries are not acceptable as dictionary keys, in order to avoid
|
|
problems when the object used as a key is modified.)
|
|
|
|
Dictionaries have two new methods: \verb\d.values()\ returns a list of
|
|
the dictionary's values, and \verb\d.items()\ returns a list of the
|
|
dictionary's (key, value) pairs. Like \verb\d.keys()\, these
|
|
operations are slow for large dictionaries. Examples:
|
|
|
|
\begin{verbatim}
|
|
>>> d = {100: 'honderd', 1000: 'duizend', 10: 'tien'}
|
|
>>> d.keys()
|
|
[100, 10, 1000]
|
|
>>> d.values()
|
|
['honderd', 'tien', 'duizend']
|
|
>>> d.items()
|
|
[(100, 'honderd'), (10, 'tien'), (1000, 'duizend')]
|
|
>>>
|
|
\end{verbatim}
|
|
|
|
\section{Miscellaneous New Built-in Functions}
|
|
|
|
The function \verb\vars()\ returns a dictionary containing the current
|
|
local variables. With a module as argument, it returns that module's
|
|
global variables. The old function \verb\dir(x)\ returns
|
|
\verb\vars(x).keys()\.
|
|
|
|
The function \verb\round(x)\ returns a floating point number rounded
|
|
to the nearest integer (but still expressed as a floating point
|
|
number). E.g. \verb\round(3.4) == 3.0\ and \verb\round(3.5) == 4.0\.
|
|
With a second argument it rounds to the specified number of digits,
|
|
e.g. \verb\round(math.pi, 4) == 3.1416\ or even
|
|
\verb\round(123.4, -2) == 100.0\.
|
|
|
|
The function \verb\hash(x)\ returns a hash value for an object.
|
|
All object types acceptable as dictionary keys have a hash value (and
|
|
it is this hash value that the dictionary implementation uses).
|
|
|
|
The function \verb\id(x)\ return a unique identifier for an object.
|
|
For two objects x and y, \verb\id(x) == id(y)\ if and only if
|
|
\verb\x is y\. (In fact the object's address is used.)
|
|
|
|
The function \verb\hasattr(x, name)\ returns whether an object has an
|
|
attribute with the given name (a string value). The function
|
|
\verb\getattr(x, name)\ returns the object's attribute with the given
|
|
name. The function \verb\setattr(x, name, value)\ assigns a value to
|
|
an object's attribute with the given name. These three functions are
|
|
useful if the attribute names are not known beforehand. Note that
|
|
\verb\getattr(x, 'foo')\ is equivalent to \verb\x.foo\, and
|
|
\verb\setattr(x, 'foo', y)\ is equivalent to \verb\x.foo = y\. By
|
|
definition, \verb\hasattr(x, name)\ returns true if and only if
|
|
\verb\getattr(x, name)\ returns without raising an exception.
|
|
|
|
\section{Else Clause For Try Statement}
|
|
|
|
The \verb\try...except\ statement now has an optional \verb\else\
|
|
clause, which must follow all \verb\except\ clauses. It is useful to
|
|
place code that must be executed if the \verb\try\ clause does not
|
|
raise an exception. For example:
|
|
|
|
\begin{verbatim}
|
|
for arg in sys.argv:
|
|
try:
|
|
f = open(arg, 'r')
|
|
except IOError:
|
|
print 'cannot open', arg
|
|
else:
|
|
print arg, 'has', len(f.readlines()), 'lines'
|
|
f.close()
|
|
\end{verbatim}
|
|
|
|
\end{document}
|