mirror of https://github.com/python/cpython
3496 lines
122 KiB
TeX
3496 lines
122 KiB
TeX
\documentclass{manual}
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% Things to do:
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% Add a section on file I/O
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% Write a chapter entitled ``Some Useful Modules''
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% --regex, math+cmath
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% Should really move the Python startup file info to an appendix
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\title{Python Tutorial}
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\input{boilerplate}
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\begin{document}
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\maketitle
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\input{copyright}
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\begin{abstract}
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\noindent
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Python is an easy to learn, powerful programming language. It has
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efficient high-level data structures and a simple but effective
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approach to object-oriented programming. Python's elegant syntax and
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dynamic typing, together with its interpreted nature, make it an ideal
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language for scripting and rapid application development in many areas
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on most platforms.
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The Python interpreter and the extensive standard library are freely
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available in source or binary form for all major platforms from the
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Python web site, \url{http://www.python.org}, and can be freely
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distributed. The same site also contains distributions of and
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pointers to many free third party Python modules, programs and tools,
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and additional documentation.
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The Python interpreter is easily extended with new functions and data
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types implemented in \C{} or \Cpp{} (or other languages callable from \C{}).
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Python is also suitable as an extension language for customizable
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applications.
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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 all examples are
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self-contained, so the tutorial can be read off-line as well.
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For a description of standard objects and modules, see the
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\emph{Python Library Reference} document. The \emph{Python Reference
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Manual} gives a more formal definition of the language. To write
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extensions in \C{} or \Cpp{}, read the \emph{Extending and Embedding} and
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\emph{Python/\C{} API} manuals. There are also several books covering
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Python in depth.
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This tutorial does not attempt to be comprehensive and cover every
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single feature, or even every commonly used feature. Instead, it
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introduces many of Python's most noteworthy features, and will give
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you a good idea of the language's flavor and style. After reading it,
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you will be able to read and write Python modules and programs, and
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you will be ready to learn more about the various Python library
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modules described in the \emph{Python Library Reference}.
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\end{abstract}
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\tableofcontents
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\chapter{Whetting Your Appetite}
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\label{intro}
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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 the problem requires variable-length strings or
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other data types (like sorted lists of file names) that are easy in
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the shell but lots of work to implement in \C{}, or perhaps you're not
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sufficiently familiar with \C{}.
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Another situation: perhaps you have to work with several \C{} libraries,
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and the usual \C{} write/compile/test/re-compile cycle is too slow. You
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need to develop software more quickly. Possibly perhaps you've
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written a program that could use an extension language, and you don't
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want to design a language, write and debug an interpreter for it, then
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tie it into your application.
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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 \emph{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
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\emph{Awk} or even \emph{Perl}, yet many things are at least as easy
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in 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 interfaces to GUI toolkits like Tk.
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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 \emph{extensible}: if you know how to program in \C{} it is easy
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to add a new built-in function or 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 Python's
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Flying Circus'' and has nothing to do with nasty reptiles. Making
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references to Monty Python skits in documentation is not only allowed,
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it is encouraged!
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\section{Where From Here}
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\label{where}
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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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\chapter{Using the Python Interpreter}
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\label{using}
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\section{Invoking the Interpreter}
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\label{invoking}
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The Python interpreter is usually installed as \file{/usr/local/bin/python}
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on those machines where it is available; putting \file{/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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\begin{verbatim}
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python
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\end{verbatim}
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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.,
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\file{/usr/local/python} is a popular alternative location.)
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Typing an EOF character (Control-D on \UNIX{}, Control-Z or F6 on DOS
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or Windows) at the primary prompt causes the interpreter to exit with
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a zero exit status. If that doesn't work, you can exit the
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interpreter by typing the following commands: \samp{import sys;
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sys.exit()}.
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The interpreter's line-editing features usually aren't very
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sophisticated. On \UNIX{}, whoever installed the interpreter may have
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enabled support for the GNU readline library, which adds more
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elaborate interactive editing and history features. Perhaps the
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quickest check to see whether command line editing is supported is
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typing Control-P to the first Python prompt you get. If it beeps, you
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have command line editing; see Appendix A for an introduction to the
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keys. If nothing appears to happen, or if \code{\^P} is echoed,
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command line editing isn't available; you'll only be able to use
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backspace to remove characters from the current line.
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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 \emph{script} from
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that file.
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A third way of starting the interpreter is
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\samp{python -c command [arg] ...}, which
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executes the statement(s) in \code{command}, analogous to the shell's
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\code{-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
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\code{command} in its entirety with double quotes.
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Note that there is a difference between \samp{python file} and
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\samp{python <file}. In the latter case, input requests from the
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program, such as calls to \code{input()} and \code{raw_input()}, are
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satisfied from \emph{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 \code{-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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\label{argPassing}
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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
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\code{sys.argv}, which is a list of strings. Its length is at least
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one; when no script and no arguments are given, \code{sys.argv[0]} is
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an empty string. When the script name is given as \code{'-'} (meaning
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standard input), \code{sys.argv[0]} is set to \code{'-'}. When \code{-c
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command} is used, \code{sys.argv[0]} is set to \code{'-c'}. Options
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found after \code{-c command} are not consumed by the Python
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interpreter's option processing but left in \code{sys.argv} for the
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command to handle.
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\subsection{Interactive Mode}
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\label{interactive}
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When commands are read from a tty, the interpreter is said to be in
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\emph{interactive mode}. In this mode it prompts for the next command
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with the \emph{primary prompt}, usually three greater-than signs
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(\samp{>>> }); for continuation lines it prompts with the
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\emph{secondary prompt},
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by default three dots (\samp{... }).
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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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\begin{verbatim}
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python
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Python 1.5b1 (#1, Dec 3 1997, 00:02:06) [GCC 2.7.2.2] on sunos5
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Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam
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>>>
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\end{verbatim}
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\section{The Interpreter and Its Environment}
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\label{interp}
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\subsection{Error Handling}
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\label{error}
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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 \code{except} clause in a
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\code{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
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\code{KeyboardInterrupt} exception, which may be handled by a
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\code{try} statement.
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\subsection{Executable Python Scripts}
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\label{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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\begin{verbatim}
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#! /usr/bin/env python
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\end{verbatim}
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(assuming that the interpreter is on the user's \envvar{PATH}) at the
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beginning of the script and giving the file an executable mode. The
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\samp{\#!} must be the first two characters of the file.
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\subsection{The Interactive Startup File}
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\label{startup}
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% XXX This should probably be dumped in an appendix, since most people
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% don't use Python interactively in non-trivial ways.
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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
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\envvar{PYTHONSTARTUP} to the name of a file containing your start-up
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commands. This is similar to the \file{.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 \file{/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 \code{sys.ps1} and \code{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,
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e.g.\ \samp{execfile('.pythonrc')}\indexii{.pythonrc.py}{file}. If
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you want to use the startup file in a script, you must do this
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explicitly in the script:
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\begin{verbatim}
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import os
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if os.path.isfile(os.environ['PYTHONSTARTUP']):
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execfile(os.environ['PYTHONSTARTUP'])
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\end{verbatim}
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\chapter{An Informal Introduction to Python}
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\label{informal}
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In the following examples, input and output are distinguished by the
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presence or absence of prompts (\samp{>>> } and \samp{... }): 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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\label{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, \samp{>>> }. (It shouldn't take long.)
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\subsection{Numbers}
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\label{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 \code{+}, \code{-}, \code{*} and \code{/}
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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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\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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\end{verbatim}
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Like in \C{}, the equal sign (\character{=}) 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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\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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\end{verbatim}
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%
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A value can be assigned to several variables simultaneously:
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\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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\end{verbatim}
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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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\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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\end{verbatim}
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%
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Complex numbers are also supported; imaginary numbers are written with
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a suffix of \samp{j} or \samp{J}. Complex numbers with a nonzero
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real component are written as \samp{(\var{real}+\var{imag}j)}, or can
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be created with the \samp{complex(\var{real}, \var{imag})} function.
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\begin{verbatim}
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>>> 1j * 1J
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(-1+0j)
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>>> 1j * complex(0,1)
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(-1+0j)
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>>> 3+1j*3
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(3+3j)
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>>> (3+1j)*3
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(9+3j)
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>>> (1+2j)/(1+1j)
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(1.5+0.5j)
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\end{verbatim}
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%
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Complex numbers are always represented as two floating point numbers,
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the real and imaginary part. To extract these parts from a complex
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number \var{z}, use \code{\var{z}.real} and \code{\var{z}.imag}.
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\begin{verbatim}
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>>> a=1.5+0.5j
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>>> a.real
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1.5
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>>> a.imag
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0.5
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\end{verbatim}
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%
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The conversion functions to floating point and integer
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(\function{float()}, \function{int()} and \function{long()}) don't
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work for complex numbers --- there is no one correct way to convert a
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complex number to a real number. Use \code{abs(\var{z})} to get its
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magnitude (as a float) or \code{z.real} to get its real part.
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\begin{verbatim}
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>>> a=1.5+0.5j
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>>> float(a)
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Traceback (innermost last):
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File "<stdin>", line 1, in ?
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TypeError: can't convert complex to float; use e.g. abs(z)
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>>> a.real
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1.5
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>>> abs(a)
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1.58113883008
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\end{verbatim}
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%
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In interactive mode, the last printed expression is assigned to the
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variable \code{_}. This means that when you are using Python as a
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desk calculator, it is somewhat easier to continue calculations, for
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example:
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\begin{verbatim}
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>>> tax = 17.5 / 100
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>>> price = 3.50
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>>> price * tax
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0.6125
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>>> price + _
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4.1125
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>>> round(_, 2)
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4.11
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\end{verbatim}
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This variable should be treated as read-only by the user. Don't
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explicitly assign a value to it --- you would create an independent
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local variable with the same name masking the built-in variable with
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its magic behavior.
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\subsection{Strings}
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\label{strings}
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Besides numbers, Python can also manipulate strings, which can be
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expressed in several ways. They can be enclosed in single quotes or
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double quotes:
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\begin{verbatim}
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>>> 'spam eggs'
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'spam eggs'
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>>> 'doesn\'t'
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"doesn't"
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>>> "doesn't"
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"doesn't"
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>>> '"Yes," he said.'
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'"Yes," he said.'
|
|
>>> "\"Yes,\" he said."
|
|
'"Yes," he said.'
|
|
>>> '"Isn\'t," she said.'
|
|
'"Isn\'t," she said.'
|
|
\end{verbatim}
|
|
|
|
String literals can span multiple lines in several ways. Newlines can
|
|
be escaped 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}
|
|
|
|
Or, strings can be surrounded in a pair of matching triple-quotes:
|
|
\code{"""} or \code {'''}. End of lines do not need to be escaped
|
|
when using triple-quotes, but they will be included in the string.
|
|
|
|
\begin{verbatim}
|
|
print """
|
|
Usage: thingy [OPTIONS]
|
|
-h Display this usage message
|
|
-H hostname Hostname to connect to
|
|
"""
|
|
\end{verbatim}
|
|
|
|
produces the following output:
|
|
|
|
\begin{verbatim}
|
|
Usage: thingy [OPTIONS]
|
|
-h Display this usage message
|
|
-H hostname Hostname to connect to
|
|
\end{verbatim}
|
|
|
|
The interpreter prints the result of string operations in the same way
|
|
as they are typed for input: inside quotes, and with quotes and other
|
|
funny characters escaped by backslashes, to show the precise
|
|
value. The string is enclosed in double quotes if the string contains
|
|
a single quote and no double quotes, else it's enclosed in single
|
|
quotes. (The \keyword{print} statement, described later, can be used
|
|
to write strings without quotes or escapes.)
|
|
|
|
Strings can be concatenated (glued together) with the \code{+}
|
|
operator, and repeated with \code{*}:
|
|
|
|
\begin{verbatim}
|
|
>>> word = 'Help' + 'A'
|
|
>>> word
|
|
'HelpA'
|
|
>>> '<' + word*5 + '>'
|
|
'<HelpAHelpAHelpAHelpAHelpA>'
|
|
\end{verbatim}
|
|
|
|
Two string literals next to each other are automatically concatenated;
|
|
the first line above could also have been written \samp{word = 'Help'
|
|
'A'}; this only works with two literals, not with arbitrary string expressions.
|
|
|
|
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 \emph{slice notation}: two indices
|
|
separated by a colon.
|
|
|
|
\begin{verbatim}
|
|
>>> word[4]
|
|
'A'
|
|
>>> word[0:2]
|
|
'He'
|
|
>>> word[2:4]
|
|
'lp'
|
|
\end{verbatim}
|
|
|
|
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.
|
|
|
|
\begin{verbatim}
|
|
>>> word[:2] # The first two characters
|
|
'He'
|
|
>>> word[2:] # All but the first two characters
|
|
'lpA'
|
|
\end{verbatim}
|
|
|
|
Here's a useful invariant of slice operations: \code{s[:i] + s[i:]}
|
|
equals \code{s}.
|
|
|
|
\begin{verbatim}
|
|
>>> word[:2] + word[2:]
|
|
'HelpA'
|
|
>>> word[:3] + word[3:]
|
|
'HelpA'
|
|
\end{verbatim}
|
|
|
|
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.
|
|
|
|
\begin{verbatim}
|
|
>>> word[1:100]
|
|
'elpA'
|
|
>>> word[10:]
|
|
''
|
|
>>> word[2:1]
|
|
''
|
|
\end{verbatim}
|
|
|
|
Indices may be negative numbers, to start counting from the right.
|
|
For example:
|
|
|
|
\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}
|
|
|
|
But note that -0 is really the same as 0, so it does not count from
|
|
the right!
|
|
|
|
\begin{verbatim}
|
|
>>> word[-0] # (since -0 equals 0)
|
|
'H'
|
|
\end{verbatim}
|
|
|
|
Out-of-range negative slice indices are truncated, but don't try this
|
|
for single-element (non-slice) indices:
|
|
|
|
\begin{verbatim}
|
|
>>> word[-100:]
|
|
'HelpA'
|
|
>>> word[-10] # error
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
IndexError: string index out of range
|
|
\end{verbatim}
|
|
|
|
The best way to remember how slices work is to think of the indices as
|
|
pointing \emph{between} characters, with the left edge of the first
|
|
character numbered 0. Then the right edge of the last character of a
|
|
string of \var{n} characters has index \var{n}, for example:
|
|
|
|
\begin{verbatim}
|
|
+---+---+---+---+---+
|
|
| H | e | l | p | A |
|
|
+---+---+---+---+---+
|
|
0 1 2 3 4 5
|
|
-5 -4 -3 -2 -1
|
|
\end{verbatim}
|
|
|
|
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 \var{i} to \var{j} consists of all characters between
|
|
the edges labeled \var{i} and \var{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
|
|
\code{word[1:3]} is 2.
|
|
|
|
The built-in function \function{len()} returns the length of a string:
|
|
|
|
\begin{verbatim}
|
|
>>> s = 'supercalifragilisticexpialidocious'
|
|
>>> len(s)
|
|
34
|
|
\end{verbatim}
|
|
|
|
\subsection{Lists}
|
|
\label{lists}
|
|
|
|
Python knows a number of \emph{compound} data types, used to group
|
|
together other values. The most versatile is the \emph{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.
|
|
|
|
\begin{verbatim}
|
|
>>> a = ['spam', 'eggs', 100, 1234]
|
|
>>> a
|
|
['spam', 'eggs', 100, 1234]
|
|
\end{verbatim}
|
|
|
|
Like string indices, list indices start at 0, and lists can be sliced,
|
|
concatenated and so on:
|
|
|
|
\begin{verbatim}
|
|
>>> a[0]
|
|
'spam'
|
|
>>> a[3]
|
|
1234
|
|
>>> a[-2]
|
|
100
|
|
>>> a[1:-1]
|
|
['eggs', 100]
|
|
>>> a[:2] + ['bacon', 2*2]
|
|
['spam', 'eggs', 'bacon', 4]
|
|
>>> 3*a[:3] + ['Boe!']
|
|
['spam', 'eggs', 100, 'spam', 'eggs', 100, 'spam', 'eggs', 100, 'Boe!']
|
|
\end{verbatim}
|
|
|
|
Unlike strings, which are \emph{immutable}, it is possible to change
|
|
individual elements of a list:
|
|
|
|
\begin{verbatim}
|
|
>>> a
|
|
['spam', 'eggs', 100, 1234]
|
|
>>> a[2] = a[2] + 23
|
|
>>> a
|
|
['spam', 'eggs', 123, 1234]
|
|
\end{verbatim}
|
|
|
|
Assignment to slices is also possible, and this can even change the size
|
|
of the list:
|
|
|
|
\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}
|
|
|
|
The built-in function \function{len()} also applies to lists:
|
|
|
|
\begin{verbatim}
|
|
>>> len(a)
|
|
8
|
|
\end{verbatim}
|
|
|
|
It is possible to nest lists (create lists containing other lists),
|
|
for example:
|
|
|
|
\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}
|
|
|
|
Note that in the last example, \code{p[1]} and \code{q} really refer to
|
|
the same object! We'll come back to \emph{object semantics} later.
|
|
|
|
\section{First Steps Towards Programming}
|
|
\label{firstSteps}
|
|
|
|
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 \emph{Fibonacci} series as follows:
|
|
|
|
\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}
|
|
|
|
This example introduces several new features.
|
|
|
|
\begin{itemize}
|
|
|
|
\item
|
|
The first line contains a \emph{multiple assignment}: the variables
|
|
\code{a} and \code{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 \keyword{while} loop executes as long as the condition (here:
|
|
\code{b < 10}) remains true. In Python, like in \C{}, any non-zero
|
|
integer value is true; zero is false. The condition may also be a
|
|
string or list value, in fact any sequence; anything with a non-zero
|
|
length is true, empty sequences are false. The test used in the
|
|
example is a simple comparison. The standard comparison operators are
|
|
written the same as in \C{}: \code{<}, \code{>}, \code{==}, \code{<=},
|
|
\code{>=} and \code{!=}.
|
|
|
|
\item
|
|
The \emph{body} of the loop is \emph{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 \keyword{print} statement writes the value of the expression(s) it is
|
|
given. It differs from just writing the expression you want to write
|
|
(as we did earlier in the calculator examples) in the way it handles
|
|
multiple expressions and strings. Strings are printed without quotes,
|
|
and a space is inserted between items, so you can format things nicely,
|
|
like this:
|
|
|
|
\begin{verbatim}
|
|
>>> i = 256*256
|
|
>>> print 'The value of i is', i
|
|
The value of i is 65536
|
|
\end{verbatim}
|
|
|
|
A trailing comma avoids the newline after the output:
|
|
|
|
\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}
|
|
|
|
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}
|
|
\label{moreControl}
|
|
|
|
Besides the \keyword{while} statement just introduced, Python knows
|
|
the usual control flow statements known from other languages, with
|
|
some twists.
|
|
|
|
\section{\keyword{if} Statements}
|
|
\label{if}
|
|
|
|
Perhaps the most well-known statement type is the \keyword{if}
|
|
statement. For example:
|
|
|
|
\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}
|
|
|
|
There can be zero or more \keyword{elif} parts, and the \keyword{else}
|
|
part is optional. The keyword `\keyword{elif}' is short for `else
|
|
if', and is useful to avoid excessive indentation. An
|
|
\keyword{if} \ldots\ \keyword{elif} \ldots\ \keyword{elif}
|
|
\ldots\ sequence is a substitute for the \emph{switch} or
|
|
% ^^^^
|
|
% Weird spacings happen here if the wrapping of the source text
|
|
% gets changed in the wrong way.
|
|
\emph{case} statements found in other languages.
|
|
|
|
\section{\keyword{for} Statements}
|
|
\label{for}
|
|
|
|
The \keyword{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
|
|
\keyword{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):
|
|
|
|
\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}
|
|
|
|
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:
|
|
|
|
\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}
|
|
|
|
\section{The \function{range()} Function}
|
|
\label{range}
|
|
|
|
If you do need to iterate over a sequence of numbers, the built-in
|
|
function \function{range()} comes in handy. It generates lists
|
|
containing arithmetic progressions, e.g.:
|
|
|
|
\begin{verbatim}
|
|
>>> range(10)
|
|
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
|
|
\end{verbatim}
|
|
|
|
The given end point is never part of the generated list;
|
|
\code{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):
|
|
|
|
\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}
|
|
|
|
To iterate over the indices of a sequence, combine \function{range()}
|
|
and \function{len()} as follows:
|
|
|
|
\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}
|
|
|
|
\section{\keyword{break} and \keyword{continue} Statements, and
|
|
\keyword{else} Clauses on Loops}
|
|
\label{break}
|
|
|
|
The \keyword{break} statement, like in \C{}, breaks out of the smallest
|
|
enclosing \keyword{for} or \keyword{while} loop.
|
|
|
|
The \keyword{continue} statement, also borrowed from \C{}, continues
|
|
with the next iteration of the loop.
|
|
|
|
Loop statements may have an \code{else} clause; it is executed when
|
|
the loop terminates through exhaustion of the list (with
|
|
\keyword{for}) or when the condition becomes false (with
|
|
\keyword{while}), but not when the loop is terminated by a
|
|
\keyword{break} statement. This is exemplified by the following loop,
|
|
which searches for prime numbers:
|
|
|
|
\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}
|
|
|
|
\section{\keyword{pass} Statements}
|
|
\label{pass}
|
|
|
|
The \keyword{pass} statement does nothing.
|
|
It can be used when a statement is required syntactically but the
|
|
program requires no action.
|
|
For example:
|
|
|
|
\begin{verbatim}
|
|
>>> while 1:
|
|
... pass # Busy-wait for keyboard interrupt
|
|
...
|
|
\end{verbatim}
|
|
|
|
\section{Defining Functions}
|
|
\label{functions}
|
|
|
|
We can create a function that writes the Fibonacci series to an
|
|
arbitrary boundary:
|
|
|
|
\begin{verbatim}
|
|
>>> def fib(n): # write Fibonacci series up to n
|
|
... "Print a 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}
|
|
|
|
The keyword \keyword{def} introduces a function \emph{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
|
|
start at the next line, indented by a tab stop. The first statement
|
|
of the function body can optionally be a string literal; this string
|
|
literal is the function's documentation string, or \dfn{docstring}.
|
|
There are tools which use docstrings to automatically produce printed
|
|
documentation, or to let the user interactively browse through code;
|
|
it's good practice to include docstrings in code that you write, so
|
|
try to make a habit of it.
|
|
|
|
The \emph{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 a value within a
|
|
function (unless named in a \keyword{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 \emph{call by value}.%
|
|
\footnote{
|
|
Actually, \emph{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:
|
|
|
|
\begin{verbatim}
|
|
>>> fib
|
|
<function object at 10042ed0>
|
|
>>> f = fib
|
|
>>> f(100)
|
|
1 1 2 3 5 8 13 21 34 55 89
|
|
\end{verbatim}
|
|
|
|
You might object that \code{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 \code{None} (it's a
|
|
built-in name). Writing the value \code{None} is normally suppressed by
|
|
the interpreter if it would be the only value written. You can see it
|
|
if you really want to:
|
|
|
|
\begin{verbatim}
|
|
>>> print fib(0)
|
|
None
|
|
\end{verbatim}
|
|
|
|
It is simple to write a function that returns a list of the numbers of
|
|
the Fibonacci series, instead of printing it:
|
|
|
|
\begin{verbatim}
|
|
>>> def fib2(n): # return Fibonacci series up to n
|
|
... "Return a list containing the 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}
|
|
%
|
|
This example, as usual, demonstrates some new Python features:
|
|
|
|
\begin{itemize}
|
|
|
|
\item
|
|
The \keyword{return} statement returns with a value from a function.
|
|
\keyword{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 \code{None} value is returned.
|
|
|
|
\item
|
|
The statement \code{result.append(b)} calls a \emph{method} of the list
|
|
object \code{result}. A method is a function that `belongs' to an
|
|
object and is named \code{obj.methodname}, where \code{obj} is some
|
|
object (this may be an expression), and \code{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 \emph{classes}, as discussed later
|
|
in this tutorial.)
|
|
The method \method{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 \samp{result = result + [b]}, but more
|
|
efficient.
|
|
|
|
\end{itemize}
|
|
|
|
\section{More on Defining Functions}
|
|
\label{defining}
|
|
|
|
It is also possible to define functions with a variable number of
|
|
arguments. There are three forms, which can be combined.
|
|
|
|
\subsection{Default Argument Values}
|
|
\label{defaultArgs}
|
|
|
|
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:
|
|
\code{ask_ok('Do you really want to quit?')} or like this:
|
|
\code{ask_ok('OK to overwrite the file?', 2)}.
|
|
|
|
The default values are evaluated at the point of function definition
|
|
in the \emph{defining} scope, so that e.g.
|
|
|
|
\begin{verbatim}
|
|
i = 5
|
|
def f(arg = i): print arg
|
|
i = 6
|
|
f()
|
|
\end{verbatim}
|
|
|
|
will print \code{5}.
|
|
|
|
\subsection{Keyword Arguments}
|
|
\label{keywordArgs}
|
|
|
|
Functions can also be called using
|
|
keyword arguments of the form \samp{\var{keyword} = \var{value}}. For
|
|
instance, the following function:
|
|
|
|
\begin{verbatim}
|
|
def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
|
|
print "-- This parrot wouldn't", action,
|
|
print "if you put", voltage, "Volts through it."
|
|
print "-- Lovely plumage, the", type
|
|
print "-- It's", state, "!"
|
|
\end{verbatim}
|
|
|
|
could be called in any of the following ways:
|
|
|
|
\begin{verbatim}
|
|
parrot(1000)
|
|
parrot(action = 'VOOOOOM', voltage = 1000000)
|
|
parrot('a thousand', state = 'pushing up the daisies')
|
|
parrot('a million', 'bereft of life', 'jump')
|
|
\end{verbatim}
|
|
|
|
but the following calls would all be invalid:
|
|
|
|
\begin{verbatim}
|
|
parrot() # required argument missing
|
|
parrot(voltage=5.0, 'dead') # non-keyword argument following keyword
|
|
parrot(110, voltage=220) # duplicate value for argument
|
|
parrot(actor='John Cleese') # unknown keyword
|
|
\end{verbatim}
|
|
|
|
In general, an argument list must have any positional arguments
|
|
followed by any keyword arguments, where the keywords must be chosen
|
|
from the formal parameter names. It's not important whether a formal
|
|
parameter has a default value or not. No argument must receive a
|
|
value more than once --- formal parameter names corresponding to
|
|
positional arguments cannot be used as keywords in the same calls.
|
|
|
|
When a final formal parameter of the form \code{**\var{name}} is
|
|
present, it receives a dictionary containing all keyword arguments
|
|
whose keyword doesn't correspond to a formal parameter. This may be
|
|
combined with a formal parameter of the form \code{*\var{name}}
|
|
(described in the next subsection) which receives a tuple containing
|
|
the positional arguments beyond the formal parameter list.
|
|
(\code{*\var{name}} must occur before \code{**\var{name}}.) For
|
|
example, if we define a function like this:
|
|
|
|
\begin{verbatim}
|
|
def cheeseshop(kind, *arguments, **keywords):
|
|
print "-- Do you have any", kind, '?'
|
|
print "-- I'm sorry, we're all out of", kind
|
|
for arg in arguments: print arg
|
|
print '-'*40
|
|
for kw in keywords.keys(): print kw, ':', keywords[kw]
|
|
\end{verbatim}
|
|
|
|
It could be called like this:
|
|
|
|
\begin{verbatim}
|
|
cheeseshop('Limburger', "It's very runny, sir.",
|
|
"It's really very, VERY runny, sir.",
|
|
client='John Cleese',
|
|
shopkeeper='Michael Palin',
|
|
sketch='Cheese Shop Sketch')
|
|
\end{verbatim}
|
|
|
|
and of course it would print:
|
|
|
|
\begin{verbatim}
|
|
-- Do you have any Limburger ?
|
|
-- I'm sorry, we're all out of Limburger
|
|
It's very runny, sir.
|
|
It's really very, VERY runny, sir.
|
|
----------------------------------------
|
|
client : John Cleese
|
|
shopkeeper : Michael Palin
|
|
sketch : Cheese Shop Sketch
|
|
\end{verbatim}
|
|
|
|
\subsection{Arbitrary Argument Lists}
|
|
\label{arbitraryArgs}
|
|
|
|
Finally, the least frequently used option is 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.
|
|
|
|
\begin{verbatim}
|
|
def fprintf(file, format, *args):
|
|
file.write(format % args)
|
|
\end{verbatim}
|
|
|
|
|
|
\subsection{Lambda Forms}
|
|
\label{lambda}
|
|
|
|
By popular demand, a few features commonly found in functional
|
|
programming languages and Lisp have been added to Python. With the
|
|
\keyword{lambda} keyword, small anonymous functions can be created.
|
|
Here's a function that returns the sum of its two arguments:
|
|
\samp{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{Documentation Strings}
|
|
\label{docstrings}
|
|
|
|
There are emerging conventions about the content and formatting of
|
|
documentation strings.
|
|
|
|
The first line should always be a short, concise summary of the
|
|
object's purpose. For brevity, it should not explicitly state the
|
|
object's name or type, since these are available by other means
|
|
(except if the name happens to be a verb describing a function's
|
|
operation). This line should begin with a capital letter and end with
|
|
a period.
|
|
|
|
If there are more lines in the documentation string, the second line
|
|
should be blank, visually separating the summary from the rest of the
|
|
description. The following lines should be one of more of paragraphs
|
|
describing the objects calling conventions, its side effects, etc.
|
|
|
|
The Python parser does not strip indentation from multi-line string
|
|
literals in Python, so tools that process documentation have to strip
|
|
indentation. This is done using the following convention. The first
|
|
non-blank line \emph{after} the first line of the string determines the
|
|
amount of indentation for the entire documentation string. (We can't
|
|
use the first line since it is generally adjacent to the string's
|
|
opening quotes so its indentation is not apparent in the string
|
|
literal.) Whitespace ``equivalent'' to this indentation is then
|
|
stripped from the start of all lines of the string. Lines that are
|
|
indented less should not occur, but if they occur all their leading
|
|
whitespace should be stripped. Equivalence of whitespace should be
|
|
tested after expansion of tabs (to 8 spaces, normally).
|
|
|
|
|
|
|
|
\chapter{Data Structures}
|
|
\label{structures}
|
|
|
|
This chapter describes some things you've learned about already in
|
|
more detail, and adds some new things as well.
|
|
|
|
\section{More on Lists}
|
|
\label{moreLists}
|
|
|
|
The list data type has some more methods. Here are all of the methods
|
|
of list objects:
|
|
|
|
\begin{description}
|
|
|
|
\item[\code{insert(i, x)}]
|
|
Insert an item at a given position. The first argument is the index of
|
|
the element before which to insert, so \code{a.insert(0, x)} inserts at
|
|
the front of the list, and \code{a.insert(len(a), x)} is equivalent to
|
|
\code{a.append(x)}.
|
|
|
|
\item[\code{append(x)}]
|
|
Equivalent to \code{a.insert(len(a), x)}.
|
|
|
|
\item[\code{index(x)}]
|
|
Return the index in the list of the first item whose value is \code{x}.
|
|
It is an error if there is no such item.
|
|
|
|
\item[\code{remove(x)}]
|
|
Remove the first item from the list whose value is \code{x}.
|
|
It is an error if there is no such item.
|
|
|
|
\item[\code{sort()}]
|
|
Sort the items of the list, in place.
|
|
|
|
\item[\code{reverse()}]
|
|
Reverse the elements of the list, in place.
|
|
|
|
\item[\code{count(x)}]
|
|
Return the number of times \code{x} appears in the list.
|
|
|
|
\end{description}
|
|
|
|
An example that uses all list methods:
|
|
|
|
\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}
|
|
|
|
\subsection{Functional Programming Tools}
|
|
\label{functional}
|
|
|
|
There are three built-in functions that are very useful when used with
|
|
lists: \function{filter()}, \function{map()}, and \function{reduce()}.
|
|
|
|
\samp{filter(\var{function}, \var{sequence})} returns a sequence (of
|
|
the same type, if possible) consisting of those items from the
|
|
sequence for which \code{\var{function}(\var{item})} is true. For
|
|
example, to compute some primes:
|
|
|
|
\begin{verbatim}
|
|
>>> def f(x): return x%2 != 0 and x%3 != 0
|
|
...
|
|
>>> filter(f, range(2, 25))
|
|
[5, 7, 11, 13, 17, 19, 23]
|
|
\end{verbatim}
|
|
|
|
\samp{map(\var{function}, \var{sequence})} calls
|
|
\code{\var{function}(\var{item})} for each of the sequence's items and
|
|
returns a list of the return values. For example, to compute some
|
|
cubes:
|
|
|
|
\begin{verbatim}
|
|
>>> def cube(x): return x*x*x
|
|
...
|
|
>>> map(cube, 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 \code{None} if some sequence
|
|
is shorter than another). If \code{None} is passed for the function,
|
|
a function returning its argument(s) is substituted.
|
|
|
|
Combining these two special cases, we see that
|
|
\samp{map(None, \var{list1}, \var{list2})} is a convenient way of
|
|
turning a pair of lists into a list of pairs. For example:
|
|
|
|
\begin{verbatim}
|
|
>>> seq = range(8)
|
|
>>> def square(x): return x*x
|
|
...
|
|
>>> map(None, seq, map(square, seq))
|
|
[(0, 0), (1, 1), (2, 4), (3, 9), (4, 16), (5, 25), (6, 36), (7, 49)]
|
|
\end{verbatim}
|
|
|
|
\samp{reduce(\var{func}, \var{sequence})} returns a single value
|
|
constructed by calling the binary function \var{func} 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}
|
|
>>> def add(x,y): return x+y
|
|
...
|
|
>>> reduce(add, 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):
|
|
... def add(x,y): return x+y
|
|
... return reduce(add, seq, 0)
|
|
...
|
|
>>> sum(range(1, 11))
|
|
55
|
|
>>> sum([])
|
|
0
|
|
\end{verbatim}
|
|
|
|
\section{The \keyword{del} statement}
|
|
\label{del}
|
|
|
|
There is a way to remove an item from a list given its index instead
|
|
of its value: the \code{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:
|
|
|
|
\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}
|
|
|
|
\keyword{del} can also be used to delete entire variables:
|
|
|
|
\begin{verbatim}
|
|
>>> del a
|
|
\end{verbatim}
|
|
|
|
Referencing the name \code{a} hereafter is an error (at least until
|
|
another value is assigned to it). We'll find other uses for
|
|
\keyword{del} later.
|
|
|
|
\section{Tuples and Sequences}
|
|
\label{tuples}
|
|
|
|
We saw that lists and strings have many common properties, e.g.,
|
|
indexing and slicing operations. They are two examples of
|
|
\emph{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 \emph{tuple}.
|
|
|
|
A tuple consists of a number of values separated by commas, for
|
|
instance:
|
|
|
|
\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}
|
|
|
|
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:
|
|
|
|
\begin{verbatim}
|
|
>>> empty = ()
|
|
>>> singleton = 'hello', # <-- note trailing comma
|
|
>>> len(empty)
|
|
0
|
|
>>> len(singleton)
|
|
1
|
|
>>> singleton
|
|
('hello',)
|
|
\end{verbatim}
|
|
|
|
The statement \code{t = 12345, 54321, 'hello!'} is an example of
|
|
\emph{tuple packing}: the values \code{12345}, \code{54321} and
|
|
\code{'hello!'} are packed together in a tuple. The reverse operation
|
|
is also possible, e.g.:
|
|
|
|
\begin{verbatim}
|
|
>>> x, y, z = t
|
|
\end{verbatim}
|
|
|
|
This is called, appropriately enough, \emph{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: \emph{list
|
|
unpacking}. This is supported by enclosing the list of variables in
|
|
square brackets:
|
|
|
|
\begin{verbatim}
|
|
>>> a = ['spam', 'eggs', 100, 1234]
|
|
>>> [a1, a2, a3, a4] = a
|
|
\end{verbatim}
|
|
|
|
\section{Dictionaries}
|
|
\label{dictionaries}
|
|
|
|
Another useful data type built into Python is the \emph{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 \emph{keys},
|
|
which can be any non-mutable type; strings and numbers can always be
|
|
keys. Tuples can be used as keys if they contain only strings,
|
|
numbers, or tuples. You can't use lists as keys, since lists can be
|
|
modified in place using their \code{append()} method.
|
|
|
|
It is best to think of a dictionary as an unordered set of
|
|
\emph{key:value} pairs, with the requirement that the keys are unique
|
|
(within one dictionary).
|
|
A pair of braces creates an empty dictionary: \code{\{\}}.
|
|
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 \code{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 \code{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 \code{sort()} method to the list of keys). To check
|
|
whether a single key is in the dictionary, use the \code{has_key()}
|
|
method of the dictionary.
|
|
|
|
Here is a small example using a dictionary:
|
|
|
|
\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}
|
|
|
|
\section{More on Conditions}
|
|
\label{conditions}
|
|
|
|
The conditions used in \code{while} and \code{if} statements above can
|
|
contain other operators besides comparisons.
|
|
|
|
The comparison operators \code{in} and \code{not in} check whether a value
|
|
occurs (does not occur) in a sequence. The operators \code{is} and
|
|
\code{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., \code{a < b == c} tests whether \code{a}
|
|
is less than \code{b} and moreover \code{b} equals \code{c}.
|
|
|
|
Comparisons may be combined by the Boolean operators \code{and} and
|
|
\code{or}, and the outcome of a comparison (or of any other Boolean
|
|
expression) may be negated with \code{not}. These all have lower
|
|
priorities than comparison operators again; between them, \code{not} has
|
|
the highest priority, and \code{or} the lowest, so that
|
|
\code{A and not B or C} is equivalent to \code{(A and (not B)) or C}. Of
|
|
course, parentheses can be used to express the desired composition.
|
|
|
|
The Boolean operators \code{and} and \code{or} are so-called
|
|
\emph{shortcut} operators: their arguments are evaluated from left to
|
|
right, and evaluation stops as soon as the outcome is determined.
|
|
E.g., if \code{A} and \code{C} are true but \code{B} is false, \code{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,
|
|
|
|
\begin{verbatim}
|
|
>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
|
|
>>> non_null = string1 or string2 or string3
|
|
>>> non_null
|
|
'Trondheim'
|
|
\end{verbatim}
|
|
|
|
Note that in Python, unlike \C{}, assignment cannot occur inside expressions.
|
|
|
|
\section{Comparing Sequences and Other Types}
|
|
\label{comparing}
|
|
|
|
Sequence objects may be compared to other objects with the same
|
|
sequence type. The comparison uses \emph{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:
|
|
|
|
\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}
|
|
|
|
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}
|
|
\label{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 running it with that file as input instead. This is known as creating a
|
|
\emph{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 \emph{module}; definitions from a module can be
|
|
\emph{imported} into other modules or into the \emph{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 \file{.py} appended. Within
|
|
a module, the module's name (as a string) is available as the value of
|
|
the global variable \code{__name__}. For instance, use your favorite text
|
|
editor to create a file called \file{fibo.py} in the current directory
|
|
with the following contents:
|
|
|
|
\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}
|
|
|
|
Now enter the Python interpreter and import this module with the
|
|
following command:
|
|
|
|
\begin{verbatim}
|
|
>>> import fibo
|
|
\end{verbatim}
|
|
|
|
This does not enter the names of the functions defined in
|
|
\code{fibo}
|
|
directly in the current symbol table; it only enters the module name
|
|
\code{fibo}
|
|
there.
|
|
Using the module name you can access the functions:
|
|
|
|
\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}
|
|
%
|
|
If you intend to use a function often you can assign it to a local name:
|
|
|
|
\begin{verbatim}
|
|
>>> fib = fibo.fib
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
\end{verbatim}
|
|
|
|
|
|
\section{More on Modules}
|
|
\label{moreModules}
|
|
|
|
A module can contain executable statements as well as function
|
|
definitions.
|
|
These statements are intended to initialize the module.
|
|
They are executed only the
|
|
\emph{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,
|
|
\code{modname.itemname}.
|
|
|
|
Modules can import other modules.
|
|
It is customary but not required to place all
|
|
\code{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
|
|
\code{import}
|
|
statement that imports names from a module directly into the importing
|
|
module's symbol table.
|
|
For example:
|
|
|
|
\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}
|
|
|
|
This does not introduce the module name from which the imports are taken
|
|
in the local symbol table (so in the example, \code{fibo} is not
|
|
defined).
|
|
|
|
There is even a variant to import all names that a module defines:
|
|
|
|
\begin{verbatim}
|
|
>>> from fibo import *
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
\end{verbatim}
|
|
|
|
This imports all names except those beginning with an underscore
|
|
(\code{_}).
|
|
|
|
\subsection{The Module Search Path}
|
|
\label{searchPath}
|
|
|
|
\indexiii{module}{search}{path}
|
|
When a module named \module{spam} is imported, the interpreter searches
|
|
for a file named \file{spam.py} in the current directory,
|
|
and then in the list of directories specified by
|
|
the environment variable \envvar{PYTHONPATH}. This has the same syntax as
|
|
the shell variable \envvar{PATH}, i.e., a list of
|
|
directory names. When \envvar{PYTHONPATH} is not set, or when the file
|
|
is not found there, the search continues in an installation-dependent
|
|
default path; on \UNIX{}, this is usually \file{.:/usr/local/lib/python}.
|
|
|
|
Actually, modules are searched in the list of directories given by the
|
|
variable \code{sys.path} which is initialized from the directory
|
|
containing the input script (or the current directory),
|
|
\envvar{PYTHONPATH} and the installation-dependent default. This allows
|
|
Python programs that know what they're doing to modify or replace the
|
|
module search path. See the section on Standard Modules later.
|
|
|
|
\subsection{``Compiled'' Python files}
|
|
|
|
As an important speed-up of the start-up time for short programs that
|
|
use a lot of standard modules, if a file called \file{spam.pyc} exists
|
|
in the directory where \file{spam.py} is found, this is assumed to
|
|
contain an already-``compiled'' version of the module \module{spam}.
|
|
The modification time of the version of \file{spam.py} used to create
|
|
\file{spam.pyc} is recorded in \file{spam.pyc}, and the file is
|
|
ignored if these don't match.
|
|
|
|
Normally, you don't need to do anything to create the \file{spam.pyc} file.
|
|
Whenever \file{spam.py} is successfully compiled, an attempt is made to
|
|
write the compiled version to \file{spam.pyc}. It is not an error if
|
|
this attempt fails; if for any reason the file is not written
|
|
completely, the resulting \file{spam.pyc} file will be recognized as
|
|
invalid and thus ignored later. The contents of the \file{spam.pyc}
|
|
file is platform independent, so a Python module directory can be
|
|
shared by machines of different architectures. (Tip for experts:
|
|
the module \module{compileall}\refstmodindex{compileall} creates
|
|
\file{.pyc} files for all modules.)
|
|
|
|
% XXX Should optimization with -O be covered here?
|
|
|
|
\section{Standard Modules}
|
|
\label{standardModules}
|
|
|
|
Python comes with a library of standard modules, described in a separate
|
|
document, the \emph{Python Library Reference} (``Library Reference''
|
|
hereafter). 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
|
|
\module{amoeba} module is only provided on systems that somehow
|
|
support Amoeba primitives. One particular module deserves some
|
|
attention: \module{sys}\refstmodindex{sys}, which is built into every
|
|
Python interpreter. The variables \code{sys.ps1} and \code{sys.ps2}
|
|
define the strings used as primary and secondary prompts:
|
|
|
|
\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.ps1
|
|
'>>> '
|
|
>>> sys.ps2
|
|
'... '
|
|
>>> sys.ps1 = 'C> '
|
|
C> print 'Yuck!'
|
|
Yuck!
|
|
C>
|
|
\end{verbatim}
|
|
|
|
These two variables are only defined if the interpreter is in
|
|
interactive mode.
|
|
|
|
The variable
|
|
\code{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
|
|
\envvar{PYTHONPATH}, or from a built-in default if \envvar{PYTHONPATH}
|
|
is not set. You can modify it using standard list operations, e.g.:
|
|
|
|
\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.path.append('/ufs/guido/lib/python')
|
|
\end{verbatim}
|
|
|
|
\section{The \function{dir()} Function}
|
|
\label{dir}
|
|
|
|
The built-in function \function{dir()} is used to find out which names
|
|
a module defines. It returns a sorted list of strings:
|
|
|
|
\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}
|
|
|
|
Without arguments, \function{dir()} lists the names you have defined
|
|
currently:
|
|
|
|
\begin{verbatim}
|
|
>>> a = [1, 2, 3, 4, 5]
|
|
>>> import fibo, sys
|
|
>>> fib = fibo.fib
|
|
>>> dir()
|
|
['__name__', 'a', 'fib', 'fibo', 'sys']
|
|
\end{verbatim}
|
|
|
|
Note that it lists all types of names: variables, modules, functions, etc.
|
|
|
|
\function{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 \module{__builtin__}\refbimodindex{__builtin__}:
|
|
|
|
\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}
|
|
|
|
|
|
\chapter{Input and Output}
|
|
\label{io}
|
|
|
|
There are several ways to present the output of a program; data can be
|
|
printed in a human-readable form, or written to a file for future use.
|
|
This chapter will discuss some of the possibilities.
|
|
|
|
\section{Fancier Output Formatting}
|
|
So far we've encountered two ways of writing values: \emph{expression
|
|
statements} and the \keyword{print} statement. (A third way is using
|
|
the \method{write()} method of file objects; the standard output file
|
|
can be referenced as \code{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. There are two ways to format
|
|
your output; the first way 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
|
|
\module{string}\refstmodindex{string} contains some useful operations
|
|
for padding strings to a given column width;
|
|
these will be discussed shortly. The second way is to use the
|
|
\code{\%} operator with a string as the left argument. \code{\%}
|
|
interprets the left argument as a \C{} \cfunction{sprintf()}-style
|
|
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: pass it to
|
|
the \function{repr()} function, or just write the value between
|
|
reverse quotes (\code{``}). Some examples:
|
|
|
|
\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 = repr(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, ('spam', 'eggs')`
|
|
"(31.4, 40000, ('spam', 'eggs'))"
|
|
\end{verbatim}
|
|
|
|
Here are two ways to write a table of squares and cubes:
|
|
|
|
\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}
|
|
|
|
(Note that one space between each column was added by the way
|
|
\keyword{print} works: it always adds spaces between its arguments.)
|
|
|
|
This example demonstrates the function \function{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
|
|
\function{string.ljust()} and \function{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
|
|
\samp{string.ljust(x,~n)[0:n]}.)
|
|
|
|
There is another function, \function{string.zfill()}, which pads a
|
|
numeric string on the left with zeros. It understands about plus and
|
|
minus signs:
|
|
|
|
\begin{verbatim}
|
|
>>> string.zfill('12', 5)
|
|
'00012'
|
|
>>> string.zfill('-3.14', 7)
|
|
'-003.14'
|
|
>>> string.zfill('3.14159265359', 5)
|
|
'3.14159265359'
|
|
\end{verbatim}
|
|
%
|
|
Using the \code{\%} operator looks like this:
|
|
|
|
\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
|
|
\function{str()} built-in function. Using \code{*} 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.
|
|
|
|
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
|
|
\function{vars()} function, which returns a dictionary containing all
|
|
local variables.
|
|
|
|
\section{Reading and Writing Files}
|
|
\label{files}
|
|
|
|
% Opening files
|
|
\function{open()}\bifuncindex{open} returns a file
|
|
object\obindex{file}, and is most commonly used with two arguments:
|
|
\samp{open(\var{filename}, \var{mode})}.
|
|
|
|
\begin{verbatim}
|
|
>>> f=open('/tmp/workfile', 'w')
|
|
>>> print f
|
|
<open file '/tmp/workfile', mode 'w' at 80a0960>
|
|
\end{verbatim}
|
|
|
|
The first argument is a string containing the filename. The second
|
|
argument is another string containing a few characters describing the
|
|
way in which the file will be used. \var{mode} can be \code{'r'} when
|
|
the file will only be read, \code{'w'} for only writing (an existing
|
|
file with the same name will be erased), and \code{'a'} opens the file
|
|
for appending; any data written to the file is automatically added to
|
|
the end. \code{'r+'} opens the file for both reading and writing.
|
|
The \var{mode} argument is optional; \code{'r'} will be assumed if
|
|
it's omitted.
|
|
|
|
On Windows and the Macintosh, \code{'b'} appended to the
|
|
mode opens the file in binary mode, so there are also modes like
|
|
\code{'rb'}, \code{'wb'}, and \code{'r+b'}. Windows makes a
|
|
distinction between text and binary files; the end-of-line characters
|
|
in text files are automatically altered slightly when data is read or
|
|
written. This behind-the-scenes modification to file data is fine for
|
|
\ASCII{} text files, but it'll corrupt binary data like that in JPEGs or
|
|
\file{.EXE} files. Be very careful to use binary mode when reading and
|
|
writing such files. (Note that the precise semantics of text mode on
|
|
the Macintosh depends on the underlying \C{} library being used.)
|
|
|
|
\subsection{Methods of File Objects}
|
|
\label{fileMethods}
|
|
|
|
The rest of the examples in this section will assume that a file
|
|
object called \code{f} has already been created.
|
|
|
|
To read a file's contents, call \code{f.read(\var{size})}, which reads
|
|
some quantity of data and returns it as a string. \var{size} is an
|
|
optional numeric argument. When \var{size} is omitted or negative,
|
|
the entire contents of the file will be read and returned; it's your
|
|
problem if the file is twice as large as your machine's memory.
|
|
Otherwise, at most \var{size} bytes are read and returned. If the end
|
|
of the file has been reached, \code{f.read()} will return an empty
|
|
string (\code {""}).
|
|
\begin{verbatim}
|
|
>>> f.read()
|
|
'This is the entire file.\012'
|
|
>>> f.read()
|
|
''
|
|
\end{verbatim}
|
|
|
|
\code{f.readline()} reads a single line from the file; a newline
|
|
character (\code{\e n}) is left at the end of the string, and is only
|
|
omitted on the last line of the file if the file doesn't end in a
|
|
newline. This makes the return value unambiguous; if
|
|
\code{f.readline()} returns an empty string, the end of the file has
|
|
been reached, while a blank line is represented by \code{'\e n'}, a
|
|
string containing only a single newline.
|
|
|
|
\begin{verbatim}
|
|
>>> f.readline()
|
|
'This is the first line of the file.\012'
|
|
>>> f.readline()
|
|
'Second line of the file\012'
|
|
>>> f.readline()
|
|
''
|
|
\end{verbatim}
|
|
|
|
\code{f.readlines()} uses \code{f.readline()} repeatedly, and returns
|
|
a list containing all the lines of data in the file.
|
|
|
|
\begin{verbatim}
|
|
>>> f.readlines()
|
|
['This is the first line of the file.\012', 'Second line of the file\012']
|
|
\end{verbatim}
|
|
|
|
\code{f.write(\var{string})} writes the contents of \var{string} to
|
|
the file, returning \code{None}.
|
|
|
|
\begin{verbatim}
|
|
>>> f.write('This is a test\n')
|
|
\end{verbatim}
|
|
|
|
\code{f.tell()} returns an integer giving the file object's current
|
|
position in the file, measured in bytes from the beginning of the
|
|
file. To change the file object's position, use
|
|
\samp{f.seek(\var{offset}, \var{from_what})}. The position is
|
|
computed from adding \var{offset} to a reference point; the reference
|
|
point is selected by the \var{from_what} argument. A \var{from_what}
|
|
value of 0 measures from the beginning of the file, 1 uses the current
|
|
file position, and 2 uses the end of the file as the reference point.
|
|
\var{from_what} can be omitted and defaults to 0, using the beginning
|
|
of the file as the reference point.
|
|
|
|
\begin{verbatim}
|
|
>>> f=open('/tmp/workfile', 'r+')
|
|
>>> f.write('0123456789abcdef')
|
|
>>> f.seek(5) # Go to the 5th byte in the file
|
|
>>> f.read(1)
|
|
'5'
|
|
>>> f.seek(-3, 2) # Go to the 3rd byte before the end
|
|
>>> f.read(1)
|
|
'd'
|
|
\end{verbatim}
|
|
|
|
When you're done with a file, call \code{f.close()} to close it and
|
|
free up any system resources taken up by the open file. After calling
|
|
\code{f.close()}, attempts to use the file object will automatically fail.
|
|
|
|
\begin{verbatim}
|
|
>>> f.close()
|
|
>>> f.read()
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1, in ?
|
|
ValueError: I/O operation on closed file
|
|
\end{verbatim}
|
|
|
|
File objects have some additional methods, such as \method{isatty()}
|
|
and \method{truncate()} which are less frequently used; consult the
|
|
Library Reference for a complete guide to file objects.
|
|
|
|
\subsection{The \module{pickle} Module}
|
|
\label{pickle}
|
|
\refstmodindex{pickle}
|
|
|
|
Strings can easily be written to and read from a file. Numbers take a
|
|
bit more effort, since the \method{read()} method only returns
|
|
strings, which will have to be passed to a function like
|
|
\function{string.atoi()}, which takes a string like \code{'123'} and
|
|
returns its numeric value 123. However, when you want to save more
|
|
complex data types like lists, dictionaries, or class instances,
|
|
things get a lot more complicated.
|
|
|
|
Rather than have users be constantly writing and debugging code to
|
|
save complicated data types, Python provides a standard module called
|
|
\module{pickle}. This is an amazing module that can take almost
|
|
any Python object (even some forms of Python code!), and convert it to
|
|
a string representation; this process is called \dfn{pickling}.
|
|
Reconstructing the object from the string representation is called
|
|
\dfn{unpickling}. Between pickling and unpickling, the string
|
|
representing the object may have been stored in a file or data, or
|
|
sent over a network connection to some distant machine.
|
|
|
|
If you have an object \code{x}, and a file object \code{f} that's been
|
|
opened for writing, the simplest way to pickle the object takes only
|
|
one line of code:
|
|
|
|
\begin{verbatim}
|
|
pickle.dump(x, f)
|
|
\end{verbatim}
|
|
|
|
To unpickle the object again, if \code{f} is a file object which has
|
|
been opened for reading:
|
|
|
|
\begin{verbatim}
|
|
x = pickle.load(f)
|
|
\end{verbatim}
|
|
|
|
(There are other variants of this, used when pickling many objects or
|
|
when you don't want to write the pickled data to a file; consult the
|
|
complete documentation for \module{pickle} in the Library Reference.)
|
|
|
|
\module{pickle} is the standard way to make Python objects which can be
|
|
stored and reused by other programs or by a future invocation of the
|
|
same program; the technical term for this is a \dfn{persistent}
|
|
object. Because \module{pickle} is so widely used, many authors who
|
|
write Python extensions take care to ensure that new data types such
|
|
as matrices can be properly pickled and unpickled.
|
|
|
|
|
|
|
|
\chapter{Errors and Exceptions}
|
|
\label{errors}
|
|
|
|
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: \emph{syntax errors}
|
|
and \emph{exceptions}.
|
|
|
|
\section{Syntax Errors}
|
|
\label{syntaxErrors}
|
|
|
|
Syntax errors, also known as parsing errors, are perhaps the most common
|
|
kind of complaint you get while you are still learning Python:
|
|
|
|
\begin{verbatim}
|
|
>>> while 1 print 'Hello world'
|
|
File "<stdin>", line 1
|
|
while 1 print 'Hello world'
|
|
^
|
|
SyntaxError: invalid syntax
|
|
\end{verbatim}
|
|
|
|
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
|
|
\emph{preceding}
|
|
the arrow: in the example, the error is detected at the keyword
|
|
\keyword{print}, since a colon (\character{:}) 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}
|
|
\label{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 \emph{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:
|
|
|
|
\begin{verbatim}
|
|
>>> 10 * (1/0)
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
ZeroDivisionError: integer division or modulo
|
|
>>> 4 + spam*3
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
NameError: spam
|
|
>>> '2' + 2
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
TypeError: illegal argument type for built-in operation
|
|
\end{verbatim}
|
|
|
|
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
|
|
\exception{ZeroDivisionError},
|
|
\exception{NameError}
|
|
and
|
|
\exception{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 Library Reference lists the built-in exceptions and their
|
|
meanings.
|
|
|
|
\section{Handling Exceptions}
|
|
\label{handling}
|
|
|
|
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:
|
|
|
|
\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}
|
|
|
|
The \keyword{try} statement works as follows.
|
|
\begin{itemize}
|
|
\item
|
|
First, the \emph{try clause}
|
|
(the statement(s) between the \keyword{try} and \keyword{except}
|
|
keywords) is executed.
|
|
\item
|
|
If no exception occurs, the
|
|
\emph{except\ clause}
|
|
is skipped and execution of the \keyword{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 \keyword{except} keyword, the rest of the
|
|
try clause is skipped, the except clause is executed, and then
|
|
execution continues after the \keyword{try} statement.
|
|
\item
|
|
If an exception occurs which does not match the exception named in the
|
|
except clause, it is passed on to outer \keyword{try} statements; if
|
|
no handler is found, it is an \emph{unhandled exception}
|
|
and execution stops with a message as shown above.
|
|
\end{itemize}
|
|
A \keyword{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 \keyword{try} statement.
|
|
An except clause may name multiple exceptions as a parenthesized list,
|
|
e.g.:
|
|
|
|
\begin{verbatim}
|
|
... except (RuntimeError, TypeError, NameError):
|
|
... pass
|
|
\end{verbatim}
|
|
|
|
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!
|
|
|
|
The \keyword{try} \ldots\ \keyword{except} statement has an optional
|
|
\emph{else clause}, which must follow all except clauses. It is
|
|
useful to place code that must be executed if the 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}
|
|
|
|
|
|
When an exception occurs, it may have an associated value, also known as
|
|
the exceptions's \emph{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:
|
|
|
|
\begin{verbatim}
|
|
>>> try:
|
|
... spam()
|
|
... except NameError, x:
|
|
... print 'name', x, 'undefined'
|
|
...
|
|
name spam undefined
|
|
\end{verbatim}
|
|
|
|
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:
|
|
|
|
\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}
|
|
|
|
|
|
\section{Raising Exceptions}
|
|
\label{raising}
|
|
|
|
The \keyword{raise} statement allows the programmer to force a
|
|
specified exception to occur.
|
|
For example:
|
|
|
|
\begin{verbatim}
|
|
>>> raise NameError, 'HiThere'
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 1
|
|
NameError: HiThere
|
|
\end{verbatim}
|
|
|
|
The first argument to \keyword{raise} names the exception to be
|
|
raised. The optional second argument specifies the exception's
|
|
argument.
|
|
|
|
|
|
\section{User-defined Exceptions}
|
|
\label{userExceptions}
|
|
|
|
Programs may name their own exceptions by assigning a string to a
|
|
variable.
|
|
For example:
|
|
|
|
\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}
|
|
|
|
Many standard modules use this to report errors that may occur in
|
|
functions they define.
|
|
|
|
|
|
\section{Defining Clean-up Actions}
|
|
\label{cleanup}
|
|
|
|
The \keyword{try} statement has another optional clause which is
|
|
intended to define clean-up actions that must be executed under all
|
|
circumstances. For example:
|
|
|
|
\begin{verbatim}
|
|
>>> try:
|
|
... raise KeyboardInterrupt
|
|
... finally:
|
|
... print 'Goodbye, world!'
|
|
...
|
|
Goodbye, world!
|
|
Traceback (innermost last):
|
|
File "<stdin>", line 2
|
|
KeyboardInterrupt
|
|
\end{verbatim}
|
|
|
|
A \emph{finally clause} is executed whether or not an exception has
|
|
occurred in the try clause. When an exception has occurred, it is
|
|
re-raised after the finally clause is executed. The finally clause is
|
|
also executed ``on the way out'' when the \keyword{try} statement is
|
|
left via a \keyword{break} or \keyword{return} statement.
|
|
|
|
A \keyword{try} statement must either have one or more except clauses
|
|
or one finally clause, but not both.
|
|
|
|
\chapter{Classes}
|
|
\label{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 \Cpp{} 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 or classes, a method can call the method of a base class with the
|
|
same name. Objects can contain an arbitrary amount of private data.
|
|
|
|
In \Cpp{} terminology, all class members (including the data members) are
|
|
\emph{public}, and all member functions are \emph{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 \Cpp{}
|
|
or Modula-3, built-in types cannot be used as base classes for
|
|
extension by the user. Also, like in \Cpp{} but unlike in Modula-3, most
|
|
built-in operators with special syntax (arithmetic operators,
|
|
subscripting etc.) can be redefined for class instances.
|
|
|
|
\section{A Word About Terminology}
|
|
\label{terminology}
|
|
|
|
Lacking universally accepted terminology to talk about classes, I will
|
|
make occasional use of Smalltalk and \Cpp{} terms. (I would use Modula-3
|
|
terms, since its object-oriented semantics are closer to those of
|
|
Python than \Cpp{}, 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 \Cpp{} and Modula-3, and
|
|
unlike Smalltalk, not all types in Python are classes: the basic
|
|
built-in types like integers and lists are not, and even somewhat more
|
|
exotic types like files aren't. However, \emph{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}
|
|
\label{scopes}
|
|
|
|
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 \emph{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 \function{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 thing 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 \emph{attribute} for any name following a
|
|
dot --- for example, in the expression \code{z.real}, \code{real} is
|
|
an attribute of the object \code{z}. Strictly speaking, references to
|
|
names in modules are attribute references: in the expression
|
|
\code{modname.funcname}, \code{modname} is a module object and
|
|
\code{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 \code{__dict__} which returns the dictionary
|
|
used to implement the module's name space; the name
|
|
\code{__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 \samp{modname.the_answer = 42}. Writable attributes may
|
|
also be deleted with the \keyword{del} statement, e.g.
|
|
\samp{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
|
|
\module{__main__}, so they have their own global name space. (The
|
|
built-in names actually also live in a module; this is called
|
|
\module{__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 \emph{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 of functions, 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 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
|
|
\samp{del x} removes the binding of \code{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 \keyword{global} statement can be used to indicate that
|
|
particular variables live in the global scope.)
|
|
|
|
|
|
\section{A First Look at Classes}
|
|
\label{firstClasses}
|
|
|
|
Classes introduce a little bit of new syntax, three new object types,
|
|
and some new semantics.
|
|
|
|
|
|
\subsection{Class Definition Syntax}
|
|
\label{classDefinition}
|
|
|
|
The simplest form of class definition looks like this:
|
|
|
|
\begin{verbatim}
|
|
class ClassName:
|
|
<statement-1>
|
|
.
|
|
.
|
|
.
|
|
<statement-N>
|
|
\end{verbatim}
|
|
|
|
Class definitions, like function definitions (\keyword{def}
|
|
statements) must be executed before they have any effect. (You could
|
|
conceivably place a class definition in a branch of an \keyword{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 \emph{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 the class name given
|
|
in the class definition header (\class{ClassName} in the example).
|
|
|
|
|
|
\subsection{Class Objects}
|
|
\label{classObjects}
|
|
|
|
Class objects support two kinds of operations: attribute references
|
|
and instantiation.
|
|
|
|
\emph{Attribute references} use the standard syntax used for all
|
|
attribute references in Python: \code{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:
|
|
"A simple example class"
|
|
i = 12345
|
|
def f(x):
|
|
return 'hello world'
|
|
\end{verbatim}
|
|
|
|
then \code{MyClass.i} and \code{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 \code{MyClass.i} by assignment. \code{__doc__} is also a valid
|
|
attribute that's read-only, returning the docstring belonging to
|
|
the class: \code{"A simple example class"}).
|
|
|
|
Class \emph{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 \emph{instance} of the class and assigns this object to
|
|
the local variable \code{x}.
|
|
|
|
|
|
\subsection{Instance Objects}
|
|
\label{instanceObjects}
|
|
|
|
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 \emph{data attributes}. These correspond to
|
|
``instance variables'' in Smalltalk, and to ``data members'' in
|
|
\Cpp{}. Data attributes need not be declared; like local variables,
|
|
they spring into existence when they are first assigned to. For
|
|
example, if \code{x} is the instance of \class{MyClass} created above,
|
|
the following piece of code will print the value \code{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 \emph{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, \code{x.f} is a valid method reference, since
|
|
\code{MyClass.f} is a function, but \code{x.i} is not, since
|
|
\code{MyClass.i} is not. But \code{x.f} is not the same thing as
|
|
\code{MyClass.f} --- it is a \emph{method object}, not a function
|
|
object.%
|
|
\obindex{method}
|
|
|
|
|
|
\subsection{Method Objects}
|
|
\label{methodObjects}
|
|
|
|
Usually, a method is called immediately, e.g.:
|
|
|
|
\begin{verbatim}
|
|
x.f()
|
|
\end{verbatim}
|
|
|
|
In our example, this will return the string \code{'hello world'}.
|
|
However, it is not necessary to call a method right away: \code{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 \samp{hello world} until the end of time.
|
|
|
|
What exactly happens when a method is called? You may have noticed
|
|
that \code{x.f()} was called without an argument above, even though
|
|
the function definition for \method{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 \code{x.f()} is exactly equivalent
|
|
to \code{MyClass.f(x)}. In general, calling a method with a list of
|
|
\var{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}
|
|
\label{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
|
|
\code{self}. This is nothing more than a convention: the name
|
|
\code{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 \emph{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 \code{f}, \code{g} and \code{h} are all attributes of class
|
|
\class{C} that refer to function objects, and consequently they are all
|
|
methods of instances of \class{C} --- \code{h} being exactly equivalent
|
|
to \code{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
|
|
\code{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. Therefore a class may define a special method named
|
|
\method{__init__()}, like this:
|
|
|
|
\begin{verbatim}
|
|
def __init__(self):
|
|
self.empty()
|
|
\end{verbatim}
|
|
|
|
When a class defines an \method{__init__()} method, class
|
|
instantiation automatically invokes \method{__init__()} for the
|
|
newly-created class instance. So in the \class{Bag} example, a new
|
|
and initialized instance can be obtained by:
|
|
|
|
\begin{verbatim}
|
|
x = Bag()
|
|
\end{verbatim}
|
|
|
|
Of course, the \method{__init__()} method may have arguments for
|
|
greater flexibility. In that case, arguments given to the class
|
|
instantiation operator are passed on to \method{__init__()}. For
|
|
example,
|
|
|
|
\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}
|
|
|
|
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}
|
|
\label{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 \class{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:
|
|
\code{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 \Cpp{} 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 \samp{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}
|
|
\label{multiple}
|
|
|
|
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
|
|
\class{DerivedClassName}, it is searched in \class{Base1}, then
|
|
(recursively) in the base classes of \class{Base1}, and only if it is
|
|
not found there, it is searched in \class{Base2}, and so on.
|
|
|
|
(To some people breadth first --- searching \class{Base2} and
|
|
\class{Base3} before the base classes of \class{Base1} --- looks more
|
|
natural. However, this would require you to know whether a particular
|
|
attribute of \class{Base1} is actually defined in \class{Base1} or in
|
|
one of its base classes before you can figure out the consequences of
|
|
a name conflict with an attribute of \class{Base2}. The depth-first
|
|
rule makes no differences between direct and inherited attributes of
|
|
\class{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{Private Variables}
|
|
\label{private}
|
|
|
|
There is limited support for class-private
|
|
identifiers. Any identifier of the form \code{__spam} (at least two
|
|
leading underscores, at most one trailing underscore) is now textually
|
|
replaced with \code{_classname__spam}, where \code{classname} is the
|
|
current class name with leading underscore(s) stripped. This mangling
|
|
is done without regard of the syntactic position of the identifier, so
|
|
it can be used to define class-private instance and class variables,
|
|
methods, as well as globals, and even to store instance variables
|
|
private to this class on instances of \emph{other} classes. Truncation
|
|
may occur when the mangled name would be longer than 255 characters.
|
|
Outside classes, or when the class name consists of only underscores,
|
|
no mangling occurs.
|
|
|
|
Name mangling is intended to give classes an easy way to define
|
|
``private'' instance variables and methods, without having to worry
|
|
about instance variables defined by derived classes, or mucking with
|
|
instance variables by code outside the class. Note that the mangling
|
|
rules are designed mostly to avoid accidents; it still is possible for
|
|
a determined soul to access or modify a variable that is considered
|
|
private. This can even be useful, e.g. for the debugger, and that's
|
|
one reason why this loophole is not closed. (Buglet: derivation of a
|
|
class with the same name as the base class makes use of private
|
|
variables of the base class possible.)
|
|
|
|
Notice that code passed to \code{exec}, \code{eval()} or
|
|
\code{evalfile()} does not consider the classname of the invoking
|
|
class to be the current class; this is similar to the effect of the
|
|
\code{global} statement, the effect of which is likewise restricted to
|
|
code that is byte-compiled together. The same restriction applies to
|
|
\code{getattr()}, \code{setattr()} and \code{delattr()}, as well as
|
|
when referencing \code{__dict__} directly.
|
|
|
|
Here's an example of a class that implements its own
|
|
\code{__getattr__} and \code{__setattr__} methods and stores all
|
|
attributes in a private variable, in a way that works in Python 1.4 as
|
|
well as in previous versions:
|
|
|
|
\begin{verbatim}
|
|
class VirtualAttributes:
|
|
__vdict = None
|
|
__vdict_name = locals().keys()[0]
|
|
|
|
def __init__(self):
|
|
self.__dict__[self.__vdict_name] = {}
|
|
|
|
def __getattr__(self, name):
|
|
return self.__vdict[name]
|
|
|
|
def __setattr__(self, name, value):
|
|
self.__vdict[name] = value
|
|
\end{verbatim}
|
|
|
|
%\emph{Warning: this is an experimental feature.} To avoid all
|
|
%potential problems, refrain from using identifiers starting with
|
|
%double underscore except for predefined uses like \code{__init__}. To
|
|
%use private names while maintaining future compatibility: refrain from
|
|
%using the same private name in classes related via subclassing; avoid
|
|
%explicit (manual) mangling/unmangling; and assume that at some point
|
|
%in the future, leading double underscore will revert to being just a
|
|
%naming convention. Discussion on extensive compile-time declarations
|
|
%are currently underway, and it is impossible to predict what solution
|
|
%will eventually be chosen for private names. Double leading
|
|
%underscore is still a candidate, of course --- just not the only one.
|
|
%It is placed in the distribution in the belief that it is useful, and
|
|
%so that widespread experience with its use can be gained. It will not
|
|
%be removed without providing a better solution and a migration path.
|
|
|
|
\section{Odds and Ends}
|
|
\label{odds}
|
|
|
|
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
|
|
\method{read()} and \method{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
|
|
%\code{sys.stdin} will not cause the interpreter to read further input
|
|
%from it.)
|
|
|
|
|
|
Instance method objects have attributes, too: \code{m.im_self} is the
|
|
object of which the method is an instance, and \code{m.im_func} is the
|
|
function object corresponding to the method.
|
|
|
|
\subsection{Exceptions Can Be Classes}
|
|
\label{exceptionClasses}
|
|
|
|
User-defined exceptions are no longer limited to being string objects
|
|
--- they can be identified by classes as well. Using this mechanism it
|
|
is possible to create extensible hierarchies of exceptions.
|
|
|
|
There are two new valid (semantic) forms for the raise statement:
|
|
|
|
\begin{verbatim}
|
|
raise Class, instance
|
|
|
|
raise instance
|
|
\end{verbatim}
|
|
|
|
In the first form, \code{instance} must be an instance of \class{Class}
|
|
or of a class derived from it. The second form is a shorthand for
|
|
|
|
\begin{verbatim}
|
|
raise instance.__class__, instance
|
|
\end{verbatim}
|
|
|
|
An except clause may list classes as well as string objects. A class
|
|
in an except clause is compatible with an exception if it is the same
|
|
class or a base class thereof (but not the other way around --- an
|
|
except clause listing a derived class is not compatible with a base
|
|
class). For example, the following code will print B, C, D in that
|
|
order:
|
|
|
|
\begin{verbatim}
|
|
class B:
|
|
pass
|
|
class C(B):
|
|
pass
|
|
class D(C):
|
|
pass
|
|
|
|
for c in [B, C, D]:
|
|
try:
|
|
raise c()
|
|
except D:
|
|
print "D"
|
|
except C:
|
|
print "C"
|
|
except B:
|
|
print "B"
|
|
\end{verbatim}
|
|
|
|
Note that if the except clauses were reversed (with \samp{except B}
|
|
first), it would have printed B, B, B --- the first matching except
|
|
clause is triggered.
|
|
|
|
When an error message is printed for an unhandled exception which is a
|
|
class, the class name is printed, then a colon and a space, and
|
|
finally the instance converted to a string using the built-in function
|
|
\function{str()}.
|
|
|
|
|
|
\chapter{What Now?}
|
|
\label{whatNow}
|
|
|
|
Hopefully reading this tutorial has reinforced your interest in using
|
|
Python. Now what should you do?
|
|
|
|
You should read, or at least page through, the Library Reference,
|
|
which gives complete (though terse) reference material about types,
|
|
functions, and modules that can save you a lot of time when writing
|
|
Python programs. The standard Python distribution includes a
|
|
\emph{lot} of code in both \C{} and Python; there are modules to read
|
|
\UNIX{} mailboxes, retrieve documents via HTTP, generate random
|
|
numbers, parse command-line options, write CGI programs, compress
|
|
data, and a lot more; skimming through the Library Reference will give
|
|
you an idea of what's available.
|
|
|
|
The major Python Web site is \url{http://www.python.org}; it contains
|
|
code, documentation, and pointers to Python-related pages around the
|
|
Web. This web site is mirrored in various places around the
|
|
world, such as Europe, Japan, and Australia; a mirror may be faster
|
|
than the main site, depending on your geographical location. A more
|
|
informal site is \url{http://starship.skyport.net}, which contains a
|
|
bunch of Python-related personal home pages; many people have
|
|
downloadable software here.
|
|
|
|
For Python-related questions and problem reports, you can post to the
|
|
newsgroup \newsgroup{comp.lang.python}, or send them to the mailing
|
|
list at \email{python-list@cwi.nl}. The newsgroup and mailing list
|
|
are gatewayed, so messages posted to one will automatically be
|
|
forwarded to the other. There are around 35--45 postings a day,
|
|
% Postings figure based on average of last six months activity as
|
|
% reported by www.findmail.com; Oct. '97 - Mar. '98: 7480 msgs / 182
|
|
% days = 41.1 msgs / day.
|
|
asking (and answering) questions, suggesting new features, and
|
|
announcing new modules. Before posting, be sure to check the list of
|
|
Frequently Asked Questions (also called the FAQ), at
|
|
\url{http://www.python.org/doc/FAQ.html}, or look for it in the
|
|
\file{Misc/} directory of the Python source distribution. The FAQ
|
|
answers many of the questions that come up again and again, and may
|
|
already contain the solution for your problem.
|
|
|
|
You can support the Python community by joining the Python Software
|
|
Activity, which runs the python.org web, ftp and email servers, and
|
|
organizes Python workshops. See \url{http://www.python.org/psa/} for
|
|
information on how to join.
|
|
|
|
|
|
\appendix
|
|
|
|
\chapter{Interactive Input Editing and History Substitution}
|
|
\label{interacting}
|
|
|
|
Some versions of the Python interpreter support editing of the current
|
|
input line and history substitution, similar to facilities found in
|
|
the Korn shell and the GNU Bash shell. This is implemented using the
|
|
\emph{GNU Readline} library, which supports Emacs-style and vi-style
|
|
editing. This library has its own documentation which I won't
|
|
duplicate here; however, the basics are easily explained.
|
|
|
|
\section{Line Editing}
|
|
\label{lineEditing}
|
|
|
|
If supported, input line editing is active whenever the interpreter
|
|
prints a primary or secondary prompt. The current line can be edited
|
|
using the conventional Emacs control characters. The most important
|
|
of these are: C-A (Control-A) moves the cursor to the beginning of the
|
|
line, C-E to the end, C-B moves it one position to the left, C-F to
|
|
the right. Backspace erases the character to the left of the cursor,
|
|
C-D the character to its right. C-K kills (erases) the rest of the
|
|
line to the right of the cursor, C-Y yanks back the last killed
|
|
string. C-underscore undoes the last change you made; it can be
|
|
repeated for cumulative effect.
|
|
|
|
\section{History Substitution}
|
|
\label{history}
|
|
|
|
History substitution works as follows. All non-empty input lines
|
|
issued are saved in a history buffer, and when a new prompt is given
|
|
you are positioned on a new line at the bottom of this buffer. C-P
|
|
moves one line up (back) in the history buffer, C-N moves one down.
|
|
Any line in the history buffer can be edited; an asterisk appears in
|
|
front of the prompt to mark a line as modified. Pressing the Return
|
|
key passes the current line to the interpreter. C-R starts an
|
|
incremental reverse search; C-S starts a forward search.
|
|
|
|
\section{Key Bindings}
|
|
\label{keyBindings}
|
|
|
|
The key bindings and some other parameters of the Readline library can
|
|
be customized by placing commands in an initialization file called
|
|
\file{\$HOME/.inputrc}. Key bindings have the form
|
|
|
|
\begin{verbatim}
|
|
key-name: function-name
|
|
\end{verbatim}
|
|
|
|
or
|
|
|
|
\begin{verbatim}
|
|
"string": function-name
|
|
\end{verbatim}
|
|
|
|
and options can be set with
|
|
|
|
\begin{verbatim}
|
|
set option-name value
|
|
\end{verbatim}
|
|
|
|
For example:
|
|
|
|
\begin{verbatim}
|
|
# I prefer vi-style editing:
|
|
set editing-mode vi
|
|
# Edit using a single line:
|
|
set horizontal-scroll-mode On
|
|
# Rebind some keys:
|
|
Meta-h: backward-kill-word
|
|
"\C-u": universal-argument
|
|
"\C-x\C-r": re-read-init-file
|
|
\end{verbatim}
|
|
|
|
Note that the default binding for TAB in Python is to insert a TAB
|
|
instead of Readline's default filename completion function. If you
|
|
insist, you can override this by putting
|
|
|
|
\begin{verbatim}
|
|
TAB: complete
|
|
\end{verbatim}
|
|
|
|
in your \file{\$HOME/.inputrc}. (Of course, this makes it hard to type
|
|
indented continuation lines...)
|
|
|
|
Automatic completion of variable and module names is optionally
|
|
available. To enable it in the interpreter's interactive mode, add
|
|
the following to your \file{\$HOME/.pythonrc} file:% $ <- bow to font-lock
|
|
\indexii{.pythonrc.py}{file}%
|
|
\refstmodindex{rlcompleter}%
|
|
\refbimodindex{readline}
|
|
|
|
\begin{verbatim}
|
|
import rlcompleter, readline
|
|
readline.parse_and_bind('tab: complete')
|
|
\end{verbatim}
|
|
|
|
This binds the TAB key to the completion function, so hitting the TAB
|
|
key twice suggests completions; it looks at Python statement names,
|
|
the current local variables, and the available module names. For
|
|
dotted expressions such as \code{string.a}, it will evaluate the the
|
|
expression up to the final \character{.} and then suggest completions
|
|
from the attributes of the resulting object. Note that this may
|
|
execute application-defined code if an object with a
|
|
\method{__getattr__()} method is part of the expression.
|
|
|
|
|
|
\section{Commentary}
|
|
\label{commentary}
|
|
|
|
This facility is an enormous step forward compared to previous
|
|
versions of the interpreter; however, some wishes are left: It would
|
|
be nice if the proper indentation were suggested on continuation lines
|
|
(the parser knows if an indent token is required next). The
|
|
completion mechanism might use the interpreter's symbol table. A
|
|
command to check (or even suggest) matching parentheses, quotes etc.
|
|
would also be useful.
|
|
|
|
% XXX Lele Gaifax's readline module, which adds name completion...
|
|
|
|
\end{document}
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