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with examples and workaround. This keeps coming up, and I believe that this section in the tutorial may have been (in part) the source of the confusion. While it didn't show examples with [] for a default, it also didn't emphasize enough why that would be a bad idea, and while it did say that defaults are evaluated at the point of function definition, the example was not relevant for this issue.
3777 lines
132 KiB
TeX
3777 lines
132 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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\ifhtml
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\chapter*{Front Matter\label{front}}
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\fi
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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 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
|
|
expressed in several ways. They can be enclosed in single quotes or
|
|
double quotes:
|
|
|
|
\begin{verbatim}
|
|
>>> 'spam eggs'
|
|
'spam eggs'
|
|
>>> 'doesn\'t'
|
|
"doesn't"
|
|
>>> "doesn't"
|
|
"doesn't"
|
|
>>> '"Yes," he said.'
|
|
'"Yes," he said.'
|
|
>>> "\"Yes,\" he said."
|
|
'"Yes," he said.'
|
|
>>> '"Isn\'t," she said.'
|
|
'"Isn\'t," she said.'
|
|
\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}.
|
|
|
|
\strong{Important warning:} The default value is evaluated only once.
|
|
This makes a difference when the default is a mutable object such as a
|
|
list or dictionary. For example, the following function accumulates
|
|
the arguments passed to it on subsequent calls:
|
|
|
|
\begin{verbatim}
|
|
def f(a, l = []):
|
|
l.append(a)
|
|
return a
|
|
print f(1)
|
|
print f(2)
|
|
print f(3)
|
|
\end{verbatim}
|
|
|
|
This will print
|
|
|
|
\begin{verbatim}
|
|
[1]
|
|
[1, 2]
|
|
[1, 2, 3]
|
|
\end{verbatim}
|
|
|
|
If you don't want the default to be shared between subsequent calls,
|
|
you can write the function like this instead:
|
|
|
|
\begin{verbatim}
|
|
def f(a, l = None):
|
|
if l is None:
|
|
l = []
|
|
l.append(a)
|
|
return a
|
|
\end{verbatim}
|
|
|
|
\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!
|
|
|
|
% XXX This is no longer necessary!
|
|
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}
|
|
|
|
% XXX Add a bit on the difference between tuples and lists.
|
|
% XXX Also explain that a tuple can *contain* a mutable object!
|
|
|
|
\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}
|
|
|
|
% XXX Need to document that a lone .pyc/.pyo is acceptable too!
|
|
|
|
\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-``byte-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.
|
|
|
|
Some tips for experts:
|
|
|
|
\begin{itemize}
|
|
|
|
\item
|
|
When the Python interpreter is invoked with the \code{-O} flag,
|
|
optimized code is generated and stored in \file{.pyo} files.
|
|
The optimizer currently doesn't help much; it only removes
|
|
\keyword{assert} statements and \code{SET_LINENO} instructions.
|
|
When \code{-O} is used, \emph{all} bytecode is optimized; \code{.pyc}
|
|
files are ignored and \code{.py} files are compiled to optimized
|
|
bytecode.
|
|
|
|
\item
|
|
A program doesn't run any faster when it is read from a
|
|
\file{.pyc} or \file{.pyo} file than when it is read from a \file{.py}
|
|
file; the only thing that's faster about \file{.pyc} or \file{.pyo}
|
|
files is the speed with which they are loaded.
|
|
|
|
\item
|
|
When a script is run by giving its name on the command line, the
|
|
bytecode for the script is never written to a \file{.pyc} or
|
|
\file{.pyo} file. Thus, the startup time of a script may be reduced
|
|
by moving most of its code to a module and having a small bootstrap
|
|
script that imports that module.
|
|
|
|
\item
|
|
It is possible to have a file called \file{spam.pyc} (or
|
|
\file{spam.pyo} when \code{-O} is used) without a module
|
|
\file{spam.py} in the same module. This can be used to distribute
|
|
a library of Python code in a form that is moderately hard to reverse
|
|
engineer.
|
|
|
|
\item
|
|
The module \module{compileall}\refstmodindex{compileall} can create
|
|
\file{.pyc} files (or \file{.pyo} files when \code{-O} is used) for
|
|
all modules in a directory.
|
|
|
|
\end{itemize}
|
|
|
|
|
|
\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}
|
|
|
|
\section{Packages}
|
|
|
|
Packages are a way of structuring Python's module namespace
|
|
by using ``dotted module names''. For example, the module name \module{A.B}
|
|
designates a submodule named \samp{B} in a package named \samp{A}. Just like the
|
|
use of modules saves the authors of different modules from having to
|
|
worry about each other's global variable names, the use of dotted
|
|
module names saves the authors of multi-module packages like NumPy or
|
|
PIL from having to worry about each other's module names.
|
|
|
|
Suppose you want to design a collection of modules (a ``package'') for
|
|
the uniform handling of sound files and sound data. There are many
|
|
different sound file formats (usually recognized by their extension,
|
|
e.g. \file{.wav}, \file{.aiff}, \file{.au}), so you may need to create
|
|
and maintain a growing collection of modules for the conversion
|
|
between the various file formats. There are also many different
|
|
operations you might want to perform on sound data (e.g. mixing,
|
|
adding echo, applying an equalizer function, creating an artificial
|
|
stereo effect), so in addition you will be writing a never-ending
|
|
stream of modules to perform these operations. Here's a possible
|
|
structure for your package (expressed in terms of a hierarchical
|
|
filesystem):
|
|
|
|
\begin{verbatim}
|
|
Sound/ Top-level package
|
|
__init__.py Initialize the sound package
|
|
Formats/ Subpackage for file format conversions
|
|
__init__.py
|
|
wavread.py
|
|
wavwrite.py
|
|
aiffread.py
|
|
aiffwrite.py
|
|
auread.py
|
|
auwrite.py
|
|
...
|
|
Effects/ Subpackage for sound effects
|
|
__init__.py
|
|
echo.py
|
|
surround.py
|
|
reverse.py
|
|
...
|
|
Filters/ Subpackage for filters
|
|
__init__.py
|
|
equalizer.py
|
|
vocoder.py
|
|
karaoke.py
|
|
...
|
|
\end{verbatim}
|
|
The \file{__init__.py} files are required to make Python treat the
|
|
directories as containing packages; this is done to prevent
|
|
directories with a common name, such as \samp{string}, from
|
|
unintentionally hiding valid modules that occur later on the module
|
|
search path. In the simplest case, \file{__init__.py} can just be an
|
|
empty file, but it can also execute initialization code for the
|
|
package or set the \code{__all__} variable, described later.
|
|
|
|
Users of the package can import individual modules from the
|
|
package, for example:
|
|
|
|
\begin{verbatim}
|
|
import Sound.Effects.echo
|
|
\end{verbatim}
|
|
This loads the submodule \module{Sound.Effects.echo}. It must be referenced
|
|
with its full name, e.g.
|
|
|
|
\begin{verbatim}
|
|
Sound.Effects.echo.echofilter(input, output, delay=0.7, atten=4)
|
|
\end{verbatim}
|
|
An alternative way of importing the submodule is:
|
|
|
|
\begin{verbatim}
|
|
from Sound.Effects import echo
|
|
\end{verbatim}
|
|
This also loads the submodule \module{echo}, and makes it available without
|
|
its package prefix, so it can be used as follows:
|
|
|
|
\begin{verbatim}
|
|
echo.echofilter(input, output, delay=0.7, atten=4)
|
|
\end{verbatim}
|
|
|
|
Yet another variation is to import the desired function or variable directly:
|
|
|
|
\begin{verbatim}
|
|
from Sound.Effects.echo import echofilter
|
|
\end{verbatim}
|
|
|
|
Again, this loads the submodule \module{echo}, but this makes its function
|
|
echofilter directly available:
|
|
|
|
\begin{verbatim}
|
|
echofilter(input, output, delay=0.7, atten=4)
|
|
\end{verbatim}
|
|
|
|
Note that when using \code{from \var{package} import \var{item}}, the
|
|
item can be either a submodule (or subpackage) of the package, or some
|
|
other name defined in the package, like a function, class or
|
|
variable. The \code{import} statement first tests whether the item is
|
|
defined in the package; if not, it assumes it is a module and attempts
|
|
to load it. If it fails to find it, \exception{ImportError} is raised.
|
|
|
|
Contrarily, when using syntax like \code{import
|
|
\var{item.subitem.subsubitem}}, each item except for the last must be
|
|
a package; the last item can be a module or a package but can't be a
|
|
class or function or variable defined in the previous item.
|
|
|
|
\subsection{Importing * From a Package}
|
|
%The \code{__all__} Attribute
|
|
|
|
Now what happens when the user writes \code{from Sound.Effects import
|
|
*}? Ideally, one would hope that this somehow goes out to the
|
|
filesystem, finds which submodules are present in the package, and
|
|
imports them all. Unfortunately, this operation does not work very
|
|
well on Mac and Windows platforms, where the filesystem does not
|
|
always have accurate information about the case of a filename! On
|
|
these platforms, there is no guaranteed way to know whether a file
|
|
\file{ECHO.PY} should be imported as a module \module{echo},
|
|
\module{Echo} or \module{ECHO}. (For example, Windows 95 has the
|
|
annoying practice of showing all file names with a capitalized first
|
|
letter.) The DOS 8+3 filename restriction adds another interesting
|
|
problem for long module names.
|
|
|
|
The only solution is for the package author to provide an explicit
|
|
index of the package. The import statement uses the following
|
|
convention: if a package's \file{__init__.py} code defines a list named
|
|
\code{__all__}, it is taken to be the list of module names that should be imported
|
|
when \code{from \var{package} import *} is
|
|
encountered. It is up to the package author to keep this list
|
|
up-to-date when a new version of the package is released. Package
|
|
authors may also decide not to support it, if they don't see a use for
|
|
importing * from their package. For example, the file
|
|
\code{Sounds/Effects/__init__.py} could contain the following code:
|
|
|
|
\begin{verbatim}
|
|
__all__ = ["echo", "surround", "reverse"]
|
|
\end{verbatim}
|
|
|
|
This would mean that \code{from Sound.Effects import *} would
|
|
import the three named submodules of the \module{Sound} package.
|
|
|
|
If \code{__all__} is not defined, the statement \code{from Sound.Effects
|
|
import *} does \emph{not} import all submodules from the package
|
|
\module{Sound.Effects} into the current namespace; it only ensures that the
|
|
package \module{Sound.Effects} has been imported (possibly running its
|
|
initialization code, \file{__init__.py}) and then imports whatever names are
|
|
defined in the package. This includes any names defined (and
|
|
submodules explicitly loaded) by \file{__init__.py}. It also includes any
|
|
submodules of the package that were explicitly loaded by previous
|
|
import statements, e.g.
|
|
|
|
\begin{verbatim}
|
|
import Sound.Effects.echo
|
|
import Sound.Effects.surround
|
|
from Sound.Effects import *
|
|
\end{verbatim}
|
|
|
|
|
|
In this example, the echo and surround modules are imported in the
|
|
current namespace because they are defined in the \module{Sound.Effects}
|
|
package when the \code{from...import} statement is executed. (This also
|
|
works when \code{__all__} is defined.)
|
|
|
|
Note that in general the practicing of importing * from a module or
|
|
package is frowned upon, since it often causes poorly readable code.
|
|
However, it is okay to use it to save typing in interactive sessions,
|
|
and certain modules are designed to export only names that follow
|
|
certain patterns.
|
|
|
|
Remember, there is nothing wrong with using \code{from Package
|
|
import specific_submodule}! In fact, this is the
|
|
recommended notation unless the importing module needs to use
|
|
submodules with the same name from different packages.
|
|
|
|
|
|
\subsection{Intra-package References}
|
|
|
|
The submodules often need to refer to each other. For example, the
|
|
\module{surround} module might use the \module{echo} module. In fact, such references
|
|
are so common that the \code{import} statement first looks in the
|
|
containing package before looking in the standard module search path.
|
|
Thus, the surround module can simply use \code{import echo} or
|
|
\code{from echo import echofilter}. If the imported module is not
|
|
found in the current package (the package of which the current module
|
|
is a submodule), the \code{import} statement looks for a top-level module
|
|
with the given name.
|
|
|
|
When packages are structured into subpackages (as with the \module{Sound}
|
|
package in the example), there's no shortcut to refer to submodules of
|
|
sibling packages - the full name of the subpackage must be used. For
|
|
example, if the module \module{Sound.Filters.vocoder} needs to use the \module{echo}
|
|
module in the \module{Sound.Effects} package, it can use \code{from
|
|
Sound.Effects import echo}.
|
|
|
|
%(One could design a notation to refer to parent packages, similar to
|
|
%the use of ".." to refer to the parent directory in Unix and Windows
|
|
%filesystems. In fact, the \module{ni} module, which was the
|
|
%ancestor of this package system, supported this using \code{__} for
|
|
%the package containing the current module,
|
|
%\code{__.__} for the parent package, and so on. This feature was dropped
|
|
%because of its awkwardness; since most packages will have a relative
|
|
%shallow substructure, this is no big loss.)
|
|
|
|
|
|
|
|
\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[1:]:
|
|
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}
|
|
|