mirror of https://github.com/python/cpython
1556 lines
48 KiB
TeX
1556 lines
48 KiB
TeX
% Format this file with latex.
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%\documentstyle[11pt,myformat]{article}
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\documentstyle[palatino,11pt,myformat]{article}
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\title{\bf
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Python Tutorial \\
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(DRAFT)
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}
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\author{
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Guido van Rossum \\
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Dept. CST, CWI, Kruislaan 413 \\
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1098 SJ Amsterdam, The Netherlands \\
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E-mail: {\tt guido@cwi.nl}
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}
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\begin{document}
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\pagenumbering{roman}
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\maketitle
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\begin{abstract}
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\noindent
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Python is a simple, yet powerful programming language that bridges the
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gap between C and shell programming, and is thus ideally suited for rapid
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prototyping.
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Its syntax is put together from constructs borrowed from a variety of other
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languages; most prominent are influences from ABC, C, Modula-3 and Icon.
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The Python interpreter is easily extended with new functions and data
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types implemented in C.
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Python is also suitable as an extension language for highly
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customizable C applications such as editors or window managers.
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Python is available for various operating systems, amongst which
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several flavors of \UNIX, Amoeba, and the Apple Macintosh O.S.
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This tutorial introduces the reader informally to the basic concepts and
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features of the Python language and system.
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It helps to have a Python interpreter handy for hands-on experience,
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but as the examples are self-contained, the tutorial can be read
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off-line as well.
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For a description of standard objects and modules, see the Library
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Reference document.
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The Language Reference document (XXX not yet existing)
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gives a more formal definition of the language.
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\end{abstract}
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\pagebreak
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\tableofcontents
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\pagebreak
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\pagenumbering{arabic}
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\section{Whetting Your Appetite}
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If you ever wrote a large shell script, you probably know this feeling:
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you'd love to add yet another feature, but it's already so slow, and so
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big, and so complicated; or the feature involves a system call or other
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funcion that is only accessible from C \ldots
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Usually the problem at hand isn't serious enough to warrant rewriting
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the script in C; perhaps because the problem requires variable-length
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strings or other data types (like sorted lists of file names) that
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are easy in the shell but lots of work to implement in C; or perhaps
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just because you're not sufficiently familiar with C.
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In such cases, Python may be just the language for you.
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Python is simple to use, but it is a real programming language, offering
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much more structure and support for large programs than the shell has.
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On the other hand, it also offers much more error checking than C, and,
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being a
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{\em very-high-level language},
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it has high-level data types built in, such as flexible arrays and
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dictionaries that would cost you days to implement efficiently in C.
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Because of its more general data types Python is applicable to a
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much larger problem domain than
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{\em Awk}
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or even
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{\em Perl},
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yet most simple things are at least as easy in Python as in those
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languages.
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Python allows you to split up your program in modules that can be reused
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in other Python programs.
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It comes with a large collection of standard modules that you can use as
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the basis for your programs --- or as examples to start learning to
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program in Python.
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There are also built-in modules that provide things like file I/O,
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system calls, and even a generic interface to window systems (STDWIN).
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Python is an interpreted language, which saves you considerable time
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during program development because no compilation and linking is
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necessary.
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The interpreter can be used interactively, which makes it easy to
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experiment with features of the language, to write throw-away programs,
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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.
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Programs written in Python are typically much shorter than equivalent C
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programs:
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No declarations are necessary (all type checking is
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dynamic); statement grouping is done by indentation instead of begin/end
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brackets; and the high-level data types allow you to express complex
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operations in a single statement.
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Python is
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{\em extensible}:
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if you know how to program in C it is easy to add a new built-in module
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to the interpreter, either to perform critical operations at maximum
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speed, or to link Python programs to libraries that may be only available
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in binary form (such as a vendor-specific graphics library).
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Once you are really hooked, you can link the Python interpreter into an
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application written in C and use it as an extension or command language.
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\subsection{Where From Here}
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Now that you are all excited about Python, you'll want to examine it in
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some more detail.
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Since the best introduction to a language is using it, you are invited
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here to do so.
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In the next section, the mechanics of using the interpreter are
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explained.
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This is rather mundane information, but essential for trying out the
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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 expressions,
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statements and data types, through functions and modules, and finally
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touching upon advanced concepts like exceptions and classes.
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\section{Using the Python Interpreter}
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The Python interpreter is usually installed as
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{\tt /usr/local/python}
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on those machines where it is available; putting
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{\tt /usr/local}
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in your {\UNIX} shell's search path makes it possible to start it by
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typing the command
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\bcode\begin{verbatim}
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python
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\end{verbatim}\ecode
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to the shell.
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Since the choice of the directory where the interpreter lives is an
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installation option, other places instead of
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{\tt /usr/local}
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are possible; check with your local Python guru or system
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administrator.
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The interpreter operates somewhat like the {\UNIX} shell: when called with
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standard input connected to a tty device, it reads and executes commands
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interactively; when called with a file name argument or with a file as
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standard input, it reads and executes a
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{\em script}
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from that file.%
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\footnote{
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There is a difference between ``{\tt python file}'' and
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``{\tt python $<$file}''. In the latter case {\tt input()} and
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{\tt raw\_input()} are satisfied from {\em file}, which has
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already been read until the end by the parser, so they will read
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EOF immediately. In the former case (which is usually what
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you want) they are satisfied from whatever file or device is
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connected to standard input of the Python interpreter.
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}
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A third possibility is ``{\tt python -c command [arg] ...}'', which
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executes the statement(s) in {\tt command}, in analogy of the shell's
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{\tt -c} option.
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When available, the script name and additional arguments thereafter are
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passed to the script in the variable
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{\tt sys.argv},
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which is a list of strings.
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When {\tt -c command} is used, {\tt sys.argv} is set to {\tt '-c'}.
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When commands are read from a tty, the interpreter is said to be in
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{\em interactive\ mode}.
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In this mode it prompts for the next command with the
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{\em primary\ prompt},
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usually three greater-than signs ({\tt >>>}); for continuation lines
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it prompts with the
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{\em secondary\ prompt},
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by default three dots ({\tt ...}).
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Typing an EOF (Control-D) at the primary prompt causes the interpreter
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to exit with a zero exit status.
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When an error occurs in interactive mode, the interpreter prints a
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message and a stack trace and returns to the primary prompt; with input
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from a file, it exits with a nonzero exit status.
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(Exceptions handled by an
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{\tt except}
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clause in a
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{\tt try}
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statement are not errors in this context.)
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Some errors are unconditionally fatal and cause an exit with a nonzero
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exit; this applies to internal inconsistencies and some cases of running
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out of memory.
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All error messages are written to the standard error stream; normal
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output from the executed commands is written to standard output.
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Typing an interrupt (normally Control-C or DEL) to the primary or
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secondary prompt cancels the input and returns to the primary prompt.
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Typing an interrupt while a command is being executed raises the
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{\tt KeyboardInterrupt}
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exception, which may be handled by a
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{\tt try}
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statement.
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When a module named
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{\tt foo}
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is imported, the interpreter searches for a file named
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{\tt foo.py}
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in a list of directories specified by the environment variable
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{\tt PYTHONPATH}.
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It has the same syntax as the {\UNIX} shell variable
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{\tt PATH},
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i.e., a list of colon-separated directory names.
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When
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{\tt PYTHONPATH}
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is not set, an installation-dependent default path is used, usually
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{\tt .:/usr/local/lib/python}.%
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\footnote{
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Modules are really searched in the list of directories given by
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the variable {\tt sys.path} which is initialized from
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{\tt PYTHONPATH} or from the installation-dependent default.
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See the section on Standard Modules later.
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}
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As an important speed-up of the start-up time of short programs, if a
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file called {\tt foo.pyc} exists in the directory where {\tt foo.py}
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is found, this is assumed to contain an already-``compiled'' version
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of the module {\tt foo}. The last modification time of {\tt foo.py}
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is recorded in {\tt foo.pyc}, and if these don't match, {\tt foo.pyc}
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is ignored. Whenever {\tt foo.py} is successfully compiled, an
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attempt is made to write the compiled version to {\tt foo.pyc}.
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On BSD'ish {\UNIX} systems, Python scripts can be made directly executable,
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like shell scripts, by putting the line
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\bcode\begin{verbatim}
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#! /usr/local/python
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\end{verbatim}\ecode
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(assuming that's the name of the interpreter) at the beginning of the
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script and giving the file an executable mode.
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(The
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{\tt \#!}
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must be the first two characters of the file.)
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\subsection{Interactive Input Editing and History Substitution}
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Some versions of the Python interpreter support editing of the current
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input line and history substitution, similar to facilities found in the
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Korn shell and the GNU Bash shell.
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This is implemented using the
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{\em GNU\ Readline}
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library, which supports Emacs-style and vi-style editing.
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This library has its own documentation which I won't duplicate here;
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however, the basics are easily explained.
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If supported,%
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\footnote{
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Perhaps the quickest check to see whether command line editing
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is supported is typing Control-P to the first Python prompt
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you get. If it beeps, you have command line editing.
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If not, you can skip the rest of this section.
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}
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input line editing is active whenever the interpreter prints a primary
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or secondary prompt.
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The current line can be edited using the conventional Emacs control
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characters.
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The most important of these are:
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C-A (Control-A) moves the cursor to the beginning of the line, C-E to
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the end, C-B moves it one position to the left, C-F to the right.
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Backspace erases the character to the left of the cursor, C-D the
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character to its right.
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C-K kills (erases) the rest of the line to the right of the cursor, C-Y
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yanks back the last killed string.
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C-underscore undoes the last change you made; it can be repeated for
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cumulative effect.
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History substitution works as follows.
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All non-empty input lines issued are saved in a history buffer,
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and when a new prompt is given you are positioned on a new line at the
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bottom of this buffer.
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C-P moves one line up (back) in the history buffer, C-N moves one down.
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Any line in the history buffer can be edited; an asterisk appears in
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front of the prompt to mark a line as modified.
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Pressing the Return key passes the current line to the interpreter.
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C-R starts an incremental reverse search; C-S starts a forward search.
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The key bindings and some other parameters of the Readline library can
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be customized by placing commands in an initialization file called
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{\tt \$HOME/.initrc}.
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Key bindings have the form
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\bcode\begin{verbatim}
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key-name: function-name
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\end{verbatim}\ecode
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and options can be set with
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\bcode\begin{verbatim}
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set option-name value
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\end{verbatim}\ecode
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Example:
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\bcode\begin{verbatim}
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# I prefer vi-style editing:
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set editing-mode vi
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# Edit using a single line:
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set horizontal-scroll-mode On
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# Rebind some keys:
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Meta-h: backward-kill-word
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Control-u: universal-argument
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\end{verbatim}\ecode
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Note that the default binding for TAB in Python is to insert a TAB
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instead of Readline's default filename completion function.
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If you insist, you can override this by putting
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\bcode\begin{verbatim}
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TAB: complete
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\end{verbatim}\ecode
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in your
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{\tt \$HOME/.inputrc}.
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(Of course, this makes it hard to type indented continuation lines.)
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This facility is an enormous step forward compared to previous versions of
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the interpreter; however, some wishes are left:
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It would be nice if the proper indentation were suggested on
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continuation lines (the parser knows if an indent token is required
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next).
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The completion mechanism might use the interpreter's symbol table.
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A function to check (or even suggest) matching parentheses, quotes
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etc. would also be useful.
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\section{An Informal Introduction to Python}
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In the following examples, input and output are distinguished by the
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presence or absence of prompts ({\tt >>>} and {\tt ...}): to repeat the
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example, you must type everything after the prompt, when the prompt
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appears; everything on lines that do not begin with a prompt is output
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from the interpreter.
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Note that a secondary prompt on a line by itself in an example means you
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must type a blank line; this is used to end a multi-line command.
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\subsection{Using Python as a Calculator}
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Let's try some simple Python commands.
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Start the interpreter and wait for the primary prompt,
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{\tt >>>}.
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The interpreter acts as a simple calculator: you can type an expression
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at it and it will write the value.
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Expression syntax is straightforward: the operators
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{\tt +},
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{\tt -},
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{\tt *}
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and
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{\tt /}
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work just as in most other languages (e.g., Pascal or C); parentheses
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can be used for grouping.
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For example:
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\bcode\begin{verbatim}
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>>> # This is a comment
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>>> 2+2
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4
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>>>
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>>> (50-5+5*6+25)/4
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25
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>>> # Division truncates towards zero:
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>>> 7/3
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2
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>>>
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\end{verbatim}\ecode
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As in C, the equal sign ({\tt =}) is used to assign a value to a variable.
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The value of an assignment is not written:
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\bcode\begin{verbatim}
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>>> width = 20
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>>> height = 5*9
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>>> width * height
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900
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>>>
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\end{verbatim}\ecode
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There is some support for floating point, but you can't mix floating
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point and integral numbers in expression (yet):
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\bcode\begin{verbatim}
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>>> 10.0 / 3.3
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3.0303030303
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>>>
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\end{verbatim}\ecode
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Besides numbers, Python can also manipulate strings, enclosed in single
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quotes:
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\bcode\begin{verbatim}
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>>> 'foo bar'
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'foo bar'
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>>> 'doesn\'t'
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'doesn\'t'
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>>>
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\end{verbatim}\ecode
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Strings are written inside quotes and with quotes and other funny
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characters escaped by backslashes, to show the precise value.
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(There is also a way to write strings without quotes and escapes.)
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Strings can be concatenated (glued together) with the
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{\tt +}
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operator, and repeated with~{\tt *}:
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\bcode\begin{verbatim}
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>>> word = 'Help' + 'A'
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>>> word
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'HelpA'
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>>> '<' + word*5 + '>'
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'<HelpAHelpAHelpAHelpAHelpA>'
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>>>
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\end{verbatim}\ecode
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Strings can be subscripted; as in C, the first character of a string has
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subscript 0.
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There is no separate character type; a character is simply a string of
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size one.
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|
As in Icon, substrings can be specified with the
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{\em slice}
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notation: two subscripts (indices) separated by a colon.
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|
\bcode\begin{verbatim}
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|
>>> word[4]
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'A'
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>>> word[0:2]
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'He'
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>>> word[2:4]
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'lp'
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>>> # Slice indices have useful defaults:
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>>> word[:2] # Take first two characters
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'He'
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>>> word[2:] # Drop first two characters
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'lpA'
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>>> # A useful invariant: s[:i] + s[i:] = s
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>>> word[:3] + word[3:]
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'HelpA'
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>>>
|
|
\end{verbatim}\ecode
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|
Degenerate cases are handled gracefully: an index that is too large is
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|
replaced by the string size, an upper bound smaller than the lower bound
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|
returns an empty string.
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|
\bcode\begin{verbatim}
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|
>>> word[1:100]
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'elpA'
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|
>>> word[10:]
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''
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|
>>> word[2:1]
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|
''
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>>>
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|
\end{verbatim}\ecode
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|
Slice indices (but not simple subscripts) may be negative numbers, to
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start counting from the right.
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|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> word[-2:] # Take last two characters
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|
'pA'
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>>> word[:-2] # Drop last two characters
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|
'Hel'
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|
>>> # But -0 does not count from the right!
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|
>>> word[-0:] # (since -0 equals 0)
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'HelpA'
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>>>
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\end{verbatim}\ecode
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|
The best way to remember how slices work is to think of the indices as
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|
pointing
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|
{\em between}
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|
characters, with the left edge of the first character numbered 0.
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|
Then the right edge of the last character of a string of
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|
{\tt n}
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|
characters has index
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|
{\tt n},
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|
for example:
|
|
\bcode\begin{verbatim}
|
|
+---+---+---+---+---+
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|
| H | e | l | p | A |
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|
+---+---+---+---+---+
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0 1 2 3 4 5
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-5 -4 -3 -2 -1
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\end{verbatim}\ecode
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|
The first row of numbers gives the position of the indices 0...5 in the
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string; the second row gives the corresponding negative indices.
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|
For nonnegative indices, the length of a slice is the difference of the
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indices, if both are within bounds,
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|
e.g.,
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the length of
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|
{\tt word[1:3]}
|
|
is 3--1 = 2.
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|
Finally, the built-in function {\tt len()} computes the length of a
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string:
|
|
\bcode\begin{verbatim}
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|
>>> s = 'supercalifragilisticexpialidocious'
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|
>>> len(s)
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34
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>>>
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\end{verbatim}\ecode
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|
Python knows a number of
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{\em compound}
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|
data types, used to group together other values.
|
|
The most versatile is the
|
|
{\em list},
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|
which can be written as a list of comma-separated values between square
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|
brackets:
|
|
\bcode\begin{verbatim}
|
|
>>> a = ['foo', 'bar', 100, 1234]
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|
>>> a
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|
['foo', 'bar', 100, 1234]
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>>>
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\end{verbatim}\ecode
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|
As for strings, list subscripts start at 0:
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|
\bcode\begin{verbatim}
|
|
>>> a[0]
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'foo'
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|
>>> a[3]
|
|
1234
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Lists can be sliced, concatenated and so on, like strings:
|
|
\bcode\begin{verbatim}
|
|
>>> a[1:3]
|
|
['bar', 100]
|
|
>>> a[:2] + ['bletch', 2*2]
|
|
['foo', 'bar', 'bletch', 4]
|
|
>>> 3*a[:3] + ['Boe!']
|
|
['foo', 'bar', 100, 'foo', 'bar', 100, 'foo', 'bar', 100, 'Boe!']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Unlike strings, which are
|
|
{\em immutable},
|
|
it is possible to change individual elements of a list:
|
|
\bcode\begin{verbatim}
|
|
>>> a
|
|
['foo', 'bar', 100, 1234]
|
|
>>> a[2] = a[2] + 23
|
|
>>> a
|
|
['foo', 'bar', 123, 1234]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Assignment to slices is also possible, and this may even change the size
|
|
of the list:
|
|
\bcode\begin{verbatim}
|
|
>>> # Replace some items:
|
|
>>> a[0:2] = [1, 12]
|
|
>>> a
|
|
[1, 12, 123, 1234]
|
|
>>> # Remove some:
|
|
>>> a[0:2] = []
|
|
>>> a
|
|
[123, 1234]
|
|
>>> # Insert some:
|
|
>>> a[1:1] = ['bletch', 'xyzzy']
|
|
>>> a
|
|
[123, 'bletch', 'xyzzy', 1234]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The built-in function {\tt len()} also applies to lists:
|
|
\bcode\begin{verbatim}
|
|
>>> len(a)
|
|
4
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsection{Tuples and Sequences}
|
|
|
|
XXX To Be Done.
|
|
|
|
\subsection{First Steps Towards Programming}
|
|
|
|
Of course, we can use Python for more complicated tasks than adding two
|
|
and two together.
|
|
For instance, we can write an initial subsequence of the
|
|
{\em Fibonacci}
|
|
series as follows:
|
|
\bcode\begin{verbatim}
|
|
>>> # Fibonacci series:
|
|
>>> # the sum of two elements defines the next
|
|
>>> a, b = 0, 1
|
|
>>> while b < 100:
|
|
... print b
|
|
... a, b = b, a+b
|
|
...
|
|
1
|
|
1
|
|
2
|
|
3
|
|
5
|
|
8
|
|
13
|
|
21
|
|
34
|
|
55
|
|
89
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
This example introduces several new features.
|
|
\begin{itemize}
|
|
\item
|
|
The first line contains a
|
|
{\em multiple\ assignment}:
|
|
the variables
|
|
{\tt a}
|
|
and
|
|
{\tt b}
|
|
simultaneously get the new values 0 and 1.
|
|
On the last line this is used again, demonstrating that the expressions
|
|
on the right-hand side are all evaluated first before any of the
|
|
assignments take place.
|
|
\item
|
|
The
|
|
{\tt while}
|
|
loop executes as long as the condition (here: $b < 100$) remains true.
|
|
In Python, as 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 as
|
|
{\tt <},
|
|
{\tt >},
|
|
{\tt =},
|
|
{\tt <=},
|
|
{\tt >=}
|
|
and
|
|
{\tt <>}.%
|
|
\footnote{
|
|
The ambiguity of using {\tt =}
|
|
for both assignment and equality is resolved by disallowing
|
|
unparenthesized conditions at the right hand side of assignments.
|
|
}
|
|
\item
|
|
The
|
|
{\em body}
|
|
of the loop is
|
|
{\em indented}: indentation is Python's way of grouping statements.
|
|
Python does not (yet!) provide an intelligent input line editing
|
|
facility, so you have to type a tab or space(s) for each indented line.
|
|
In practice you will prepare more complicated input for Python with a
|
|
text editor; most text editors have an auto-indent facility.
|
|
When a compound statement is entered interactively, it must be
|
|
followed by a blank line to indicate completion (since the parser
|
|
cannot guess when you have typed the last line).
|
|
\item
|
|
The
|
|
{\tt print}
|
|
statement writes the value of the expression(s) it is given.
|
|
It differs from just writing the expression you want to write (as we did
|
|
earlier in the calculator examples) in the way it handles multiple
|
|
expressions and strings.
|
|
Strings are written without quotes and a space is inserted between
|
|
items, so you can format things nicely, like this:
|
|
\bcode\begin{verbatim}
|
|
>>> i = 256*256
|
|
>>> print 'The value of i is', i
|
|
The value of i is 65536
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
A trailing comma avoids the newline after the output:
|
|
\bcode\begin{verbatim}
|
|
>>> a, b = 0, 1
|
|
>>> while b < 1000:
|
|
... print b,
|
|
... a, b = b, a+b
|
|
...
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Note that the interpreter inserts a newline before it prints the next
|
|
prompt if the last line was not completed.
|
|
\end{itemize}
|
|
|
|
\subsection{More Control Flow Tools}
|
|
|
|
Besides the {\tt while} statement just introduced, Python knows the
|
|
usual control flow statements known from other languages, with some
|
|
twists.
|
|
|
|
\subsubsection{If Statements}
|
|
|
|
Perhaps the most well-known statement type is the {\tt if} statement.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> if x < 0:
|
|
... x = 0
|
|
... print 'Negative changed to zero'
|
|
... elif x = 0:
|
|
... print 'Zero'
|
|
... elif x = 1:
|
|
... print 'Single'
|
|
... else:
|
|
... print 'More'
|
|
...
|
|
\end{verbatim}\ecode
|
|
There can be zero or more {\tt elif} parts, and the {\tt else} part is
|
|
optional.
|
|
The keyword `{\tt elif}' is short for `{\tt else if}', and is useful to
|
|
avoid excessive indentation.
|
|
An {\tt if...elif...elif...} sequence is a substitute for the
|
|
{\em switch} or {\em case} statements found in other languages.
|
|
|
|
\subsubsection{For Statements}
|
|
|
|
The {\tt for} statement in Python differs a bit from what you may be
|
|
used to in C or Pascal.
|
|
Rather than always iterating over an arithmetic progression of numbers
|
|
(as Pascal), or leaving the user completely free in the iteration test
|
|
and step (as C), Python's {\tt for} statement iterates over the items
|
|
of any sequence (e.g., a list or a string).
|
|
For example (no pun intended):
|
|
\bcode\begin{verbatim}
|
|
>>> # Measure some strings:
|
|
>>> a = ['cat', 'window', 'defenestrate']
|
|
>>> for x in a:
|
|
... print x, len(x)
|
|
...
|
|
cat 3
|
|
window 6
|
|
defenestrate 12
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{The {\tt range()} Function}
|
|
|
|
If you do need to iterate over a sequence of numbers, the built-in
|
|
function {\tt range()} comes in handy.
|
|
It generates lists containing arithmetic progressions,
|
|
e.g.:
|
|
\bcode\begin{verbatim}
|
|
>>> range(10)
|
|
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The given end point is never part of the generated list;
|
|
{\tt range(10)} generates a list of 10 values,
|
|
exactly the legal indices for items of a sequence of length 10.
|
|
It is possible to let the range start at another number, or to specify a
|
|
different increment (even negative):
|
|
\bcode\begin{verbatim}
|
|
>>> range(5, 10)
|
|
[5, 6, 7, 8, 9]
|
|
>>> range(0, 10, 3)
|
|
[0, 3, 6, 9]
|
|
>>> range(-10, -100, -30)
|
|
[-10, -40, -70]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
To iterate over the indices of a sequence, combine {\tt range()}
|
|
and {\tt len()} as follows:
|
|
\bcode\begin{verbatim}
|
|
>>> a = ['Mary', 'had', 'a', 'little', 'boy']
|
|
>>> for i in range(len(a)):
|
|
... print i, a[i]
|
|
...
|
|
0 Mary
|
|
1 had
|
|
2 a
|
|
3 little
|
|
4 boy
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{Break Statements and Else Clauses on Loops}
|
|
|
|
The {\tt break} statement breaks out of the smallest enclosing {\tt for}
|
|
or {\tt while} loop.
|
|
Loop statements may have an {\tt else} clause; it is executed when the
|
|
loop terminates through exhaustion of the list (with {\tt for}) or when
|
|
the condition becomes false (with {\tt while}) but not when the loop is
|
|
terminated by a {\tt break} statement.
|
|
This is exemplified by the following loop, which searches for a list
|
|
item of value 0:
|
|
\bcode\begin{verbatim}
|
|
>>> for n in range(2, 10):
|
|
... for x in range(2, n):
|
|
... if n % x = 0:
|
|
... print n, 'equals', x, '*', n/x
|
|
... break
|
|
... else:
|
|
... print n, 'is a prime number'
|
|
...
|
|
2 is a prime number
|
|
3 is a prime number
|
|
4 equals 2 * 2
|
|
5 is a prime number
|
|
6 equals 2 * 3
|
|
7 is a prime number
|
|
8 equals 2 * 4
|
|
9 equals 3 * 3
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{Pass Statements}
|
|
|
|
The {\tt pass} statement does nothing.
|
|
It can be used when a statement is required syntactically but the
|
|
program requires no action.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> while 1:
|
|
... pass # Busy-wait for keyboard interrupt
|
|
...
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{Conditions Revisited}
|
|
|
|
XXX To Be Done.
|
|
|
|
\subsection{Defining Functions}
|
|
|
|
We can create a function that writes the Fibonacci series to an
|
|
arbitrary boundary:
|
|
\bcode\begin{verbatim}
|
|
>>> def fib(n): # write Fibonacci series up to n
|
|
... a, b = 0, 1
|
|
... while b <= n:
|
|
... print b,
|
|
... a, b = b, a+b
|
|
...
|
|
>>> # Now call the function we just defined:
|
|
>>> fib(2000)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The keyword
|
|
{\tt def}
|
|
introduces a function
|
|
{\em definition}.
|
|
It must be followed by the function name and the parenthesized list of
|
|
formal parameters.
|
|
The statements that form the body of the function starts at the next
|
|
line, indented by a tab stop.
|
|
The
|
|
{\em execution}
|
|
of a function introduces a new symbol table used for the local variables
|
|
of the function.
|
|
More precisely, all variable assignments in a function store the value
|
|
in the local symbol table; 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, the global symbol table is
|
|
{\em read-only}
|
|
within a function.
|
|
The actual parameters (arguments) to a function call are introduced in
|
|
the local symbol table of the called function when it is called;
|
|
thus, arguments are passed using
|
|
{\em call\ by\ value}.%
|
|
\footnote{
|
|
Actually, {\em call by object reference} would be a better
|
|
description, since if a mutable object is passed, the caller
|
|
will see any changes the callee makes to it (e.g., items
|
|
inserted into a list).
|
|
}
|
|
When a function calls another function, a new local symbol table is
|
|
created for that call.
|
|
|
|
A function definition introduces the function name in the global symbol
|
|
table.
|
|
The value has a type that is recognized by the interpreter as a
|
|
user-defined function.
|
|
This value can be assigned to another name which can then also be used
|
|
as a function.
|
|
This serves as a general renaming mechanism:
|
|
\bcode\begin{verbatim}
|
|
>>> fib
|
|
<function object at 10042ed0>
|
|
>>> f = fib
|
|
>>> f(100)
|
|
1 1 2 3 5 8 13 21 34 55 89
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
You might object that
|
|
{\tt fib}
|
|
is not a function but a procedure.
|
|
In Python, as in C, procedures are just functions that don't return a
|
|
value.
|
|
In fact, technically speaking, procedures do return a value, albeit a
|
|
rather boring one.
|
|
This value is called {\tt None} (it's a built-in name).
|
|
Writing the value {\tt None} is normally suppressed by the interpreter
|
|
if it would be the only value written.
|
|
You can see it if you really want to:
|
|
\bcode\begin{verbatim}
|
|
>>> print fib(0)
|
|
None
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
It is simple to write a function that returns a list of the numbers of
|
|
the Fibonacci series, instead of printing it:
|
|
\bcode\begin{verbatim}
|
|
>>> def fib2(n): # return Fibonacci series up to n
|
|
... result = []
|
|
... a, b = 0, 1
|
|
... while b <= n:
|
|
... result.append(b) # see below
|
|
... a, b = b, a+b
|
|
... return result
|
|
...
|
|
>>> f100 = fib2(100) # call it
|
|
>>> f100 # write the result
|
|
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
This example, as usual, demonstrates some new Python features:
|
|
\begin{itemize}
|
|
\item
|
|
The
|
|
{\tt return}
|
|
statement returns with a value from a function.
|
|
{\tt return}
|
|
without an expression argument is used to return from the middle of a
|
|
procedure (falling off the end also returns from a proceduce).
|
|
\item
|
|
The statement
|
|
{\tt ret.append(b)}
|
|
calls a
|
|
{\em method}
|
|
of the list object
|
|
{\tt ret}.
|
|
A method is a function that `belongs' to an object and is named
|
|
{\tt obj.methodname},
|
|
where
|
|
{\tt obj}
|
|
is some object (this may be an expression), and
|
|
{\tt methodname}
|
|
is the name of a method that is defined by the object's type.
|
|
Different types define different methods.
|
|
Methods of different types may have the same name without causing
|
|
ambiguity.
|
|
See the section on classes, later, to find out how you can define your
|
|
own object types and methods.
|
|
The method
|
|
{\tt append}
|
|
shown in the example, is defined for list objects; it adds a new element
|
|
at the end of the list.
|
|
In this case it is equivalent to
|
|
{\tt ret = ret + [b]},
|
|
but more efficient.%
|
|
\footnote{
|
|
There is a subtle semantic difference if the object
|
|
is referenced from more than one place.
|
|
}
|
|
\end{itemize}
|
|
The list object type has two more methods:
|
|
\begin{description}
|
|
\item[{\tt insert(i, x)}]
|
|
Inserts an item at a given position.
|
|
The first argument is the index of the element before which to insert,
|
|
so {\tt a.insert(0, x)} inserts at the front of the list, and
|
|
{\tt a.insert(len(a), x)} is equivalent to {\tt a.append(x)}.
|
|
\item[{\tt sort()}]
|
|
Sorts the elements of the list.
|
|
\end{description}
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> a = [10, 100, 1, 1000]
|
|
>>> a.insert(2, -1)
|
|
>>> a
|
|
[10, 100, -1, 1, 1000]
|
|
>>> a.sort()
|
|
>>> a
|
|
[-1, 1, 10, 100, 1000]
|
|
>>> # Strings are sorted according to ASCII:
|
|
>>> b = ['Mary', 'had', 'a', 'little', 'boy']
|
|
>>> b.sort()
|
|
>>> b
|
|
['Mary', 'a', 'boy', 'had', 'little']
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsection{Modules}
|
|
|
|
If you quit from the Python interpreter and enter it again, the
|
|
definitions you have made (functions and variables) are lost.
|
|
Therefore, if you want to write a somewhat longer program, you are
|
|
better off using a text editor to prepare the input for the interpreter
|
|
and run it with that file as input instead.
|
|
This is known as creating a
|
|
{\em script}.
|
|
As your program gets longer, you may want to split it into several files
|
|
for easier maintenance.
|
|
You may also want to use a handy function that you've written in several
|
|
programs without copying its definition into each program.
|
|
To support this, Python has a way to put definitions in a file and use
|
|
them in a script or in an interactive instance of the interpreter.
|
|
Such a file is called a
|
|
{\em module};
|
|
definitions from a module can be
|
|
{\em imported}
|
|
into other modules or into the
|
|
{\em main}
|
|
module (the collection of variables that you have access to in
|
|
a script and in calculator mode).
|
|
|
|
A module is a file containing Python definitions and statements.
|
|
The file name is the module name with the suffix
|
|
{\tt .py}
|
|
appended.
|
|
For instance, use your favorite text editor to create a file called
|
|
{\tt fibo.py}
|
|
in the current directory with the following contents:
|
|
\bcode\begin{verbatim}
|
|
# Fibonacci numbers module
|
|
|
|
def fib(n): # write Fibonacci series up to n
|
|
a, b = 0, 1
|
|
while b <= n:
|
|
print b,
|
|
a, b = b, a+b
|
|
|
|
def fib2(n): # return Fibonacci series up to n
|
|
ret = []
|
|
a, b = 0, 1
|
|
while b <= n:
|
|
ret.append(b)
|
|
a, b = b, a+b
|
|
return ret
|
|
\end{verbatim}\ecode
|
|
Now enter the Python interpreter and import this module with the
|
|
following command:
|
|
\bcode\begin{verbatim}
|
|
>>> import fibo
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
This does not enter the names of the functions defined in
|
|
{\tt fibo}
|
|
directly in the symbol table; it only enters the module name
|
|
{\tt fibo}
|
|
there.
|
|
Using the module name you can access the functions:
|
|
\bcode\begin{verbatim}
|
|
>>> fibo.fib(1000)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
|
|
>>> fibo.fib2(100)
|
|
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
If you intend to use a function often you can assign it to a local name:
|
|
\bcode\begin{verbatim}
|
|
>>> fib = fibo.fib
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{More on Modules}
|
|
|
|
A module can contain executable statements as well as function
|
|
definitions.
|
|
These statements are intended to initialize the module.
|
|
They are executed only the
|
|
{\em first}
|
|
time the module is imported somewhere.%
|
|
\footnote{
|
|
In fact function definitions are also `statements' that are
|
|
`executed'; the execution enters the function name in the
|
|
module's global symbol table.
|
|
}
|
|
|
|
Each module has its own private symbol table, which is used as the
|
|
global symbol table by all functions defined in the module.
|
|
Thus, the author of a module can use global variables in the module
|
|
without worrying about accidental clashes with a user's global
|
|
variables.
|
|
On the other hand, if you know what you are doing you can touch a
|
|
module's global variables with the same notation used to refer to its
|
|
functions,
|
|
{\tt modname.itemname}.
|
|
|
|
Modules can import other modules.
|
|
It is customary but not required to place all
|
|
{\tt import}
|
|
statements at the beginning of a module (or script, for that matter).
|
|
The imported module names are placed in the importing module's global
|
|
symbol table.
|
|
|
|
There is a variant of the
|
|
{\tt import}
|
|
statement that imports names from a module directly into the importing
|
|
module's symbol table.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> from fibo import fib, fib2
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
This does not introduce the module name from which the imports are taken
|
|
in the local symbol table (so in the example, {\tt fibo} is not
|
|
defined).
|
|
|
|
There is even a variant to import all names that a module defines:
|
|
\bcode\begin{verbatim}
|
|
>>> from fibo import *
|
|
>>> fib(500)
|
|
1 1 2 3 5 8 13 21 34 55 89 144 233 377
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
This imports all names except those beginning with an underscore
|
|
({\tt \_}).
|
|
|
|
\subsubsection{Standard Modules}
|
|
|
|
Python comes with a library of standard modules, described in a separate
|
|
document (Python Library and Module Reference).
|
|
Some modules are built into the interpreter; these provide access to
|
|
operations that are not part of the core of the language but are
|
|
nevertheless built in, either for efficiency or to provide access to
|
|
operating system primitives such as system calls.
|
|
The set of such modules is a configuration option; e.g., the
|
|
{\tt amoeba}
|
|
module is only provided on systems that somehow support Amoeba
|
|
primitives.
|
|
One particular module deserves some attention:
|
|
{\tt sys},
|
|
which is built into every Python interpreter.
|
|
The variables
|
|
{\tt sys.ps1}
|
|
and
|
|
{\tt sys.ps2}
|
|
define the strings used as primary and secondary prompts:
|
|
\bcode\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.ps1
|
|
'>>> '
|
|
>>> sys.ps2
|
|
'... '
|
|
>>> sys.ps1 = 'C> '
|
|
C> print 'Yuck!'
|
|
Yuck!
|
|
C>
|
|
\end{verbatim}\ecode
|
|
These two variables are only defined if the interpreter is in
|
|
interactive mode.
|
|
|
|
The variable
|
|
{\tt sys.path}
|
|
is a list of strings that determine the interpreter's search path for
|
|
modules.
|
|
It is initialized to a default path taken from the environment variable
|
|
{\tt PYTHONPATH},
|
|
or from a built-in default if
|
|
{\tt PYTHONPATH}
|
|
is not set.
|
|
You can modify it using standard list operations, e.g.:
|
|
\bcode\begin{verbatim}
|
|
>>> import sys
|
|
>>> sys.path.append('/ufs/guido/lib/python')
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsection{Errors and Exceptions}
|
|
|
|
Until now error messages haven't yet been mentioned, but if you have
|
|
tried out the examples you have probably seen some.
|
|
There are (at least) two distinguishable kinds of errors:
|
|
{\em syntax\ errors}
|
|
and
|
|
{\em exceptions}.
|
|
|
|
\subsubsection{Syntax Errors}
|
|
|
|
Syntax errors, also known as parsing errors, are perhaps the most common
|
|
kind of complaint you get while you are still learning Python:
|
|
\bcode\begin{verbatim}
|
|
>>> while 1 print 'Hello world'
|
|
Parsing error: file <stdin>, line 1:
|
|
while 1 print 'Hello world'
|
|
^
|
|
Unhandled exception: run-time error: syntax error
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The parser repeats the offending line and displays a little `arrow'
|
|
pointing at the earliest point in the line where the error was detected.
|
|
The error is caused by (or at least detected at) the token
|
|
{\em preceding}
|
|
the arrow: in the example, the error is detected at the keyword
|
|
{\tt print}, since a colon ({\tt :}) is missing before it.
|
|
File name and line number are printed so you know where to look in case
|
|
the input came from a script.
|
|
|
|
\subsubsection{Exceptions}
|
|
|
|
Even if a statement or expression is syntactically correct, it may cause
|
|
an error when an attempt is made to execute it:
|
|
\bcode\small\begin{verbatim}
|
|
>>> 10 * (1/0)
|
|
Unhandled exception: run-time error: integer division by zero
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 1
|
|
>>> 4 + foo*3
|
|
Unhandled exception: undefined name: foo
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 1
|
|
>>> '2' + 2
|
|
Unhandled exception: type error: illegal argument type for built-in operation
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Errors detected during execution are called
|
|
{\em exceptions}
|
|
and are not unconditionally fatal: you will soon learn how to handle
|
|
them in Python programs.
|
|
Most exceptions are not handled by programs, however, and result
|
|
in error messages as shown here.
|
|
|
|
The first line of the error message indicates what happened.
|
|
Exceptions come in different types, and the type is printed as part of
|
|
the message: the types in the example are
|
|
{\tt run-time error},
|
|
{\tt undefined name}
|
|
and
|
|
{\tt type error}.
|
|
The rest of the line is a detail whose interpretation depends on the
|
|
exception type.
|
|
|
|
The rest of the error message shows the context where the
|
|
exception happened.
|
|
In general it contains a stack backtrace listing source lines; however,
|
|
it will not display lines read from standard input.
|
|
|
|
Here is a summary of the most common exceptions:
|
|
\begin{itemize}
|
|
\item
|
|
{\em Run-time\ errors}
|
|
are generally caused by wrong data used by the program; this can be the
|
|
programmer's fault or caused by bad input.
|
|
The detail states the cause of the error in more detail.
|
|
\item
|
|
{\em Undefined\ name}
|
|
errors are more serious: these are usually caused by misspelled
|
|
identifiers.%
|
|
\footnote{
|
|
The parser does not check whether names used in a program are at
|
|
all defined elsewhere in the program, so such checks are
|
|
postponed until run-time. The same holds for type checking.
|
|
}
|
|
The detail is the offending identifier.
|
|
\item
|
|
{\em Type\ errors}
|
|
are also pretty serious: this is another case of using wrong data (or
|
|
better, using data the wrong way), but here the error can be glanced
|
|
from the object type(s) alone.
|
|
The detail shows in what context the error was detected.
|
|
\end{itemize}
|
|
|
|
\subsubsection{Handling Exceptions}
|
|
|
|
It is possible to write programs that handle selected exceptions.
|
|
Look at the following example, which prints a table of inverses of
|
|
some floating point numbers:
|
|
\bcode\begin{verbatim}
|
|
>>> numbers = [0.3333, 2.5, 0.0, 10.0]
|
|
>>> for x in numbers:
|
|
... print x,
|
|
... try:
|
|
... print 1.0 / x
|
|
... except RuntimeError:
|
|
... print '*** has no inverse ***'
|
|
...
|
|
0.3333 3.00030003
|
|
2.5 0.4
|
|
0 *** has no inverse ***
|
|
10 0.1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The {\tt try} statement works as follows.
|
|
\begin{itemize}
|
|
\item
|
|
First, the
|
|
{\em try\ clause}
|
|
(the statement(s) between the {\tt try} and {\tt except} keywords) is
|
|
executed.
|
|
\item
|
|
If no exception occurs, the
|
|
{\em except\ clause}
|
|
is skipped and execution of the {\tt try} statement is finished.
|
|
\item
|
|
If an exception occurs during execution of the try clause, and its
|
|
type matches the exception named after the {\tt except} keyword, the
|
|
rest of the try clause is skipped, the except clause is executed, and
|
|
then execution continues after the {\tt try} statement.
|
|
\item
|
|
If an exception occurs which does not match the exception named in the
|
|
except clause, it is passed on to outer try statements; if no handler is
|
|
found, it is an
|
|
{\em unhandled\ exception}
|
|
and execution stops with a message as shown above.
|
|
\end{itemize}
|
|
A {\tt try} statement may have more than one except clause, to specify
|
|
handlers for different exceptions.
|
|
At most one handler will be executed.
|
|
Handlers only handle exceptions that occur in the corresponding try
|
|
clause, not in other handlers of the same {\tt try} statement.
|
|
An except clause may name multiple exceptions as a parenthesized list,
|
|
e.g.:
|
|
\bcode\begin{verbatim}
|
|
... except (RuntimeError, TypeError, NameError):
|
|
... pass
|
|
\end{verbatim}\ecode
|
|
The last except clause may omit the exception name(s), to serve as a
|
|
wildcard.
|
|
Use this with extreme caution!
|
|
|
|
When an exception occurs, it may have an associated value, also known as
|
|
the exceptions's
|
|
{\em argument}.
|
|
The presence and type of the argument depend on the exception type.
|
|
For exception types which have an argument, the except clause may
|
|
specify a variable after the exception name (or list) to receive the
|
|
argument's value, as follows:
|
|
\bcode\begin{verbatim}
|
|
>>> try:
|
|
... foo()
|
|
... except NameError, x:
|
|
... print 'name', x, 'undefined'
|
|
...
|
|
name foo undefined
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
If an exception has an argument, it is printed as the third part
|
|
(`detail') of the message for unhandled exceptions.
|
|
|
|
Standard exception names are built-in identifiers (not reserved
|
|
keywords).
|
|
These are in fact string objects whose
|
|
{\em object\ identity}
|
|
(not their value!) identifies the exceptions.%
|
|
\footnote{
|
|
There should really be a separate exception type; it is pure
|
|
laziness that exceptions are identified by strings, and this may
|
|
be fixed in the future.
|
|
}
|
|
The string is printed as the second part of the message for unhandled
|
|
exceptions.
|
|
Their names and values are:
|
|
\bcode\begin{verbatim}
|
|
EOFError 'end-of-file read'
|
|
KeyboardInterrupt 'keyboard interrupt'
|
|
MemoryError 'out of memory' *
|
|
NameError 'undefined name' *
|
|
RuntimeError 'run-time error' *
|
|
SystemError 'system error' *
|
|
TypeError 'type error' *
|
|
\end{verbatim}\ecode
|
|
The meanings should be clear enough.
|
|
Those exceptions with a {\tt *} in the third column have an argument.
|
|
|
|
Exception handlers don't just handle exceptions if they occur
|
|
immediately in the try clause, but also if they occur inside functions
|
|
that are called (even indirectly) in the try clause.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> def this_fails():
|
|
... x = 1/0
|
|
...
|
|
>>> try:
|
|
... this_fails()
|
|
... except RuntimeError, detail:
|
|
... print 'Handling run-time error:', detail
|
|
...
|
|
Handling run-time error: integer division by zero
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
|
|
\subsubsection{Raising Exceptions}
|
|
|
|
The {\tt raise} statement allows the programmer to force a specified
|
|
exception to occur.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> raise NameError, 'Hi There!'
|
|
Unhandled exception: undefined name: Hi There!
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 1
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The first argument to {\tt raise} names the exception to be raised.
|
|
The optional second argument specifies the exception's argument.
|
|
|
|
\subsubsection{User-defined Exceptions}
|
|
|
|
Programs may name their own exceptions by assigning a string to a
|
|
variable.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> my_exc = 'nobody likes me!'
|
|
>>> try:
|
|
... raise my_exc, 2*2
|
|
... except my_exc, val:
|
|
... print 'My exception occurred, value:', val
|
|
...
|
|
My exception occured, value: 4
|
|
>>> raise my_exc, 1
|
|
Unhandled exception: nobody likes me!: 1
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 7
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
Many standard modules use this to report errors that may occur in
|
|
functions they define.
|
|
|
|
\subsubsection{Defining Clean-up Actions}
|
|
|
|
The {\tt try} statement has another optional clause which is intended to
|
|
define clean-up actions that must be executed under all circumstances.
|
|
For example:
|
|
\bcode\begin{verbatim}
|
|
>>> try:
|
|
... raise KeyboardInterrupt
|
|
... finally:
|
|
... print 'Goodbye, world!'
|
|
...
|
|
Goodbye, world!
|
|
Unhandled exception: keyboard interrupt
|
|
Stack backtrace (innermost last):
|
|
File "<stdin>", line 2
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
The
|
|
{\em finally\ clause}
|
|
must follow the except clauses(s), if any.
|
|
It is executed whether or not an exception occurred.
|
|
If the exception is handled, the finally clause is executed after the
|
|
handler (and even if another exception occurred in the handler).
|
|
It is also executed when the {\tt try} statement is left via a
|
|
{\tt break} or {\tt return} statement.
|
|
|
|
\subsection{Classes}
|
|
|
|
Classes in Python make it possible to play the game of encapsulation in a
|
|
somewhat different way than it is played with modules.
|
|
Classes are an advanced topic and are probably best skipped on the first
|
|
encounter with Python.
|
|
|
|
\subsubsection{Prologue}
|
|
|
|
Python's class mechanism is not particularly elegant, but quite powerful.
|
|
It is a mixture of the class mechanisms found in C++ and Modula-3.
|
|
As is true for modules, classes in Python do not put an absolute barrier
|
|
between definition and user, but rather rely on the politeness of the
|
|
user not to ``break into the definition.''
|
|
The most important features of classes are retained with full power,
|
|
however: the class inheritance mechanism allows multiple base classes,
|
|
a derived class can override any method of its base class(es), a method
|
|
can call the method of a base class with the same name.
|
|
Objects can contain an arbitrary amount of private data.
|
|
|
|
In C++ terminology, all class members (including data members) are
|
|
{\em public},
|
|
and all member functions (methods) are
|
|
{\em virtual}.
|
|
There are no special constructors or destructors.
|
|
As in Modula-3, there are no shorthands for referencing the object's
|
|
members from its methods: the method function is declared with an
|
|
explicit first argument representing the object, which is provided
|
|
implicitly by the call.
|
|
As in Smalltalk, classes themselves are objects, albeit in the wider
|
|
sense of the word: in Python, all data types are objects.
|
|
This provides semantics for renaming or aliasing.
|
|
But, just like in C++ or Modula-3, the built-in types cannot be used as
|
|
base classes for extension by the user.
|
|
Also, like Modula-3 but unlike C++, the built-in operators with special
|
|
syntax (arithmetic operators, subscripting etc.) cannot be redefined for
|
|
class members.%
|
|
\footnote{
|
|
They can be redefined for new object types implemented in C in
|
|
extensions to the interpreter, however. It would require only a
|
|
naming convention and a relatively small change to the
|
|
interpreter to allow operator overloading for classes, so
|
|
perhaps someday...
|
|
}
|
|
|
|
\subsubsection{A Simple Example}
|
|
|
|
Consider the following example, which defines a class {\tt Set}
|
|
representing a (finite) mathematical set with operations to add and
|
|
remove elements, a membership test, and a request for the size of the
|
|
set.
|
|
\bcode\begin{verbatim}
|
|
class Set():
|
|
def new(self):
|
|
self.elements = []
|
|
return self
|
|
def add(self, e):
|
|
if e not in self.elements:
|
|
self.elements.append(e)
|
|
def remove(self, e):
|
|
if e in self.elements:
|
|
for i in range(len(self.elements)):
|
|
if self.elements[i] = e:
|
|
del self.elements[i]
|
|
break
|
|
def is_element(self, e):
|
|
return e in self.elements
|
|
def size(self):
|
|
return len(self.elements)
|
|
\end{verbatim}\ecode
|
|
Note that the class definition looks like a big compound statement,
|
|
with all the function definitons indented repective to the
|
|
{\tt class}
|
|
keyword.
|
|
|
|
Let's assume that this
|
|
{\em class\ definition}
|
|
is the only contents of the module file
|
|
{\tt SetClass.py}.
|
|
We can then use it in a Python program as follows:
|
|
\bcode\begin{verbatim}
|
|
>>> from SetClass import Set
|
|
>>> a = Set().new() # create a Set object
|
|
>>> a.add(2)
|
|
>>> a.add(3)
|
|
>>> a.add(1)
|
|
>>> a.add(1)
|
|
>>> if a.is_element(3): print '3 is in the set'
|
|
...
|
|
3 is in the set
|
|
>>> if not a.is_element(4): print '4 is not in the set'
|
|
...
|
|
4 is not in the set
|
|
>>> print 'a has', a.size(), 'elements'
|
|
a has 3 elements
|
|
>>> a.remove(1)
|
|
>>> print 'now a has', a.size(), 'elements'
|
|
>>>
|
|
now a has 2 elements
|
|
>>>
|
|
\end{verbatim}\ecode
|
|
From the example we learn in the first place that the functions defined
|
|
in the class (e.g.,
|
|
{\tt add})
|
|
can be called using the
|
|
{\em member}
|
|
notation for the object
|
|
{\tt a}.
|
|
The member function is called with one less argument than it is defined:
|
|
the object is implicitly passed as the first argument.
|
|
Thus, the call
|
|
{\tt a.add(2)}
|
|
is equivalent to
|
|
{\tt Set.add(a, 2)}.
|
|
|
|
XXX This section is not complete yet! Inheritance!
|
|
|
|
\section{XXX P.M.}
|
|
|
|
\begin{itemize}
|
|
\item The {\tt del} statement.
|
|
\item The {\tt dir()} function.
|
|
\item Tuples.
|
|
\item Dictionaries.
|
|
\item Objects and types in general.
|
|
\item Backquotes.
|
|
\item Output formatting.
|
|
\item And/Or/Not.
|
|
\item ``.pyc'' files.
|
|
\end{itemize}
|
|
|
|
\end{document}
|