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Moved author and date to boilerplate.tex.
Added copyright.tex to all files. Added descr of check_interval to libsys.tex. Corrected lotsa typos in tut.tex (thanks to George M. Sipe). Corrected mktuple (should be newtupleobject) example in ext.tex.
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14 changed files with 132 additions and 90 deletions
37
Doc/tut.tex
37
Doc/tut.tex
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@ -1,15 +1,8 @@
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\documentstyle[twoside,11pt,myformat]{report}
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\title{Python Tutorial}
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\author{
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Guido van Rossum \\
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Dept. CST, CWI, P.O. Box 94079 \\
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1090 GB Amsterdam, The Netherlands \\
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E-mail: {\tt guido@cwi.nl}
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}
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\date{14 July 1994 \\ Release 1.0.3} % XXX update before release!
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\input{boilerplate}
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\begin{document}
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@ -17,6 +10,8 @@
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\maketitle
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\input{copyright}
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\begin{abstract}
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\noindent
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@ -791,7 +786,7 @@ assignments take place.
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\item
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The {\tt while} loop executes as long as the condition (here: {\tt b <
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100}) remains true. In Python, like in C, any non-zero integer value is
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10}) remains true. In Python, like in C, any non-zero integer value is
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true; zero is false. The condition may also be a string or list value,
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in fact any sequence; anything with a non-zero length is true, empty
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sequences are false. The test used in the example is a simple
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@ -813,7 +808,7 @@ line).
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The {\tt print} statement writes the value of the expression(s) it is
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given. It differs from just writing the expression you want to write
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(as we did earlier in the calculator examples) in the way it handles
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multiple expressions and strings. Strings are written without quotes,
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multiple expressions and strings. Strings are printed without quotes,
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and a space is inserted between items, so you can format things nicely,
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like this:
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@ -1007,7 +1002,7 @@ arbitrary boundary:
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\bcode\begin{verbatim}
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>>> def fib(n): # write Fibonacci series up to n
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... a, b = 0, 1
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... while b <= n:
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... while b < n:
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... print b,
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... a, b = b, a+b
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...
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@ -1084,7 +1079,7 @@ the Fibonacci series, instead of printing it:
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>>> def fib2(n): # return Fibonacci series up to n
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... result = []
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... a, b = 0, 1
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... while b <= n:
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... while b < n:
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... result.append(b) # see below
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... a, b = b, a+b
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... return result
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@ -1359,7 +1354,7 @@ only matters for mutable objects like lists. All comparison operators
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have the same priority, which is lower than that of all numerical
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operators.
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Comparisons can be chained: e.g., {\tt a < b = c} tests whether {\tt a}
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Comparisons can be chained: e.g., {\tt a < b == c} tests whether {\tt a}
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is less than {\tt b} and moreover {\tt b} equals {\tt c}.
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Comparisons may be combined by the Boolean operators {\tt and} and {\tt
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@ -1460,14 +1455,14 @@ with the following contents:
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def fib(n): # write Fibonacci series up to n
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a, b = 0, 1
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while b <= n:
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while b < n:
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print b,
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a, b = b, a+b
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def fib2(n): # return Fibonacci series up to n
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result = []
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a, b = 0, 1
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while b <= n:
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while b < n:
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result.append(b)
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a, b = b, a+b
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return result
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@ -2101,7 +2096,7 @@ may change in the future. Examples of name spaces are: the set of
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built-in names (functions such as \verb\abs()\, and built-in exception
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names); the global names in a module; and the local names in a
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function invocation. In a sense the set of attributes of an object
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also form a name space. The important things to know about name
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also form a name space. The important thing to know about name
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spaces is that there is absolutely no relation between names in
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different name spaces; for instance, two different modules may both
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define a function ``maximize'' without confusion --- users of the
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@ -2162,7 +2157,7 @@ names, and the outermost scope (searched last) is the name space
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containing built-in names.
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Usually, the local scope references the local names of the (textually)
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current function. Outside functions, the the local scope references
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current function. Outside of functions, the the local scope references
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the same name space as the global scope: the module's name space.
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Class definitions place yet another name space in the local scope.
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@ -2643,7 +2638,7 @@ Python is an evolving language. Since this tutorial was last
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thoroughly revised, several new features have been added to the
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language. While ideally I should revise the tutorial to incorporate
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them in the mainline of the text, lack of time currently requires me
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to follow a more modest approach. In this chapter I will briefly list the
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to take a more modest approach. In this chapter I will briefly list the
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most important improvements to the language and how you can use them
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to your benefit.
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@ -2984,7 +2979,9 @@ Reference for a full description.
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\section{Generalized Dictionaries}
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The keys of dictionaries are no longer restricted to strings -- they
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can be numbers, tuples, or (certain) class instances. (Lists and
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can be
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any immutable basic type including strings,
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numbers, tuples, or (certain) class instances. (Lists and
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dictionaries are not acceptable as dictionary keys, in order to avoid
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problems when the object used as a key is modified.)
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@ -3007,7 +3004,7 @@ operations are slow for large dictionaries. Examples:
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\section{Miscellaneous New Built-in Functions}
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The function \verb\vars()\ returns a dictionary containing the current
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local variables. With a module as argument, it returns that module's
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local variables. With a module argument, it returns that module's
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global variables. The old function \verb\dir(x)\ returns
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\verb\vars(x).keys()\.
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