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Old 09-18-2008, 06:38 AM
rabi
 
Default chapter4

4. More Control Flow Tools

Besides the while statement just introduced, Python knows the usual
control flow statements known from other languages, with some twists.


4.1 if Statements

Perhaps the most well-known statement type is the if statement. For
example:

>>> x = int(raw_input("Please enter an integer: "))
>>> if x < 0:
... x = 0
... print 'Negative changed to zero'
... elif x == 0:
... print 'Zero'
... elif x == 1:
... print 'Single'
... else:
... print 'More'
...

There can be zero or more elif parts, and the else part is optional.
The keyword `elif' is short for `else if', and is useful to avoid
excessive indentation. An if ... elif ... elif ... sequence is a
substitute for the switch or case statements found in other languages.


4.2 for Statements

The 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 giving the user the
ability to define both the iteration step and halting condition (as
C), Python's for statement iterates over the items of any sequence (a
list or a string), in the order that they appear in the sequence. For
example (no pun intended):

>>> # Measure some strings:
... a = ['cat', 'window', 'defenestrate']
>>> for x in a:
... print x, len(x)
...
cat 3
window 6
defenestrate 12

It is not safe to modify the sequence being iterated over in the loop
(this can only happen for mutable sequence types, such as lists). If
you need to modify the list you are iterating over (for example, to
duplicate selected items) you must iterate over a copy. The slice
notation makes this particularly convenient:

>>> 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']


4.3 The range() Function

If you do need to iterate over a sequence of numbers, the built-in
function range() comes in handy. It generates lists containing
arithmetic progressions:

>>> range(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

The given end point is never part of the generated list; 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;
sometimes this is called the `step'):

>>> range(5, 10)
[5, 6, 7, 8, 9]
>>> range(0, 10, 3)
[0, 3, 6, 9]
>>> range(-10, -100, -30)
[-10, -40, -70]

To iterate over the indices of a sequence, combine range() and len()
as follows:

>>> 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


4.4 break and continue Statements, and else Clauses on Loops

The break statement, like in C, breaks out of the smallest enclosing
for or while loop.

The continue statement, also borrowed from C, continues with the next
iteration of the loop.

Loop statements may have an else clause; it is executed when the loop
terminates through exhaustion of the list (with for) or when the
condition becomes false (with while), but not when the loop is
terminated by a break statement. This is exemplified by the following
loop, which searches for prime numbers:

>>> for n in range(2, 10):
... for x in range(2, n):
... if n % x == 0:
... print n, 'equals', x, '*', n/x
... break
... else:
... # loop fell through without finding a factor
... 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


4.5 pass Statements

The pass statement does nothing. It can be used when a statement is
required syntactically but the program requires no action. For
example:

>>> while 1:
... pass # Busy-wait for keyboard interrupt
...


4.6 Defining Functions

We can create a function that writes the Fibonacci series to an
arbitrary boundary:

>>> 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

The keyword def introduces a function 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, and must be indented. The first statement of the function body
can optionally be a string literal; this string literal is the
function's documentation string, or docstring.

There are tools which use docstrings to automatically produce online
or 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 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 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 call by value (where the value is always an
object reference, not the value of the object).4.1 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:

>>> fib
<function object at 10042ed0>
>>> f = fib
>>> f(100)
1 1 2 3 5 8 13 21 34 55 89

You might object that 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 None (it's a built-in
name). Writing the value None is normally suppressed by the
interpreter if it would be the only value written. You can see it if
you really want to:

>>> print fib(0)
None

It is simple to write a function that returns a list of the numbers of
the Fibonacci series, instead of printing it:

>>> 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]

This example, as usual, demonstrates some new Python features:

* The return statement returns with a value from a function.
return without an expression argument returns None. Falling off the
end of a procedure also returns None.

* The statement result.append(b) calls a method of the list object
result. A method is a function that `belongs' to an object and is
named obj.methodname, where obj is some object (this may be an
expression), and 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
classes, as discussed later in this tutorial.) The 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
"result = result + [b]", but more efficient.


4.7 More on Defining Functions

It is also possible to define functions with a variable number of
arguments. There are three forms, which can be combined.


4.7.1 Default Argument Values

The most useful form is to specify a default value for one or more
arguments. This creates a function that can be called with fewer
arguments than it is defined

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

This function can be called either like this: ask_ok('Do you really
want to quit?') or like this: ask_ok('OK to overwrite the file?', 2).

The default values are evaluated at the point of function definition
in the defining scope, so that

i = 5

def f(arg=i):
print arg

i = 6
f()

will print 5.

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:

def f(a, L=[]):
L.append(a)
return L

print f(1)
print f(2)
print f(3)

This will print

[1]
[1, 2]
[1, 2, 3]

If you don't want the default to be shared between subsequent calls,
you can write the function like this instead:

def f(a, L=None):
if L is None:
L = []
L.append(a)
return L


4.7.2 Keyword Arguments

Functions can also be called using keyword arguments of the form
"keyword = value". For instance, the following function:

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, "!"

could be called in any of the following ways:

parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')

but the following calls would all be invalid:

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

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 may receive a value
more than once -- formal parameter names corresponding to positional
arguments cannot be used as keywords in the same calls. Here's an
example that fails due to this restriction:

>>> def function(a):
... pass
...
>>> function(0, a=0)
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: keyword parameter redefined

When a final formal parameter of the form **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 *name (described in the next subsection)
which receives a tuple containing the positional arguments beyond the
formal parameter list. (*name must occur before **name.) For example,
if we define a function like this:

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
keys = keywords.keys()
keys.sort()
for kw in keys: print kw, ':', keywords[kw]

It could be called like this:

cheeseshop('Limburger', "It's very runny, sir.",
"It's really very, VERY runny, sir.",
client='John Cleese',
shopkeeper='Michael Palin',
sketch='Cheese Shop Sketch')

and of course it would print:

-- 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

Note that the sort() method of the list of keyword argument names is
called before printing the contents of the keywords dictionary; if
this is not done, the order in which the arguments are printed is
undefined.


4.7.3 Arbitrary Argument Lists

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.

def fprintf(file, format, *args):
file.write(format % args)


4.7.4 Lambda Forms

By popular demand, a few features commonly found in functional
programming languages and Lisp have been added to Python. With the
lambda keyword, small anonymous functions can be created. Here's a
function that returns the sum of its two arguments: "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 can
reference variables from the containing scope:

>>> def make_incrementor(n):
... return lambda x: x + n
...
>>> f = make_incrementor(42)
>>> f(0)
42
>>> f(1)
43


4.7.5 Documentation Strings

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 or more paragraphs
describing the object's 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 if desired. This is done using the following convention.
The first non-blank line 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).

Here is an example of a multi-line docstring:

>>> def my_function():
... """Do nothing, but document it.
...
... No, really, it doesn't do anything.
... """
... pass
...
>>> print my_function.__doc__
Do nothing, but document it.

No, really, it doesn't do anything.


Footnotes

... object).4.1
Actually, 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 (items inserted into a list).
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