.. _tut-morecontrol:

***********************

More Control Flow Tools

***********************

Besides the :keyword:`while` statement just introduced, Python knows the usual

control flow statements known from other languages, with some twists.

.. _tut-if:

:keyword:`if` Statements

========================

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

example::

   >>> x = int(raw_input("Please enter an integer: "))

   Please enter an integer: 42

   >>> if x < 0:

   ...      x = 0

   ...      print 'Negative changed to zero'

   ... elif x == 0:

   ...      print 'Zero'

   ... elif x == 1:

   ...      print 'Single'

   ... else:

   ...      print 'More'

   ...

   More

There can be zero or more :keyword:`elif` parts, and the :keyword:`else` part is

optional.  The keyword ':keyword:`elif`' is short for 'else if', and is useful

to avoid excessive indentation.  An  :keyword:`if` ... :keyword:`elif` ...

:keyword:`elif` ... sequence is a substitute for the ``switch`` or

``case`` statements found in other languages.

.. _tut-for:

:keyword:`for` Statements

=========================

.. index::

   statement: for

   statement: for

The :keyword:`for` statement in Python differs a bit from what you may be used

to in C or Pascal.  Rather than always iterating over an arithmetic progression

of numbers (like in Pascal), or giving the user the ability to define both the

iteration step and halting condition (as C), Python's :keyword:`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):

.. One suggestion was to give a real C example here, but that may only serve to

   confuse non-C programmers.

::

   >>> # 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']

.. _tut-range:

The :func:`range` Function

==========================

If you do need to iterate over a sequence of numbers, the built-in function

:func:`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, 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 :func:`range` and :func:`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

.. _tut-break:

:keyword:`break` and :keyword:`continue` Statements, and :keyword:`else` Clauses on Loops

=========================================================================================

The :keyword:`break` statement, like in C, breaks out of the smallest enclosing

:keyword:`for` or :keyword:`while` loop.

The :keyword:`continue` statement, also borrowed from C, continues with the next

iteration of the loop.

Loop statements may have an ``else`` clause; it is executed when the loop

terminates through exhaustion of the list (with :keyword:`for`) or when the

condition becomes false (with :keyword:`while`), but not when the loop is

terminated by a :keyword:`break` statement.  This is exemplified by the

following loop, which searches for prime numbers::

   >>> 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

.. _tut-pass:

:keyword:`pass` Statements

==========================

The :keyword:`pass` statement does nothing. It can be used when a statement is

required syntactically but the program requires no action. For example::

   >>> while True:

   ...     pass  # Busy-wait for keyboard interrupt (Ctrl+C)

   ... 

This is commonly used for creating minimal classes such as exceptions, or

for ignoring unwanted exceptions::

   >>> class ParserError(Exception):

   ...     pass

   ... 

   >>> try:

   ...     import audioop

   ... except ImportError:

   ...     pass

   ... 

Another place :keyword:`pass` can be used is as a place-holder for a function or

conditional body when you are working on new code, allowing you to keep

thinking at a more abstract level.  However, as :keyword:`pass` is silently

ignored, a better choice may be to raise a :exc:`NotImplementedError`

exception::

   >>> def initlog(*args):

   ...     raise NotImplementedError   # Open logfile if not already open

   ...     if not logfp:

   ...         raise NotImplementedError  # Set up dummy log back-end

   ...     raise NotImplementedError('Call log initialization handler')

   ... 

If :keyword:`pass` were used here and you later ran tests, they may fail

without indicating why.  Using :exc:`NotImplementedError` causes this code

to raise an exception, telling you exactly where the incomplete code 

is.  Note the two calling styles of the exceptions above.

The first style, with no message but with an accompanying comment, 

lets you easily leave the comment when you remove the exception,

which ideally would be a good description for

the block of code the exception is a placeholder for.  However, the 

third example, providing a message for the exception, will produce 

a more useful traceback.

.. _tut-functions:

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

.. index::

   single: documentation strings

   single: docstrings

   single: strings, documentation

The keyword :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 :dfn:`docstring`.

(More about docstrings can be found in the section :ref:`tut-docstrings`.)

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 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 local symbol tables of

enclosing functions, then in the global symbol table, and finally in the table

of built-in names. Thus, global variables cannot be directly assigned a value

within a function (unless named in a :keyword:`global` statement), although they

may be referenced.

The actual parameters (arguments) to a function call are introduced in the local

symbol table of the called function when it is called; thus, arguments are

passed using *call by value* (where the *value* is always an object *reference*,

not the value of the object). [#]_ 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 fib at 10042ed0>

   >>> f = fib

   >>> f(100)

   1 1 2 3 5 8 13 21 34 55 89

Coming from other languages, you might object that ``fib`` is not a function but

a procedure since it doesn't return a value.  In fact, even functions without a

:keyword:`return` statement 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 using :keyword:`print`::

   >>> fib(0)

   >>> 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 :keyword:`return` statement returns with a value from a function.

  :keyword:`return` without an expression argument returns ``None``. Falling off

  the end of a function 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 :meth:`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.

.. _tut-defining:

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.

.. _tut-defaultargs:

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 to allow.  For example::

   def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):

       while True:

           ok = raw_input(prompt)

           if ok in ('y', 'ye', 'yes'): return True

           if ok in ('n', 'no', 'nop', 'nope'): return False

           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)``.

This example also introduces the :keyword:`in` keyword. This tests whether or

not a sequence contains a certain value.

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, dictionary, or

instances of most classes.  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

.. _tut-keywordargs:

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: function() got multiple values for keyword argument 'a'

When a final formal parameter of the form ``**name`` is present, it receives a

dictionary (see :ref:`typesmapping`) containing all keyword arguments except for

those corresponding 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.",

              shopkeeper='Michael Palin',

              client="John Cleese",

              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 :meth:`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.

.. _tut-arbitraryargs:

Arbitrary Argument Lists

------------------------

.. index::

  statement: *  

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 (see :ref:`tut-tuples`).  Before the variable number of arguments,

zero or more normal arguments may occur. ::

   def write_multiple_items(file, separator, *args):

       file.write(separator.join(args))

.. _tut-unpacking-arguments:

Unpacking Argument Lists

------------------------

The reverse situation occurs when the arguments are already in a list or tuple

but need to be unpacked for a function call requiring separate positional

arguments.  For instance, the built-in :func:`range` function expects separate

*start* and *stop* arguments.  If they are not available separately, write the

function call with the  ``*``\ -operator to unpack the arguments out of a list

or tuple::

   >>> range(3, 6)             # normal call with separate arguments

   [3, 4, 5]

   >>> args = [3, 6]

   >>> range(*args)            # call with arguments unpacked from a list

   [3, 4, 5]

.. index::

  statement: **

In the same fashion, dictionaries can deliver keyword arguments with the ``**``\

-operator::

   >>> def parrot(voltage, state='a stiff', action='voom'):

   ...     print "-- This parrot wouldn't", action,

   ...     print "if you put", voltage, "volts through it.",

   ...     print "E's", state, "!"

   ...

   >>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}

   >>> parrot(**d)

   -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !

.. _tut-lambda:

Lambda Forms

------------

By popular demand, a few features commonly found in functional programming