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-<body bgcolor="white" text="black" link="#0000FF" vlink="#840084" alink="#0000FF"><span style="color: red"><html><span style="color: red"><body><span style="color: red"><document><span style="color: red"><title>Functional Approach</title></span><span style="color: red"><paragraph><span class="emphasis"><em>Functions</em></span> allow us to enclose a set of statements and call the function again
-and again instead of repeating the group of statements everytime. Functions also
-allow us to isolate a piece of code from all the other code and provides the
-convenience of not polluting the global variables.</paragraph></span><span style="color: red"><paragraph><span class="emphasis"><em>Function</em></span> in python is defined with the keyword <span style="color: red"><strong>def</strong></span> followed by the name
-of the function, in turn followed by a pair of parenthesis which encloses the
-list of parameters to the function. The definition line ends with a ':'. The
-definition line is followed by the body of the function intended by one block.
-The <span class="emphasis"><em>Function</em></span> must return a value:</paragraph></span><span style="color: red"><literal_block>def factorial(n):
- fact = 1
- for i in range(2, n):
- fact *= i
-
- return fact</literal_block></span><span style="color: red"><paragraph>The code snippet above defines a function with the name factorial, takes the
-number for which the factorial must be computed, computes the factorial and
-returns the value.</paragraph></span><span style="color: red"><paragraph>A <span class="emphasis"><em>Function</em></span> once defined can be used or called anywhere else in the program. We
-call a fucntion with its name followed by a pair of parenthesis which encloses
-the arguments to the function.</paragraph></span><span style="color: red"><paragraph>The value that function returns can be assigned to a variable. Let's call the
-above function and store the factorial in a variable:</paragraph></span><span style="color: red"><literal_block>fact5 = factorial(5)</literal_block></span><span style="color: red"><paragraph>The value of fact5 will now be 120, which is the factorial of 5. Note that we
-passed 5 as the argument to the function.</paragraph></span><span style="color: red"><paragraph>It may be necessary to document what the function does, for each of the function
-to help the person who reads our code to understand it better. In order to do
-this Python allows the first line of the function body to be a string. This
-string is called as <span class="emphasis"><em>Documentation String</em></span> or <span class="emphasis"><em>docstring</em></span>. <span class="emphasis"><em>docstrings</em></span> prove
-to be very handy since there are number of tools which can pull out all the
-docstrings from Python functions and generate the documentation automatically
-from it. <span class="emphasis"><em>docstrings</em></span> for functions can be written as follows:</paragraph></span><span style="color: red"><literal_block>def factorial(n):
- 'Returns the factorial for the number n.'
- fact = 1
- for i in range(2, n):
- fact *= i
-
- return fact</literal_block></span><span style="color: red"><paragraph>An important point to note at this point is that, a function can return any
-Python value or a Python object, which also includes a <span class="emphasis"><em>Tuple</em></span>. A <span class="emphasis"><em>Tuple</em></span> is
-just a collection of values and those values themselves can be of any other
-valid Python datatypes, including <span class="emphasis"><em>Lists</em></span>, <span class="emphasis"><em>Tuples</em></span>, <span class="emphasis"><em>Dictionaries</em></span> among other
-things. So effectively, if a function can return a tuple, it can return any
-number of values through a tuple</paragraph></span><span style="color: red"><paragraph>Let us write a small function to swap two values:</paragraph></span><span style="color: red"><literal_block>def swap(a, b):
- return b, a
-
-c, d = swap(a, b)</literal_block></span><div class="section" title="1. Function scope">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2981898"></a>1. Function scope</h2></div></div></div>
-<span style="color: red"><paragraph>The variables used inside the function are confined to the function's scope
-and doesn't pollute the variables of the same name outside the scope of the
-function. Also the arguments passed to the function are passed by-value if
-it is of basic Python data type:</paragraph></span><span style="color: red"><literal_block>def cant_change(n):
- n = 10
-
-n = 5
-cant_change(n)</literal_block></span><span style="color: red"><paragraph>Upon running this code, what do you think would have happened to value of n
-which was assigned 5 before the function call? If you have already tried out
-that snippet on the interpreter you already know that the value of n is not
-changed. This is true of any immutable types of Python like <span class="emphasis"><em>Numbers</em></span>, <span class="emphasis"><em>Strings</em></span>
-and <span class="emphasis"><em>Tuples</em></span>. But when you pass mutable objects like <span class="emphasis"><em>Lists</em></span> and <span class="emphasis"><em>Dictionaries</em></span>
-the values are manipulated even outside the function:</paragraph></span><span style="color: red"><literal_block>>>> def can_change(n):
-... n[1] = James
-...
-
->>> name = ['Mr.', 'Steve', 'Gosling']
->>> can_change(name)
->>> name
-['Mr.', 'James', 'Gosling']</literal_block></span><span style="color: red"><paragraph>If nothing is returned by the function explicitly, Python takes care to return
-None when the funnction is called.</paragraph></span>
-</div>
-<div class="section" title="2. Default Arguments">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2981970"></a>2. Default Arguments</h2></div></div></div>
-<span style="color: red"><paragraph>There may be situations where we need to allow the functions to take the
-arguments optionally. Python allows us to define function this way by providing
-a facility called <span class="emphasis"><em>Default Arguments</em></span>. For example, we need to write a function
-that returns a list of fibonacci numbers. Since our function cannot generate an
-infinite list of fibonacci numbers, we need to specify the number of elements
-that the fibonacci sequence must contain. Suppose, additionally, we want to the
-function to return 10 numbers in the sequence if no option is specified we can
-define the function as follows:</paragraph></span><span style="color: red"><literal_block>def fib(n=10):
- fib_list = [0, 1]
- for i in range(n - 2):
- next = fib_list[-2] + fib_list[-1]
- fib_list.append(next)
- return fib_list</literal_block></span><span style="color: red"><paragraph>When we call this function, we can optionally specify the value for the
-parameter n, during the call as an argument. Calling with no argument and
-argument with n=5 returns the following fibonacci sequences:</paragraph></span><span style="color: red"><literal_block>fib()
-[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
-fib(5)
-[0, 1, 1, 2, 3]</literal_block></span>
-</div>
-<div class="section" title="3. Keyword Arguments">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2981995"></a>3. Keyword Arguments</h2></div></div></div>
-<span style="color: red"><paragraph>When a function takes a large number of arguments, it may be difficult to
-remember the order of the parameters in the function definition or it may
-be necessary to pass values to only certain parameters since others take
-the default value. In either of these cases, Python provides the facility
-of passing arguments by specifying the name of the parameter as defined in
-the function definition. This is known as <span class="emphasis"><em>Keyword Arguments</em></span>.</paragraph></span><span style="color: red"><paragraph>In a function call, <span class="emphasis"><em>Keyword arguments</em></span> can be used for each argument, in the
-following fashion:</paragraph></span><span style="color: red"><literal_block>argument_name=argument_value
-Also denoted as: keyword=argument
-
-def wish(name='World', greetings='Hello'):
- print "%s, %s!" % (greetings, name)</literal_block></span><span style="color: red"><paragraph>This function can be called in one of the following ways. It is important to
-note that no restriction is imposed in the order in which <span class="emphasis"><em>Keyword arguments</em></span>
-can be specified. Also note, that we have combined <span class="emphasis"><em>Keyword arguments</em></span> with
-<span class="emphasis"><em>Default arguments</em></span> in this example, however it is not necessary:</paragraph></span><span style="color: red"><literal_block>wish(name='Guido', greetings='Hey')
-wish(greetings='Hey', name='Guido')</literal_block></span><span style="color: red"><paragraph>Calling functions by specifying arguments in the order of parameters specified
-in the function definition is called as <span class="emphasis"><em>Positional arguments</em></span>, as opposed to
-<span class="emphasis"><em>Keyword arguments</em></span>. It is possible to use both <span class="emphasis"><em>Positional arguments</em></span> and
-<span class="emphasis"><em>Keyword arguments</em></span> in a single function call. But Python doesn't allow us to
-bungle up both of them. The arguments to the function, in the call, must always
-start with <span class="emphasis"><em>Positional arguments</em></span> which is in turn followed by <span class="emphasis"><em>Keyword
-arguments</em></span>:</paragraph></span><span style="color: red"><literal_block>def my_func(x, y, z, u, v, w):
- # initialize variables.
- ...
- # do some stuff
- ...
- # return the value</literal_block></span><span style="color: red"><paragraph>It is valid to call the above functions in the following ways:</paragraph></span><span style="color: red"><literal_block>my_func(10, 20, 30, u=1.0, v=2.0, w=3.0)
-my_func(10, 20, 30, 1.0, 2.0, w=3.0)
-my_func(10, 20, z=30, u=1.0, v=2.0, w=3.0)
-my_func(x=10, y=20, z=30, u=1.0, v=2.0, w=3.0)</literal_block></span><span style="color: red"><paragraph>Following lists some of the invalid calls:</paragraph></span><span style="color: red"><literal_block>my_func(10, 20, z=30, 1.0, 2.0, 3.0)
-my_func(x=10, 20, z=30, 1.0, 2.0, 3.0)
-my_func(x=10, y=20, z=30, u=1.0, v=2.0, 3.0)</literal_block></span>
-</div>
-<div class="section" title="4. Parameter Packing and Unpacking">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2982116"></a>4. Parameter Packing and Unpacking</h2></div></div></div>
-<span style="color: red"><paragraph>The positional arguments passed to a function can be collected in a tuple
-parameter and keyword arguments can be collected in a dictionary. Since keyword
-arguments must always be the last set of arguments passed to a function, the
-keyword dictionary parameter must be the last parameter. The function definition
-must include a list explicit parameters, followed by tuple paramter collecting
-parameter, whose name is preceded by a <span style="color: red"><strong>*</strong></span>, for collecting positional
-parameters, in turn followed by the dictionary collecting parameter, whose name
-is preceded by a <span style="color: red"><strong>**</strong></span></paragraph></span><span style="color: red"><literal_block>def print_report(title, *args, **name):
- """Structure of *args*
- (age, email-id)
- Structure of *name*
- {
- 'first': First Name
- 'middle': Middle Name
- 'last': Last Name
- }
- """
-
- print "Title: %s" % (title)
- print "Full name: %(first)s %(middle)s %(last)s" % name
- print "Age: %d\nEmail-ID: %s" % args</literal_block></span><span style="color: red"><paragraph>The above function can be called as. Note, the order of keyword parameters can
-be interchanged:</paragraph></span><span style="color: red"><literal_block>>>> print_report('Employee Report', 29, 'johny@example.com', first='Johny',
- last='Charles', middle='Douglas')
-Title: Employee Report
-Full name: Johny Douglas Charles
-Age: 29
-Email-ID: johny@example.com</literal_block></span><span style="color: red"><paragraph>The reverse of this can also be achieved by using a very identical syntax while
-calling the function. A tuple or a dictionary can be passed as arguments in
-place of a list of <span class="emphasis"><em>Positional arguments</em></span> or <span class="emphasis"><em>Keyword arguments</em></span> respectively
-using <span style="color: red"><strong>*</strong></span> or <span style="color: red"><strong>**</strong></span></paragraph></span><span style="color: red"><literal_block>def print_report(title, age, email, first, middle, last):
- print "Title: %s" % (title)
- print "Full name: %s %s %s" % (first, middle, last)
- print "Age: %d\nEmail-ID: %s" % (age, email)
-
->>> args = (29, 'johny@example.com')
->>> name = {
- 'first': 'Johny',
- 'middle': 'Charles',
- 'last': 'Douglas'
- }
->>> print_report('Employee Report', *args, **name)
-Title: Employee Report
-Full name: Johny Charles Douglas
-Age: 29
-Email-ID: johny@example.com</literal_block></span>
-</div>
-<div class="section" title="5. Nested Functions and Scopes">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2982188"></a>5. Nested Functions and Scopes</h2></div></div></div>
-<span style="color: red"><paragraph>Python allows nesting one function inside another. This style of programming
-turns out to be extremely flexible and powerful features when we use <span class="emphasis"><em>Python
-decorators</em></span>. We will not talk about decorators is beyond the scope of this
-course. If you are interested in knowing more about <span class="emphasis"><em>decorator programming</em></span> in
-Python you are suggested to read:</paragraph></span><span style="color: red"><line_block><span style="color: red"><line><div class="reference">
-<div class="titlepage"><hr></div>http://avinashv.net/2008/04/python-decorators-syntactic-sugar/</div></line></span><span style="color: red"><line><div class="reference">
-<div class="titlepage"><hr></div>http://personalpages.tds.net/~kent37/kk/00001.html</div></line></span></line_block></span><span style="color: red"><paragraph>However, the following is an example for nested functions in Python:</paragraph></span><span style="color: red"><literal_block>def outer():
- print "Outer..."
- def inner():
- print "Inner..."
- print "Outer..."
- inner()
-
->>> outer()</literal_block></span>
-</div>
-<div class="section" title="6. map, reduce and filter functions">
-<div class="titlepage"><div><div><h2 class="title" style="clear: both">
-<a name="id2982258"></a>6. map, reduce and filter functions</h2></div></div></div>
-<span style="color: red"><paragraph>Python provides several built-in functions for convenience. The <span style="color: red"><strong>map()</strong></span>,
-<span style="color: red"><strong>reduce()</strong></span> and <span style="color: red"><strong>filter()</strong></span> functions prove to be very useful with sequences like
-<span class="emphasis"><em>Lists</em></span>.</paragraph></span><span style="color: red"><paragraph>The <span style="color: red"><strong>map</strong></span> (<span class="emphasis"><em>function</em></span>, <span class="emphasis"><em>sequence</em></span>) function takes two arguments: <span class="emphasis"><em>function</em></span>
-and a <span class="emphasis"><em>sequence</em></span> argument. The <span class="emphasis"><em>function</em></span> argument must be the name of the
-function which in turn takes a single argument, the individual element of the
-<span class="emphasis"><em>sequence</em></span>. The <span style="color: red"><strong>map</strong></span> function calls <span class="emphasis"><em>function(item)</em></span>, for each item in the
-sequence and returns a list of values, where each value is the value returned
-by each call to <span class="emphasis"><em>function(item)</em></span>. <span style="color: red"><strong>map()</strong></span> function allows to pass more than
-one sequence. In this case, the first argument, <span class="emphasis"><em>function</em></span> must take as many
-arguments as the number of sequences passed. This function is called with each
-corresponding element in the each of the sequences, or <span style="color: red"><strong>None</strong></span> if one of the
-sequence is exhausted:</paragraph></span><span style="color: red"><literal_block>def square(x):
- return x*x
-
->>> map(square, [1, 2, 3, 4])
-[1, 4, 9, 16]
-
-def mul(x, y):
- return x*y
-
->>> map(mul, [1, 2, 3, 4], [6, 7, 8, 9])</literal_block></span><span style="color: red"><paragraph>The <span style="color: red"><strong>filter</strong></span> (<span class="emphasis"><em>function</em></span>, <span class="emphasis"><em>sequence</em></span>) function takes two arguments, similar to
-the <span style="color: red"><strong>map()</strong></span> function. The <span style="color: red"><strong>filter</strong></span> function calls <span class="emphasis"><em>function(item)</em></span>, for each
-item in the sequence and returns all the elements in the sequence for which
-<span class="emphasis"><em>function(item)</em></span> returned True:</paragraph></span><span style="color: red"><literal_block>def even(x):
- if x % 2:
- return True
- else:
- return False
-
->>> filter(even, range(1, 10))
-[1, 3, 5, 7, 9]</literal_block></span><span style="color: red"><paragraph>The <span style="color: red"><strong>reduce</strong></span> (<span class="emphasis"><em>function</em></span>, <span class="emphasis"><em>sequence</em></span>) function takes two arguments, similar to
-<span style="color: red"><strong>map</strong></span> function, however multiple sequences are not allowed. The <span style="color: red"><strong>reduce</strong></span>
-function calls <span class="emphasis"><em>function</em></span> with first two consecutive elements in the sequence,
-obtains the result, calls <span class="emphasis"><em>function</em></span> with the result and the subsequent element
-in the sequence and so on until the end of the list and returns the final result:</paragraph></span><span style="color: red"><literal_block>def mul(x, y):
- return x*y
-
->>> reduce(mul, [1, 2, 3, 4])
-24</literal_block></span><div class="section" title="6.1. List Comprehensions">
-<div class="titlepage"><div><div><h3 class="title">
-<a name="id2982429"></a>6.1. List Comprehensions</h3></div></div></div>
-<span style="color: red"><paragraph>List Comprehension is a convenvience utility provided by Python. It is a
-syntatic sugar to create <span class="emphasis"><em>Lists</em></span>. Using <span class="emphasis"><em>List Comprehensions</em></span> one can create
-<span class="emphasis"><em>Lists</em></span> from other type of sequential data structures or other <span class="emphasis"><em>Lists</em></span> itself.
-The syntax of <span class="emphasis"><em>List Comprehensions</em></span> consists of a square brackets to indicate
-the result is a <span class="emphasis"><em>List</em></span> within which we include at least one <span style="color: red"><strong>for</strong></span> clause and
-multiple <span style="color: red"><strong>if</strong></span> clauses. It will be more clear with an example:</paragraph></span><span style="color: red"><literal_block>>>> num = [1, 2, 3]
->>> sq = [x*x for x in num]
->>> sq
-[1, 4, 9]
->>> all_num = [1, 2, 3, 4, 5, 6, 7, 8, 9]
->>> even = [x for x in all_num if x%2 == 0]</literal_block></span><span style="color: red"><paragraph>The syntax used here is very clear from the way it is written. It can be
-translated into english as, "for each element x in the list all_num,
-if remainder of x divided by 2 is 0, add x to the list."</paragraph></span>
-</div>
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