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diff --git a/basic_python/intro.rst b/basic_python/intro.rst index 1bfc2a9..7ae98d8 100644 --- a/basic_python/intro.rst +++ b/basic_python/intro.rst @@ -687,6 +687,294 @@ cannot be performed on it. Hence the exception is raised. **int()** method ~~~~~~~~~~~~~~~~ -Generally for computing purposes +Generally for computing purposes, the data used is not strings or raw data but +on integers, floats and similar mathematical data structures. The data obtained +from **raw_input()** is raw data in the form of strings. In order to obtain integers +from strings we use the method **int()**. Let us look at an example. + +:: + + >>> intpal = int(pal) + >>> intpal + 121 + +In the previous example it was observed that *pal* was a string variable. Here +using the **int()** method the string *pal* was converted to an integer variable. + +*Try This Yourself:* + +:: + + >>> stringvar = raw_input("Enter a name:") + Enter a name:Guido Van Rossum + >>> stringvar + 'Guido Van Rossum' + >>> numvar = int(stringvar) + + +Functions in Python: **def** +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +*Functions* 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. + +*Function* in python is defined with the keyword **def** 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 *Function* must return a value:: + + def factorial(n): + fact = 1 + for i in range(2, n): + fact *= i + + return fact + +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. + +A *Function* 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. + +The value that function returns can be assigned to a variable. Let's call the +above function and store the factorial in a variable:: + + fact5 = factorial(5) + +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. + +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 *Documentation String* or *docstring*. *docstrings* 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. *docstrings* for functions can be written as follows:: + + def factorial(n): + 'Returns the factorial for the number n.' + fact = 1 + for i in range(2, n): + fact *= i + + return fact + +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 *Tuple*. A *Tuple* is +just a collection of values and those values themselves can be of any other +valid Python datatypes, including *Lists*, *Tuples*, *Dictionaries* among other +things. So effectively, if a function can return a tuple, it can return any +number of values through a tuple + +Let us write a small function to swap two values:: + + def swap(a, b): + return b, a + + c, d = swap(a, b) + +Function scope +--------------- +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:: + + def cant_change(n): + n = 10 + + n = 5 + cant_change(n) + +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 *Numbers*, *Strings* +and *Tuples*. But when you pass mutable objects like *Lists* and *Dictionaries* +the values are manipulated even outside the function:: + + >>> def can_change(n): + ... n[1] = James + ... + + >>> name = ['Mr.', 'Steve', 'Gosling'] + >>> can_change(name) + >>> name + ['Mr.', 'James', 'Gosling'] + +If nothing is returned by the function explicitly, Python takes care to return +None when the funnction is called. + +Default Arguments +----------------- + +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 *Default Arguments*. 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:: + + 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 + +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:: + + fib() + [0, 1, 1, 2, 3, 5, 8, 13, 21, 34] + fib(5) + [0, 1, 1, 2, 3] + +Keyword Arguments +----------------- + +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 *Keyword Arguments*. + +In a function call, *Keyword arguments* can be used for each argument, in the +following fashion:: + + argument_name=argument_value + Also denoted as: keyword=argument + + def wish(name='World', greetings='Hello'): + print "%s, %s!" % (greetings, name) + +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 *Keyword arguments* +can be specified. Also note, that we have combined *Keyword arguments* with +*Default arguments* in this example, however it is not necessary:: + + wish(name='Guido', greetings='Hey') + wish(greetings='Hey', name='Guido') + +Calling functions by specifying arguments in the order of parameters specified +in the function definition is called as *Positional arguments*, as opposed to +*Keyword arguments*. It is possible to use both *Positional arguments* and +*Keyword arguments* 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 *Positional arguments* which is in turn followed by *Keyword +arguments*:: + + def my_func(x, y, z, u, v, w): + # initialize variables. + ... + # do some stuff + ... + # return the value + +It is valid to call the above functions in the following ways:: + + 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) + +Following lists some of the invalid calls:: + + 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) + +Parameter Packing and Unpacking +------------------------------- + +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 *****, for collecting positional +parameters, in turn followed by the dictionary collecting parameter, whose name +is preceded by a ****** :: + + 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 + +The above function can be called as. Note, the order of keyword parameters can +be interchanged:: + + >>> 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 + +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 *Positional arguments* or *Keyword arguments* respectively +using ***** or ****** :: + + 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 + +Nested Functions and Scopes +--------------------------- + +Python allows nesting one function inside another. This style of programming +turns out to be extremely flexible and powerful features when we use *Python +decorators*. We will not talk about decorators is beyond the scope of this +course. If you are interested in knowing more about *decorator programming* in +Python you are suggested to read: + +| http://avinashv.net/2008/04/python-decorators-syntactic-sugar/ +| http://personalpages.tds.net/~kent37/kk/00001.html + +However, the following is an example for nested functions in Python:: + + def outer(): + print "Outer..." + def inner(): + print "Inner..." + print "Outer..." + inner() + + >>> outer() + |