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Python - Tutorial

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. It was created by Guido van Rossum during 1985- 1990. Like Perl, Python source code is also available under the GNU General Public License (GPL). This tutorial gives enough understanding on Python programming language.

Audience

This tutorial is designed for software programmers who need to learn Python programming language from scratch.

Prerequisites

You should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages is a plus.

Python - Overview


Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.
  • Python is Interpreted − Python is processed at runtime by the interpreter. You do not need to compile your program before executing it. This is similar to PERL and PHP.
  • Python is Interactive − You can actually sit at a Python prompt and interact with the interpreter directly to write your programs.
  • Python is Object-Oriented − Python supports Object-Oriented style or technique of programming that encapsulates code within objects.
  • Python is a Beginner's Language − Python is a great language for the beginner-level programmers and supports the development of a wide range of applications from simple text processing to WWW browsers to games.

History of Python

Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands.
Python is derived from many other languages, including ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell and other scripting languages.
Python is copyrighted. Like Perl, Python source code is now available under the GNU General Public License (GPL).
Python is now maintained by a core development team at the institute, although Guido van Rossum still holds a vital role in directing its progress.

Python Features

Python's features include −
  • Easy-to-learn − Python has few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language quickly.
  • Easy-to-read − Python code is more clearly defined and visible to the eyes.
  • Easy-to-maintain − Python's source code is fairly easy-to-maintain.
  • A broad standard library − Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.
  • Interactive Mode − Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.
  • Portable − Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
  • Extendable − You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.
  • Databases − Python provides interfaces to all major commercial databases.
  • GUI Programming − Python supports GUI applications that can be created and ported to many system calls, libraries and windows systems, such as Windows MFC, Macintosh, and the X Window system of Unix.
  • Scalable − Python provides a better structure and support for large programs than shell scripting.
Apart from the above-mentioned features, Python has a big list of good features, few are listed below −
  • It supports functional and structured programming methods as well as OOP.
  • It can be used as a scripting language or can be compiled to byte-code for building large applications.
  • It provides very high-level dynamic data types and supports dynamic type checking.
  • It supports automatic garbage collection.
  • It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.

  • Python - Basic Syntax

    The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages.

    First Python Program

    Let us execute programs in different modes of programming.

    Interactive Mode Programming

    Invoking the interpreter without passing a script file as a parameter brings up the following prompt −
    $ python
Python 2.4.3 (#1, Nov 11 2010, 13:34:43)
[GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>>
    Type the following text at the Python prompt and press the Enter −
    >>> print "Hello, Python!"
    If you are running new version of Python, then you would need to use print statement with parenthesis as in print ("Hello, Python!");. However in Python version 2.4.3, this produces the following result −
    Hello, Python!

    Script Mode Programming

    Invoking the interpreter with a script parameter begins execution of the script and continues until the script is finished. When the script is finished, the interpreter is no longer active.
    Let us write a simple Python program in a script. Python files have extension .py. Type the following source code in a test.py file −
    print "Hello, Python!"
    We assume that you have Python interpreter set in PATH variable. Now, try to run this program as follows −
    $ python test.py
    This produces the following result −
    Hello, Python!
    Let us try another way to execute a Python script. Here is the modified test.py file −
    #!/usr/bin/python

print "Hello, Python!"
    We assume that you have Python interpreter available in /usr/bin directory. Now, try to run this program as follows −
    $ chmod +x test.py     # This is to make file executable
$./test.py
    This produces the following result −
    Hello, Python!

    Python Identifiers

    A Python identifier is a name used to identify a variable, function, class, module or other object. An identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters, underscores and digits (0 to 9).
    Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case sensitive programming language. Thus, Manpower and manpower are two different identifiers in Python.
    Here are naming conventions for Python identifiers −
    • Class names start with an uppercase letter. All other identifiers start with a lowercase letter.
    • Starting an identifier with a single leading underscore indicates that the identifier is private.
    • Starting an identifier with two leading underscores indicates a strongly private identifier.
    • If the identifier also ends with two trailing underscores, the identifier is a language-defined special name.

    Reserved Words

    The following list shows the Python keywords. These are reserved words and you cannot use them as constant or variable or any other identifier names. All the Python keywords contain lowercase letters only.
    andexecnot
    assertfinallyor
    breakforpass
    classfromprint
    continueglobalraise
    defifreturn
    delimporttry
    elifinwhile
    elseiswith
    exceptlambdayield

    Lines and Indentation

    Python provides no braces to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by line indentation, which is rigidly enforced.
    The number of spaces in the indentation is variable, but all statements within the block must be indented the same amount. For example −
    if True:
   print "True"
else:
   print "False"
    However, the following block generates an error −
    if True:
print "Answer"
print "True"
else:
print "Answer"
print "False"
    Thus, in Python all the continuous lines indented with same number of spaces would form a block. The following example has various statement blocks −
    Note − Do not try to understand the logic at this point of time. Just make sure you understood various blocks even if they are without braces.
    #!/usr/bin/python

import sys

try:
   # open file stream
   file = open(file_name, "w")
except IOError:
   print "There was an error writing to", file_name
   sys.exit()
print "Enter '", file_finish,
print "' When finished"
while file_text != file_finish:
   file_text = raw_input("Enter text: ")
   if file_text == file_finish:
      # close the file
      file.close
      break
   file.write(file_text)
   file.write("\n")
file.close()
file_name = raw_input("Enter filename: ")
if len(file_name) == 0:
   print "Next time please enter something"
   sys.exit()
try:
   file = open(file_name, "r")
except IOError:
   print "There was an error reading file"
   sys.exit()
file_text = file.read()
file.close()
print file_text

    Multi-Line Statements

    Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character (\) to denote that the line should continue. For example −
    total = item_one + \
        item_two + \
        item_three
    Statements contained within the [], {}, or () brackets do not need to use the line continuation character. For example −
    days = ['Monday', 'Tuesday', 'Wednesday',
        'Thursday', 'Friday']

    Quotation in Python

    Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the same type of quote starts and ends the string.
    The triple quotes are used to span the string across multiple lines. For example, all the following are legal −
    word = 'word'
sentence = "This is a sentence."
paragraph = """This is a paragraph. It is
made up of multiple lines and sentences."""

    Comments in Python

    A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to the end of the physical line are part of the comment and the Python interpreter ignores them.
    #!/usr/bin/python

# First comment
print "Hello, Python!" # second comment
    This produces the following result −
    Hello, Python!
    You can type a comment on the same line after a statement or expression −
    name = "Madisetti" # This is again comment
    You can comment multiple lines as follows −
    # This is a comment.
# This is a comment, too.
# This is a comment, too.
# I said that already.

    Using Blank Lines

    A line containing only whitespace, possibly with a comment, is known as a blank line and Python totally ignores it.
    In an interactive interpreter session, you must enter an empty physical line to terminate a multiline statement.

    Waiting for the User

    The following line of the program displays the prompt, the statement saying “Press the enter key to exit”, and waits for the user to take action −
    #!/usr/bin/python

raw_input("\n\nPress the enter key to exit.")
    Here, "\n\n" is used to create two new lines before displaying the actual line. Once the user presses the key, the program ends. This is a nice trick to keep a console window open until the user is done with an application.

    Multiple Statements on a Single Line

    The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a new code block. Here is a sample snip using the semicolon −
    import sys; x = 'foo'; sys.stdout.write(x + '\n')

    Multiple Statement Groups as Suites

    A group of individual statements, which make a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class require a header line and a suite.
    Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by one or more lines which make up the suite. For example −
    if expression : 
   suite
elif expression : 
   suite 
else : 
   suite

    Command Line Arguments

    Many programs can be run to provide you with some basic information about how they should be run. Python enables you to do this with -h −
    $ python -h
usage: python [option] ... [-c cmd | -m mod | file | -] [arg] ...
Options and arguments (and corresponding environment variables):
-c cmd : program passed in as string (terminates option list)
-d     : debug output from parser (also PYTHONDEBUG=x)
-E     : ignore environment variables (such as PYTHONPATH)
-h     : print this help message and exit

[ etc. ]
    You can also program your script in such a way that it should accept various options. Command Line Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the Python concepts.

  • Python - Variable Types

    Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory.
    Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you can store integers, decimals or characters in these variables.

    Assigning Values to Variables

    Python variables do not need explicit declaration to reserve memory space. The declaration happens automatically when you assign a value to a variable. The equal sign (=) is used to assign values to variables.
    The operand to the left of the = operator is the name of the variable and the operand to the right of the = operator is the value stored in the variable. For example −
    #!/usr/bin/python

counter = 100          # An integer assignment
miles   = 1000.0       # A floating point
name    = "John"       # A string

print counter
print miles
print name
    Here, 100, 1000.0 and "John" are the values assigned to counter, miles, and name variables, respectively. This produces the following result −
    100
1000.0
John

    Multiple Assignment

    Python allows you to assign a single value to several variables simultaneously. For example −
    a = b = c = 1
    Here, an integer object is created with the value 1, and all three variables are assigned to the same memory location. You can also assign multiple objects to multiple variables. For example −
    a,b,c = 1,2,"john"
    Here, two integer objects with values 1 and 2 are assigned to variables a and b respectively, and one string object with the value "john" is assigned to the variable c.

    Standard Data Types

    The data stored in memory can be of many types. For example, a person's age is stored as a numeric value and his or her address is stored as alphanumeric characters. Python has various standard data types that are used to define the operations possible on them and the storage method for each of them.
    Python has five standard data types −
    • Numbers
    • String
    • List
    • Tuple
    • Dictionary

    Python Numbers

    Number data types store numeric values. Number objects are created when you assign a value to them. For example −
    var1 = 1
var2 = 10
    You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −
    del var1[,var2[,var3[....,varN]]]]
    You can delete a single object or multiple objects by using the del statement. For example −
    del var
del var_a, var_b
    Python supports four different numerical types −
    • int (signed integers)
    • long (long integers, they can also be represented in octal and hexadecimal)
    • float (floating point real values)
    • complex (complex numbers)

    Examples

    Here are some examples of numbers −
    intlongfloatcomplex
    1051924361L0.03.14j
    100-0x19323L15.2045.j
    -7860122L-21.99.322e-36j
    0800xDEFABCECBDAECBFBAEl32.3+e18.876j
    -0490535633629843L-90.-.6545+0J
    -0x260-052318172735L-32.54e1003e+26J
    0x69-4721885298529L70.2-E124.53e-7j
    • Python allows you to use a lowercase l with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L.
    • A complex number consists of an ordered pair of real floating-point numbers denoted by x + yj, where x and y are the real numbers and j is the imaginary unit.

    Python Strings

    Strings in Python are identified as a contiguous set of characters represented in the quotation marks. Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -1 at the end.
    The plus (+) sign is the string concatenation operator and the asterisk (*) is the repetition operator. For example −
    #!/usr/bin/python

str = 'Hello World!'

print str          # Prints complete string
print str[0]       # Prints first character of the string
print str[2:5]     # Prints characters starting from 3rd to 5th
print str[2:]      # Prints string starting from 3rd character
print str * 2      # Prints string two times
print str + "TEST" # Prints concatenated string
    This will produce the following result −
    Hello World!
H
llo
llo World!
Hello World!Hello World!
Hello World!TEST

    Python Lists

    Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One difference between them is that all the items belonging to a list can be of different data type.
    The values stored in a list can be accessed using the slice operator ([ ] and [:]) with indexes starting at 0 in the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator, and the asterisk (*) is the repetition operator. For example −
    #!/usr/bin/python

list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']

print list          # Prints complete list
print list[0]       # Prints first element of the list
print list[1:3]     # Prints elements starting from 2nd till 3rd 
print list[2:]      # Prints elements starting from 3rd element
print tinylist * 2  # Prints list two times
print list + tinylist # Prints concatenated lists
    This produce the following result −
    ['abcd', 786, 2.23, 'john', 70.2]
abcd
[786, 2.23]
[2.23, 'john', 70.2]
[123, 'john', 123, 'john']
['abcd', 786, 2.23, 'john', 70.2, 123, 'john']

    Python Tuples

    A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parentheses.
    The main differences between lists and tuples are: Lists are enclosed in brackets ( [ ] ) and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only lists. For example −
    #!/usr/bin/python

tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
tinytuple = (123, 'john')

print tuple           # Prints complete list
print tuple[0]        # Prints first element of the list
print tuple[1:3]      # Prints elements starting from 2nd till 3rd 
print tuple[2:]       # Prints elements starting from 3rd element
print tinytuple * 2   # Prints list two times
print tuple + tinytuple # Prints concatenated lists
    This produce the following result −
    ('abcd', 786, 2.23, 'john', 70.2)
abcd
(786, 2.23)
(2.23, 'john', 70.2)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.2, 123, 'john')
    The following code is invalid with tuple, because we attempted to update a tuple, which is not allowed. Similar case is possible with lists −
    #!/usr/bin/python

tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
list = [ 'abcd', 786 , 2.23, 'john', 70.2  ]
tuple[2] = 1000    # Invalid syntax with tuple
list[2] = 1000     # Valid syntax with list

    Python Dictionary

    Python's dictionaries are kind of hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.
    Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For example −
    #!/usr/bin/python

dict = {}
dict['one'] = "This is one"
dict[2]     = "This is two"

tinydict = {'name': 'john','code':6734, 'dept': 'sales'}


print dict['one']       # Prints value for 'one' key
print dict[2]           # Prints value for 2 key
print tinydict          # Prints complete dictionary
print tinydict.keys()   # Prints all the keys
print tinydict.values() # Prints all the values
    This produce the following result −
    This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']
    Dictionaries have no concept of order among elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.

    Data Type Conversion

    Sometimes, you may need to perform conversions between the built-in types. To convert between types, you simply use the type name as a function.
    There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value.
    Sr.No.Function & Description
    1
    int(x [,base])
    Converts x to an integer. base specifies the base if x is a string.
    2
    long(x [,base] )
    Converts x to a long integer. base specifies the base if x is a string.
    3
    float(x)
    Converts x to a floating-point number.
    4
    complex(real [,imag])
    Creates a complex number.
    5
    str(x)
    Converts object x to a string representation.
    6
    repr(x)
    Converts object x to an expression string.
    7
    eval(str)
    Evaluates a string and returns an object.
    8
    tuple(s)
    Converts s to a tuple.
    9
    list(s)
    Converts s to a list.
    10
    set(s)
    Converts s to a set.
    11
    dict(d)
    Creates a dictionary. d must be a sequence of (key,value) tuples.
    12
    frozenset(s)
    Converts s to a frozen set.
    13
    chr(x)
    Converts an integer to a character.
    14
    unichr(x)
    Converts an integer to a Unicode character.
    15
    ord(x)
    Converts a single character to its integer value.
    16
    hex(x)
    Converts an integer to a hexadecimal string.
    17
    oct(x)
    Converts an integer to an octal string.

  • Python - Loops

    In general, statements are executed sequentially: The first statement in a function is executed first, followed by the second, and so on. There may be a situation when you need to execute a block of code several number of times.
    Programming languages provide various control structures that allow for more complicated execution paths.
    A loop statement allows us to execute a statement or group of statements multiple times. The following diagram illustrates a loop statement −
    Loop Architecture
    Python programming language provides following types of loops to handle looping requirements.
    Sr.No.Loop Type & Description
    1while loop
    Repeats a statement or group of statements while a given condition is TRUE. It tests the condition before executing the loop body.
    2for loop
    Executes a sequence of statements multiple times and abbreviates the code that manages the loop variable.
    3nested loops
    You can use one or more loop inside any another while, for or do..while loop.

    Loop Control Statements

    Loop control statements change execution from its normal sequence. When execution leaves a scope, all automatic objects that were created in that scope are destroyed.
    Python supports the following control statements. Click the following links to check their detail.
    Let us go through the loop control statements briefly
    Sr.No.Control Statement & Description
    1break statement
    Terminates the loop statement and transfers execution to the statement immediately following the loop.
    2continue statement
    Causes the loop to skip the remainder of its body and immediately retest its condition prior to reiterating.
    3pass statement
    The pass statement in Python is used when a statement is required syntactically but you do not want any command or code to execute.

    Python - Numbers

    Number data types store numeric values. They are immutable data types, means that changing the value of a number data type results in a newly allocated object.
    Number objects are created when you assign a value to them. For example −
    var1 = 1
var2 = 10
    You can also delete the reference to a number object by using the delstatement. The syntax of the del statement is −
    del var1[,var2[,var3[....,varN]]]]
    You can delete a single object or multiple objects by using the del statement. For example −
    del var
del var_a, var_b
    Python supports four different numerical types −
    • int (signed integers) − They are often called just integers or ints, are positive or negative whole numbers with no decimal point.
    • long (long integers ) − Also called longs, they are integers of unlimited size, written like integers and followed by an uppercase or lowercase L.
    • float (floating point real values) − Also called floats, they represent real numbers and are written with a decimal point dividing the integer and fractional parts. Floats may also be in scientific notation, with E or e indicating the power of 10 (2.5e2 = 2.5 x 102 = 250).
    • complex (complex numbers) − are of the form a + bJ, where a and b are floats and J (or j) represents the square root of -1 (which is an imaginary number). The real part of the number is a, and the imaginary part is b. Complex numbers are not used much in Python programming.

    Examples

    Here are some examples of numbers
    intlongfloatcomplex
    1051924361L0.03.14j
    100-0x19323L15.2045.j
    -7860122L-21.99.322e-36j
    0800xDEFABCECBDAECBFBAEL32.3+e18.876j
    -0490535633629843L-90.-.6545+0J
    -0x260-052318172735L-32.54e1003e+26J
    0x69-4721885298529L70.2-E124.53e-7j
    • Python allows you to use a lowercase L with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L.
    • A complex number consists of an ordered pair of real floating point numbers denoted by a + bj, where a is the real part and b is the imaginary part of the complex number.

    Number Type Conversion

    Python converts numbers internally in an expression containing mixed types to a common type for evaluation. But sometimes, you need to coerce a number explicitly from one type to another to satisfy the requirements of an operator or function parameter.
    • Type int(x) to convert x to a plain integer.
    • Type long(x) to convert x to a long integer.
    • Type float(x) to convert x to a floating-point number.
    • Type complex(x) to convert x to a complex number with real part x and imaginary part zero.
    • Type complex(x, y) to convert x and y to a complex number with real part x and imaginary part y. x and y are numeric expressions

    Mathematical Functions

    Python includes following functions that perform mathematical calculations.
    Sr.No.Function & Returns ( description )
    1abs(x)
    The absolute value of x: the (positive) distance between x and zero.
    2ceil(x)
    The ceiling of x: the smallest integer not less than x
    3cmp(x, y)
    -1 if x < y, 0 if x == y, or 1 if x > y
    4exp(x)
    The exponential of x: ex
    5fabs(x)
    The absolute value of x.
    6floor(x)
    The floor of x: the largest integer not greater than x
    7log(x)
    The natural logarithm of x, for x> 0
    8log10(x)
    The base-10 logarithm of x for x> 0.
    9max(x1, x2,...)
    The largest of its arguments: the value closest to positive infinity
    10min(x1, x2,...)
    The smallest of its arguments: the value closest to negative infinity
    11modf(x)
    The fractional and integer parts of x in a two-item tuple. Both parts have the same sign as x. The integer part is returned as a float.
    12pow(x, y)
    The value of x**y.
    13round(x [,n])
    x rounded to n digits from the decimal point. Python rounds away from zero as a tie-breaker: round(0.5) is 1.0 and round(-0.5) is -1.0.
    14sqrt(x)
    The square root of x for x > 0

    Random Number Functions

    Random numbers are used for games, simulations, testing, security, and privacy applications. Python includes following functions that are commonly used.
    Sr.No.Function & Description
    1choice(seq)
    A random item from a list, tuple, or string.
    2randrange ([start,] stop [,step])
    A randomly selected element from range(start, stop, step)
    3random()
    A random float r, such that 0 is less than or equal to r and r is less than 1
    4seed([x])
    Sets the integer starting value used in generating random numbers. Call this function before calling any other random module function. Returns None.
    5shuffle(lst)
    Randomizes the items of a list in place. Returns None.
    6uniform(x, y)
    A random float r, such that x is less than or equal to r and r is less than y

    Trigonometric Functions

    Python includes following functions that perform trigonometric calculations.
    Sr.No.Function & Description
    1acos(x)
    Return the arc cosine of x, in radians.
    2asin(x)
    Return the arc sine of x, in radians.
    3atan(x)
    Return the arc tangent of x, in radians.
    4atan2(y, x)
    Return atan(y / x), in radians.
    5cos(x)
    Return the cosine of x radians.
    6hypot(x, y)
    Return the Euclidean norm, sqrt(x*x + y*y).
    7sin(x)
    Return the sine of x radians.
    8tan(x)
    Return the tangent of x radians.
    9degrees(x)
    Converts angle x from radians to degrees.
    10radians(x)
    Converts angle x from degrees to radians.

    Mathematical Constants

    The module also defines two mathematical constants −
    Sr.No.Constants & Description
    1
    pi
    The mathematical constant pi.
    2
    e
    The mathematical constant e.
    NEXT TOPIC -STRINGS IN ANOTHER POST.


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