Python Programming


Python is a high-level, interpreted, interactive and object-oriented scripting language. Python was designed to be highly readable which uses English keywords frequently where as other languages use punctuation and it has fewer syntactical constructions than other languages.

  • Python is Interpreted:This means that it is processed at runtime by the interpreter and you do not need to compile your program before executing it. This is similar to PERL and PHP.
  • Python is Interactive:This means that you can actually sit at a Python prompt and interact with the interpreter directly to write your programs.
  • Python is Object-Oriented:This means that Python supports Object-Oriented style or technique of programming that encapsulates code within objects.
  • Python is Beginner’s Language:Python is a great language for the beginner 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 feature highlights include:

  • Easy-to-learn:Python has relatively few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language in a relatively short period of time.
  • Easy-to-read:Python code is much more clearly defined and visible to the eyes.
  • Easy-to-maintain:Python’s success is that its source code is fairly easy-to-maintain.
  • A broad standard library:One of Python’s greatest strengths is the bulk of the library is very portable and cross-platform compatible on UNIX, Windows and Macintosh.
  • Interactive Mode:Support for an interactive mode in which you can enter results from a terminal right to the language, allowing 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:

  • Support for 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.
  • Very high-level dynamic data types and supports dynamic type checking.
  • Supports automatic garbage collection.
  • It can be easily integrated with C, C++, COM, ActiveX, CORBA and Java.

Python Environment Variables:

Here are important environment variables, which can be recognized by Python:

Variable Description
PYTHONPATH Has a role similar to PATH. This variable tells the Python interpreter where to locate the module files you import into a program. PYTHONPATH should include the Python source library directory and the directories containing your Python source code. PYTHONPATH is sometimes preset by the Python installer.
PYTHONSTARTUP Contains the path of an initialization file containing Python source code that is executed every time you start the interpreter (similar to the Unix .profile or .login file). This file, often named .pythonrc.py in Unix, usually contains commands that load utilities or modify PYTHONPATH.
PYTHONCASEOK Used in Windows to instruct Python to find the first case-insensitive match in an import statement. Set this variable to any value to activate it.
PYTHONHOME An alternative module search path. It’s usually embedded in the PYTHONSTARTUP or PYTHONPATH directories to make switching module libraries easy.

Running Python:

There are three different ways to start Python:

(1) Interactive Interpreter:

You can enter python and start coding right away in the interactive interpreter by starting it from the command line. You can do this from Unix, DOS or any other system, which provides you a command-line interpreter or shell window.

$python # Unix/Linux or python% # Unix/Linux or C:>python # Windows/DOS

Here is the list of all the available command line options:

Option Description
-d provide debug output
-O generate optimized bytecode (resulting in .pyo files)
-S do not run import site to look for Python paths on startup
-v verbose output (detailed trace on import statements)
-X disable class-based built-in exceptions (just use strings); obsolete starting with version 1.6
-c cmd run Python script sent in as cmd string
file run Python script from given file

(2) Script from the Command-line:

A Python script can be executed at command line by invoking the interpreter on your application, as in the following:

$python script.py # Unix/Linux or python% script.py # Unix/Linux or C:>python script.py # Windows/DOS

Note: Be sure the file permission mode allows execution.

(3) Integrated Development Environment

You can run Python from a graphical user interface (GUI) environment as well. All you need is a GUI application on your system that supports Python.

  • Unix:IDLE is the very first Unix IDE for Python.
  • Windows:PythonWin is the first Windows interface for Python and is an IDE with a GUI.
  • Macintosh:The Macintosh version of Python along with the IDLE IDE is available from the main website, downloadable as either MacBinary or BinHex’d files.

Before proceeding to next chapter, make sure your environment is properly set up and working perfectly fine. If you are not able to set up the environment properly, then you can take help from your system admin.

All the examples given in subsequent chapters have been executed with Python 2.4.3 version available on CentOS flavor of Linux.

The Python language has many similarities to Perl, C and Java. However, there are some definite differences between the languages. This chapter is designed to quickly get you up to speed on the syntax that is expected in Python.

Programming In Python

 

First Python Program:

 

–INTERACTIVE MODE PROGRAMMING:

Invoking the interpreter without passing a script file as a parameter brings up the following prompt:

$ pythonPython 2.4.3 (#1, Nov 11 2010, 13:34:43)[GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2Type “help”, “copyright”, “credits” or “license” for more information.>>>

Type the following text to the right of the Python prompt and press the Enter key:

>> print “Hello, Python!”;

If you are running new version of Python, then you would need to use print statement with parenthesis like print (“Hello, Python!”);. However at Python version 2.4.3, this will produce 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. All python files will have extension .py. So put the following source code in a test.py file.

print “Hello, Python!”;

Here, I assumed that you have Python interpreter set in PATH variable. Now, try to run this program as follows:

$ python test.py

This will produce the following result:

Hello, Python!

Let’s try another way to execute a Python script. Below is the modified test.py file:

#!/usr/bin/python print “Hello, Python!”;

Here, I assumed 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 will produce 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 following identifier naming convention for Python:

  • Class names start with an uppercase letter and all other identifiers with a lowercase letter.
  • Starting an identifier with a single leading underscore indicates by convention that the identifier is meant to be 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 reserved words in Python. These reserved words may not be used as constant or variable or any other identifier names. All the Python keywords contain lowercase letters only.

and exec not
assert finally or
break for pass
class from print
continue global raise
def if return
del import try
elif in while
else is with
except lambda yield

Lines and Indentation:

One of the first caveats programmers encounter when learning Python is the fact that there are 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. Both blocks in this example are fine:

if True: print “True”else: print “False”

However, the second block in this example will generate an error:

if True: print “Answer” print “True”else: print “Answer” print “False”

Thus, in Python all the continous lines indented with similar number of spaces would form a block. Following is the example having various statement blocks:

Note: Don’t try to understand logic or different functions used. 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 can be 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 ismade 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 physical line end are part of the comment and the Python interpreter ignores them.

#!/usr/bin/python # First commentprint “Hello, Python!”; # second comment

This will produce the following result:

Hello, Python!

A comment may be 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, Press the enter key to exit and waits for the user to press the Enter key:

#!/usr/bin/python raw_input(“nnPress the enter key to exit.”)

Here, “nn” are being 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, are those which 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 : suiteelif expression : suite else : suite

Command Line Arguments:

You may have seen, for instance, that many programs can be run so that they provide you with some basic information about how they should be run. Python enables you to do this with -h:

$ python -husage: 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.

 

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 have to be explicitly declared 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 assignmentmiles = 1000.0 # A floating pointname = “John” # A string print counterprint milesprint name

Here, 100, 1000.0 and “John” are the values assigned to counter, miles and name variables, respectively. While running this program, this will produce the following result:

1001000.0John

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, 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 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. They are immutable data types which 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 = 1var2 = 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 vardel var_a, var_b

Python supports four different numerical types:

  • int (signed integers)
  • long (long integers [can also be represented in octal and hexadecimal])
  • float (floating point real values)
  • complex (complex numbers)

Examples:

Here are some examples of numbers:

int long float complex
10 51924361L 0.0 3.14j
100 -0x19323L 15.20 45.j
-786 0122L -21.9 9.322e-36j
080 0xDEFABCECBDAECBFBAEl 32.3+e18 .876j
-0490 535633629843L -90. -.6545+0J
-0x260 -052318172735L -32.54e100 3e+26J
0x69 -4721885298529L 70.2-E12 4.53e-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.

Python Strings:

Strings in Python are identified as a contiguous set of characters in between 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 stringprint str[0] # Prints first character of the stringprint str[2:5] # Prints characters starting from 3rd to 5thprint str[2:] # Prints string starting from 3rd characterprint str * 2 # Prints string two timesprint str + “TEST” # Prints concatenated string

This will produce the following result:

Hello World!Hllollo 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 listprint list[0] # Prints first element of the listprint list[1:3] # Prints elements starting from 2nd till 3rd print list[2:] # Prints elements starting from 3rd elementprint tinylist * 2 # Prints list two timesprint list + tinylist # Prints concatenated lists

This will produce the following result:

[‘abcd’, 786, 2.23, ‘john’, 70.200000000000003]abcd[786, 2.23][2.23, ‘john’, 70.200000000000003][123, ‘john’, 123, ‘john’][‘abcd’, 786, 2.23, ‘john’, 70.200000000000003, 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 listprint tuple[0] # Prints first element of the listprint tuple[1:3] # Prints elements starting from 2nd till 3rd print tuple[2:] # Prints elements starting from 3rd elementprint tinytuple * 2 # Prints list two timesprint tuple + tinytuple # Prints concatenated lists

This will produce the following result:

(‘abcd’, 786, 2.23, ‘john’, 70.200000000000003)abcd(786, 2.23)(2.23, ‘john’, 70.200000000000003)(123, ‘john’, 123, ‘john’)(‘abcd’, 786, 2.23, ‘john’, 70.200000000000003, 123, ‘john’)

Following 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 tuplelist[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’ keyprint dict[2] # Prints value for 2 keyprint tinydict # Prints complete dictionaryprint tinydict.keys() # Prints all the keysprint tinydict.values() # Prints all the values

This will produce the following result:

This is oneThis 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.

Function Description
int(x [,base]) Converts x to an integer. base specifies the base if x is a string.
long(x [,base] ) Converts x to a long integer. base specifies the base if x is a string.
float(x) Converts x to a floating-point number.
complex(real [,imag]) Creates a complex number.
str(x) Converts object x to a string representation.
repr(x) Converts object x to an expression string.
eval(str) Evaluates a string and returns an object.
tuple(s) Converts s to a tuple.
list(s) Converts s to a list.
set(s) Converts s to a set.
dict(d) Creates a dictionary. d must be a sequence of (key,value) tuples.
frozenset(s) Converts s to a frozen set.
chr(x) Converts an integer to a character.
unichr(x) Converts an integer to a Unicode character.
ord(x) Converts a single character to its integer value.
hex(x) Converts an integer to a hexadecimal string.
oct(x) Converts an integer to an octal string.

 

~Taken from anonymous site

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Python Programming

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