Swaroop c h a byte of python

A Byte of Python
Swaroop C H
Copyright © 2003-2005 Swaroop C H
Abstract
This book will help you to learn the Python programming language, whether you are new to computers
or are an experienced programmer.
This book is released under the Creative Commons Attribution-NonCommercial-ShareAlike License 2.0 .

Table of Contents
Preface ......................................................................................................................x
Who This Book Is For ..........................................................................................x
History Lesson ...................................................................................................x
Status of the book ................................................................................................x
Official Website ................................................................................................. xi
License Terms ................................................................................................... xi
Feedback .......................................................................................................... xi
Something To Think About .................................................................................. xi
1. Introduction ............................................................................................................1
Introduction .......................................................................................................1
Features of Python ..............................................................................................1
Summary ...................................................................................................2
Why not Perl? ....................................................................................................3
What Programmers Say ........................................................................................3
2. Installing Python .....................................................................................................4
For Linux/BSD users ...........................................................................................4
For Windows Users .............................................................................................4
Summary ...........................................................................................................5
3. First Steps ..............................................................................................................6
Introduction .......................................................................................................6
Using the interpreter prompt ..................................................................................6
Choosing an Editor ..............................................................................................6
Using a Source File .............................................................................................7
Output ......................................................................................................7
How It Works .............................................................................................8
Executable Python programs .................................................................................8
Getting Help ......................................................................................................9
Summary ......................................................................................................... 10
4. The Basics ............................................................................................................ 11
Literal Constants ............................................................................................... 11
Numbers ......................................................................................................... 11
Strings ............................................................................................................ 11
Variables ......................................................................................................... 13
Identifier Naming .............................................................................................. 13
Data Types ...................................................................................................... 14
Objects ........................................................................................................... 14
Output .................................................................................................... 15
How It Works ........................................................................................... 15
Logical and Physical Lines ................................................................................. 15
Indentation ...................................................................................................... 17
Summary ......................................................................................................... 18
5. Operators and Expressions ....................................................................................... 19
Introduction ..................................................................................................... 19
Operators ......................................................................................................... 19
Operator Precedence .......................................................................................... 21
Order of Evaluation ................................................................................... 22
Associativity ............................................................................................ 22
Expressions ...................................................................................................... 22
Using Expressions ..................................................................................... 22
Summary ......................................................................................................... 23
6. Control Flow ........................................................................................................ 24
Introduction ..................................................................................................... 24
The if statement ................................................................................................ 24
iv

Using the if statement ................................................................................ 24
How It Works ........................................................................................... 25
The while statement ........................................................................................... 26
Using the while statement ........................................................................... 26
The for loop ..................................................................................................... 27
Using the for statement .............................................................................. 27
The break statement ........................................................................................... 28
Using the break statement ........................................................................... 28
The continue statement ....................................................................................... 30
Using the continue statement ....................................................................... 30
Summary ......................................................................................................... 30
7. Functions ............................................................................................................. 32
Introduction ..................................................................................................... 32
Defining a Function ................................................................................... 32
Function Parameters .......................................................................................... 32
Using Function Parameters ......................................................................... 33
Local Variables ................................................................................................ 33
Using Local Variables ................................................................................ 34
Using the global statement .......................................................................... 34
Default Argument Values ................................................................................... 35
Using Default Argument Values .................................................................. 35
Keyword Arguments .......................................................................................... 36
Using Keyword Arguments ......................................................................... 37
The return statement .......................................................................................... 37
Using the literal statement ........................................................................... 38
DocStrings ....................................................................................................... 38
Using DocStrings ...................................................................................... 39
Summary ......................................................................................................... 40
8. Modules ............................................................................................................... 41
Introduction ..................................................................................................... 41
Using the sys module ................................................................................. 41
Byte-compiled .pyc files ..................................................................................... 42
The from..import statement ................................................................................. 42
A module's __name__ ........................................................................................ 42
Using a module's __name__ ........................................................................ 43
Making your own Modules ................................................................................. 43
Creating your own Modules ........................................................................ 43
from..import ............................................................................................. 44
The dir() function .............................................................................................. 45
Using the dir function ................................................................................ 45
Summary ......................................................................................................... 46
9. Data Structures ...................................................................................................... 47
Introduction ..................................................................................................... 47
List ................................................................................................................ 47
Quick introduction to Objects and Classes ..................................................... 47
Using Lists .............................................................................................. 47
Tuple .............................................................................................................. 49
Using Tuples ............................................................................................ 49
Tuples and the print statement ..................................................................... 50
Dictionary ....................................................................................................... 51
Using Dictionaries ..................................................................................... 51
Sequences ........................................................................................................ 53
Using Sequences ....................................................................................... 53
References ....................................................................................................... 54
Objects and References .............................................................................. 55
More about Strings ............................................................................................ 56
String Methods ......................................................................................... 56
Summary ......................................................................................................... 57
A Byte of Python
v

10. Problem Solving - Writing a Python Script ................................................................ 58
The Problem .................................................................................................... 58
The Solution .................................................................................................... 58
First Version ............................................................................................ 58
Second Version ........................................................................................ 60
Third Version ........................................................................................... 61
Fourth Version ......................................................................................... 63
More Refinements ..................................................................................... 64
The Software Development Process ...................................................................... 65
Summary ......................................................................................................... 65
11. Object-Oriented Programming ................................................................................ 67
Introduction ..................................................................................................... 67
The self ........................................................................................................... 67
Classes ............................................................................................................ 68
Creating a Class ........................................................................................ 68
object Methods ................................................................................................. 69
Using Object Methds ................................................................................. 69
The __init__ method .......................................................................................... 69
Using the __init__ method .......................................................................... 69
Class and Object Variables ................................................................................. 70
Using Class and Object Variables ................................................................. 71
Inheritance ....................................................................................................... 73
Using Inheritance ...................................................................................... 73
Summary ......................................................................................................... 75
12. Input/Output ....................................................................................................... 76
Files ............................................................................................................... 76
Using file ................................................................................................ 76
Pickle ............................................................................................................. 77
Pickling and Unpickling ............................................................................. 77
Summary ......................................................................................................... 78
13. Exceptions .......................................................................................................... 79
Errors ............................................................................................................. 79
Try..Except ...................................................................................................... 79
Handling Exceptions .................................................................................. 79
Raising Exceptions ............................................................................................ 80
How To Raise Exceptions ........................................................................... 81
Try..Finally ...................................................................................................... 82
Using Finally ........................................................................................... 82
Summary ......................................................................................................... 83
14. The Python Standard Library .................................................................................. 84
Introduction ..................................................................................................... 84
The sys module ................................................................................................. 84
Command Line Arguments ......................................................................... 84
More sys ................................................................................................. 86
The os module .................................................................................................. 86
Summary ......................................................................................................... 87
15. More Python ....................................................................................................... 88
Special Methods ............................................................................................... 88
Single Statement Blocks ..................................................................................... 88
List Comprehension ........................................................................................... 89
Using List Comprehensions ........................................................................ 89
Receiving Tuples and Lists in Functions ................................................................ 89
Lambda Forms ................................................................................................. 90
Using Lambda Forms ................................................................................. 90
The exec and eval statements ............................................................................... 91
The assert statement .......................................................................................... 91
The repr function .............................................................................................. 91
Summary ......................................................................................................... 92
A Byte of Python
vi

16. What Next? ......................................................................................................... 93
Graphical Software ............................................................................................ 93
Summary of GUI Tools .............................................................................. 94
Explore More ................................................................................................... 94
Summary ......................................................................................................... 95
A. Free/Libré and Open Source Software (FLOSS) .......................................................... 96
B. About ................................................................................................................. 98
Colophon ......................................................................................................... 98
About the Author .............................................................................................. 98
C. Revision History ................................................................................................... 99
Timestamp ....................................................................................................... 99
A Byte of Python
vii

List of Tables
5.1. Operators and their usage ...................................................................................... 19
5.2. Operator Precedence ............................................................................................ 21
15.1. Some Special Methods ....................................................................................... 88
viii

List of Examples
3.1. Using the python interpreter prompt ..........................................................................6
3.2. Using a Source File ...............................................................................................7
4.1. Using Variables and Literal constants ...................................................................... 14
5.1. Using Expressions ............................................................................................... 22
6.1. Using the if statement .......................................................................................... 24
6.2. Using the while statement ..................................................................................... 26
6.3. Using the for statement ......................................................................................... 27
6.4. Using the break statement ..................................................................................... 29
6.5. Using the continue statement ................................................................................. 30
7.1. Defining a function .............................................................................................. 32
7.2. Using Function Parameters .................................................................................... 33
7.3. Using Local Variables .......................................................................................... 34
7.4. Using the global statement .................................................................................... 35
7.5. Using Default Argument Values ............................................................................. 36
7.6. Using Keyword Arguments ................................................................................... 37
7.7. Using the literal statement ..................................................................................... 38
7.8. Using DocStrings ................................................................................................ 39
8.1. Using the sys module ........................................................................................... 41
8.2. Using a module's __name__ .................................................................................. 43
8.3. How to create your own module ............................................................................. 43
8.4. Using the dir function .......................................................................................... 45
9.1. Using lists .......................................................................................................... 47
9.2. Using Tuples ...................................................................................................... 49
9.3. Output using tuples .............................................................................................. 50
9.4. Using dictionaries ............................................................................................... 51
9.5. Using Sequences ................................................................................................. 53
9.6. Objects and References ........................................................................................ 55
9.7. String Methods ................................................................................................... 56
10.1. Backup Script - The First Version ......................................................................... 58
10.2. Backup Script - The Second Version ..................................................................... 60
10.3. Backup Script - The Third Version (does not work!) ................................................. 62
10.4. Backup Script - The Fourth Version ...................................................................... 63
11.1. Creating a Class ................................................................................................ 68
11.2. Using Object Methods ........................................................................................ 69
11.3. Using the __init__ method ................................................................................... 69
11.4. Using Class and Object Variables ......................................................................... 71
11.5. Using Inheritance .............................................................................................. 73
12.1. Using files ........................................................................................................ 76
12.2. Pickling and Unpickling ...................................................................................... 77
13.1. Handling Exceptions .......................................................................................... 80
13.2. How to Raise Exceptions .................................................................................... 81
13.3. Using Finally .................................................................................................... 82
14.1. Using sys.argv .................................................................................................. 84
15.1. Using List Comprehensions ................................................................................. 89
15.2. Using Lambda Forms ......................................................................................... 90
ix

Preface
Python is probably one of the few programming languages which is both simple and powerful. This is
good for both and beginners as well as experts, and more importantly, is fun to program with. This book
aims to help you learn this wonderful language and show how to get things done quickly and painlessly -
in effect 'The Perfect Anti-venom to your programming problems'.
Who This Book Is For
This book serves as a guide or tutorial to the Python programming language. It is mainly targeted at
newbies. It is useful for experienced programmers as well.
The aim is that if all you know about computers is how to save text files, then you can learn Python from
this book. If you have previous programming experience, then you can also learn Python from this book.
If you do have previous programming experience, you will be interested in the differences between Py-
thon and your favorite programming language - I have highlighted many such differences. A little warn-
ing though, Python is soon going to become your favorite programming language!
History Lesson
I first started with Python when I needed to write an installer for my software Diamond
[http://www.g2swaroop.net/software/] so that I could make the installation easy. I had to choose
between Python and Perl bindings for the Qt library. I did some research on the web and I came across
an article where Eric S. Raymond, the famous and respected hacker, talked about how Python has be-
come his favorite programming language. I also found out that the PyQt bindings were very good com-
pared to Perl-Qt. So, I decided that Python was the language for me.
Then, I started searching for a good book on Python. I couldn't find any! I did find some O'Reilly books
but they were either too expensive or were more like a reference manual than a guide. So, I settled for
the documentation that came with Python. However, it was too brief and small. It did give a good idea
about Python but was not complete. I managed with it since I had previous programming experience, but
it was unsuitable for newbies.
About six months after my first brush with Python, I installed the (then) latest Red Hat 9.0 Linux and I
was playing around with KWord. I got excited about it and suddenly got the idea of writing some stuff
on Python. I started writing a few pages but it quickly became 30 pages long. Then, I became serious
about making it more useful in a book form. After a lot of rewrites, it has reached a stage where it has
become a useful guide to learning the Python language. I consider this book to be my contribution and
tribute to the open source community.
This book started out as my personal notes on Python and I still consider it in the same way, although
I've taken a lot of effort to make it more palatable to others :)
In the true spirit of open source, I have received lots of constructive suggestions, criticisms and feedback
from enthusiastic readers which has helped me improve this book a lot.
Status of the book
This book is a work-in-progress. Many chapters are constantly being changed and improved. However,
the book has matured a lot. You should be able to learn Python easily from this book. Please do tell me
if you find any part of the book to be incorrect or incomprehensible.
More chapters are planned for the future, such as on wxPython, Twisted and maybe even Boa Construct-
x

or.
Official Website
The official website of the book is www.byteofpython.info [http://www.byteofpython.info] . From the
website, you can read the whole book online or you can download the latest versions of the book, and
also send me feedback.
License Terms
This book is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike License 2.0
[http://creativecommons.org/licenses/by-nc-sa/2.0/] .
Basically, you are free to copy, distribute, and display the book, as long as you give credit to me. The re-
strictions are that you cannot use the book for commercial purposes without my permission. You are
free to modify and build upon this work, provided that you clearly mark all changes and release the
modified work under the same license as this book.
Please visit the Creative Commons website [http://creativecommons.org/licenses/by-nc-sa/2.0/] for the
full and exact text of the license, or for an easy-to-understand version. There is even a comic strip ex-
plaining the terms of the license.
Feedback
I have put in a lot of effort to make this book as interesting and as accurate as possible. However, if you
find some material to be inconsistent or incorrect, or simply needs improvement, then please do inform
me, so that I can make suitable improvements. You can reach me at
<swaroop@byteofpython.info> .
Something To Think About
There are two ways of constructing a software design: one way is to make it so simple
that there are obviously no deficiencies; the other is to make it so complicated that
there are no obvious deficiencies.
—C. A. R. Hoare
Success in life is a matter not so much of talent and opportunity as of concentration
and perseverance.
—C. W. Wendte
Preface
xi

Chapter 1. Introduction
Introduction
Python is one of those rare languages which can claim to be both simple and powerful. You will find
that you will be pleasantly surprised on how easy it is to concentrate on the solution to the problem
rather than the syntax and structure of the language you are programming in.
The official introduction to Python is
Python is an easy to learn, powerful programming language. It has efficient high-level
data structures and a simple but effective approach to object-oriented programming.
Python's elegant syntax and dynamic typing, together with its interpreted nature, make
it an ideal language for scripting and rapid application development in many areas on
most platforms.
I will discuss most of these features in more detail in the next section.
Note
Guido van Rossum, the creator of the Python language, named the language after the BBC
show "Monty Python's Flying Circus ". He doesn't particularly like snakes that kill animals for
food by winding their long bodies around them and crushing them.
Features of Python
Simple Python is a simple and minimalistic language. Reading a good Python
program feels almost like reading English, although very strict English!
This pseudo-code nature of Python is one of its greatest strengths. It al-
lows you to concentrate on the solution to the problem rather than the
language itself.
Easy to Learn As you will see, Python is extremely easy to get started with. Python
has an extraordinarily simple syntax, as already mentioned.
Free and Open Source Python is an example of a FLOSS (Free/Libré and Open Source Soft-
ware). In simple terms, you can freely distribute copies of this software,
read it's source code, make changes to it, use pieces of it in new free
programs, and that you know you can do these things. FLOSS is based
on the concept of a community which shares knowledge. This is one of
the reasons why Python is so good - it has been created and is con-
stantly improved by a community who just want to see a better Python.
High-level Language When you write programs in Python, you never need to bother about the
low-level details such as managing the memory used by your program,
etc.
Portable Due to its open-source nature, Python has been ported (i.e. changed to
make it work on) to many platforms. All your Python programs can
work on any of these platforms without requiring any changes at all if
you are careful enough to avoid any system-dependent features.
You can use Python on Linux, Windows, FreeBSD, Macintosh, Solaris,
OS/2, Amiga, AROS, AS/400, BeOS, OS/390, z/OS, Palm OS, QNX,
VMS, Psion, Acorn RISC OS, VxWorks, PlayStation, Sharp Zaurus,
1

Windows CE and even PocketPC !
Interpreted This requires a bit of explanation.
A program written in a compiled language like C or C++ is converted
from the source language i.e. C or C++ into a language that is spoken
by your computer (binary code i.e. 0s and 1s) using a compiler with
various flags and options. When you run the program, the linker/loader
software copies the program from hard disk to memory and starts run-
ning it.
Python, on the other hand, does not need compilation to binary. You
just run the program directly from the source code. Internally, Python
converts the source code into an intermediate form called bytecodes and
then translates this into the native language of your computer and then
runs it. All this, actually, makes using Python much easier since you
don't have to worry about compiling the program, making sure that the
proper libraries are linked and loaded, etc, etc. This also makes your Py-
thon programs much more portable, since you can just copy your Py-
thon program onto another computer and it just works!
Object Oriented Python supports procedure-oriented programming as well as object-
oriented programming. In procedure-oriented languages, the program is
built around procedures or functions which are nothing but reusable
pieces of programs. In object-oriented languages, the program is built
around objects which combine data and functionality. Python has a very
powerful but simplistic way of doing OOP, especially when compared
to big languages like C++ or Java.
Extensible If you need a critical piece of code to run very fast or want to have some
piece of algorithm not to be open, you can code that part of your pro-
gram in C or C++ and then use them from your Python program.
Embeddable You can embed Python within your C/C++ programs to give 'scripting'
capabilities for your program's users.
Extensive Libraries The Python Standard Library is huge indeed. It can help you do various
things involving regular expressions, documentation generation, unit
testing, threading, databases, web browsers, CGI, ftp, email, XML,
XML-RPC, HTML, WAV files, cryptography, GUI (graphical user in-
terfaces), Tk, and other system-dependent stuff. Remember, all this is
always available wherever Python is installed. This is called the 'Batter-
ies Included' philosophy of Python.
Besides, the standard library, there are various other high-quality librar-
ies such as wxPython [http://www.wxpython.org], Twisted
[http://www.twistedmatrix.com/products/twisted], Python Imaging Lib-
rary [http://www.pythonware.com/products/pil/index.htm] and many
more.
Summary
Python is indeed an exciting and powerful language. It has the right combination of performance and
features that make writing programs in Python both fun and easy.
Introduction
2

Why not Perl?
If you didn't know already, Perl is another extremely popular open source interpreted programming lan-
guage.
If you have ever tried writing a large program in Perl, you would have answered this question yourself!
In other words, Perl programs are easy when they are small and it excels at small hacks and scripts to
'get work done'. However, they quickly become unwieldy once you start writing bigger programs and I
am speaking this out of experience of writing large Perl programs at Yahoo!
When compared to Perl, Python programs are definitely simpler, clearer, easier to write and hence more
understandable and maintainable. I do admire Perl and I do use it on a daily basis for various things but
whenever I write a program, I always start thinking in terms of Python because it has become so natural
for me. Perl has undergone so many hacks and changes, that it feels like it is one big (but one hell of a)
hack. Sadly, the upcoming Perl 6 does not seem to be making any improvements regarding this.
The only and very significant advantage that I feel Perl has, is its huge CPAN [http://cpan.perl.org] lib-
rary - the Comprehensive Perl Archive Network. As the name suggests, this is a humongous collection
of Perl modules and it is simply mind-boggling because of its sheer size and depth - you can do virtually
anything you can do with a computer using these modules. One of the reasons that Perl has more librar-
ies than Python is that it has been around for a much longer time than Python. Maybe I should suggest a
port-Perl-modules-to-Python hackathon on comp.lang.python
[http://groups.google.com/groups?q=comp.lang.python] :)
Also, the new Parrot virtual machine [http://www.parrotcode.org] is designed to run both the completely
redesigned Perl 6 as well as Python and other interpreted languages like Ruby, PHP and Tcl. What this
means to you is that maybe you will be able to use all Perl modules from Python in the future, so that
will give you the best of both worlds - the powerful CPAN library combined with the powerful Python
language. However, we will have to just wait and see what happens.
What Programmers Say
You may find it interesting to read what great hackers like ESR have to say about Python:
• Eric S. Raymond is the author of 'The Cathedral and the Bazaar' and is also the person who coined
the term 'Open Source'. He says that Python has become his favorite programming language
[http://www.linuxjournal.com/article.php?sid=3882]. This article was the real inspiration for my first
brush with Python.
• Bruce Eckel is the author of the famous 'Thinking in Java' and 'Thinking in C++' books. He says
that no language has made him more productive than Python. He says that Python is perhaps the
only language that focuses on making things easier for the programmer. Read the complete interview
[http://www.artima.com/intv/aboutme.html] for more details.
• Peter Norvig is a well-known Lisp author and Director of Search Quality at Google (thanks to
Guido van Rossum for pointing that out). He says that Python has always been an integral part of
Google. You can actually verify this statement by looking at the Google Jobs
[http://www.google.com/jobs/index.html] page which lists Python knowledge as a requirement for
software engineers.
• Bruce Perens is a co-founder of OpenSource.org and the UserLinux project. UserLinux aims to cre-
ate a standardized Linux distribution supported by multiple vendors. Python has beaten contenders
like Perl and Ruby to become the main programming language that will be supported by UserLinux.
Introduction
3

Chapter 2. Installing Python
For Linux/BSD users
If you are using a Linux distribution such as Fedora or Mandrake or {put your choice here}, or a BSD
system such as FreeBSD, then you probably already have Python installed on your system.
To test if you have Python already installed on your Linux box, open a shell program (like konsole or
gnome-terminal) and enter the command python -V as shown below.
$ python -V
Python 2.3.4
Note
$ is the prompt of the shell. It will be different for you depending on the settings of your OS,
hence I will indicate the prompt by just the $ symbol.
If you see some version information like the one shown above, then you have Python installed already.
However, if you get a message like this one:
$ python -V
bash: python: command not found
then, you don't have Python installed. This is highly unlikely but possible.
In this case, you have two ways of installing Python on your system.
• Install the binary packages using the package management software that comes with your OS, such
as yum in Fedora Linux, urpmi in Mandrake Linux, apt-get in Debian Linux, pkg_add in FreeBSD,
etc. Note that you will need an internet connection to use this method.
Alternatively, you can download the binaries from somewhere else and then copy to your PC and in-
stall it.
• You can compile Python from the source code [http://www.python.org/download/] and install it. The
compilation instructions are provided at the website.
For Windows Users
Visit Python.org/download [http://www.python.org/download/] and download the latest version from
this website (which was 2.3.4 [http://www.python.org/ftp/python/2.3.4/Python-2.3.4.exe] as of this writ-
ing. This is just 9.4 MB which is very compact compared to most other languages. The installation is
just like any other Windows-based software.
4

Caution
When you are given the option of unchecking any optional components, don't uncheck any!
Some of these components can be useful for you, especially IDLE.
An interesting fact is that about 70% of Python downloads are by Windows users. Of course, this doesn't
give the complete picture since almost all Linux users will have Python installed already on their sys-
tems by default.
Using Python in the Windows command line
If you want to be able to use Python from the Windows command line, then you need to set the
PATH variable appropriately.
For Windows 2000, XP, 2003 , click on Control Panel -> System -> Advanced -> Environment
Variables. Click on the variable named PATH in the 'System Variables' section, then select
Edit and add ;C:Python23 (without the quotes) to the end of what is already there. Of course,
use the appropriate directory name.
For older versions of Windows, add the following line to the file C:AUTOEXEC.BAT :
'PATH=%PATH%;C:Python23' (without the quotes) and restart the system. For Windows
NT, use the AUTOEXEC.NT file.
Summary
For a Linux system, you most probably already have Python installed on your system. Otherwise, you
can install it using the package management software that comes with your distribution. For a Windows
system, installing Python is as easy as downloading the installer and double-clicking on it. From now
on, we will assume that you have Python installed on your system.
Next, we will write our first Python program.
Installing Python
5

Chapter 3. First Steps
Introduction
We will now see how to run a traditional 'Hello World' program in Python. This will teach you how to
write, save and run Python programs.
There are two ways of using Python to run your program - using the interactive interpreter prompt or us-
ing a source file. We will now see how to use both the methods.
Using the interpreter prompt
Start the intepreter on the command line by entering python at the shell prompt. Now enter print
'Hello World' followed by the Enter key. You should see the words Hello World as output.
For Windows users, you can run the interpreter in the command line if you have set the PATH variable
appropriately. Alternatively, you can use the IDLE program. IDLE is short for Integrated DeveLopment
Environment. Click on Start -> Programs -> Python 2.3 -> IDLE (Python GUI). Linux users can use
IDLE too.
Note that the <<< signs are the prompt for entering Python statements.
Example 3.1. Using the python interpreter prompt
$ python
Python 2.3.4 (#1, Oct 26 2004, 16:42:40)
[GCC 3.4.2 20041017 (Red Hat 3.4.2-6.fc3)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> print 'hello world'
hello world
>>>
Notice that Python gives you the output of the line immediately! What you just entered is a single Py-
thon statement. We use print to (unsurprisingly) print any value that you supply to it. Here, we are
supplying the text Hello World and this is promptly printed to the screen.
How to quit the Python prompt
To exit the prompt, press Ctrl-d if you are using IDLE or are using a Linux/BSD shell. In case
of the Windows command prompt, press Ctrl-z followed by Enter.
Choosing an Editor
Before we move on to writing Python programs in source files, we need an editor to write the source
files. The choice of an editor is crucial indeed. You have to choose an editor as you would choose a car
you would buy. A good editor will help you write Python programs easily, making your journey more
comfortable and helps you reach your destination (achieve your goal) in a much faster and safer way.
6

1 one of the leading Perl6/Parrot hackers and the author of the amazing 'Beginning Perl' book
One of the very basic requirements is syntax highlighting where all the different parts of your Python
program are colorized so that you can see your program and visualize its running.
If you are using Windows, then I suggest that you use IDLE. IDLE does syntax highlighting and a lot
more such as allowing you to run your programs within IDLE among other things. A special note: don't
use Notepad - it is a bad choice because it does not do syntax highlighting and also importantly it does
not support indentation of the text which is very important in our case as we will see later. Good editors
such as IDLE (and also VIM) will automatically help you do this.
If you are using Linux/FreeBSD, then you have a lot of choices for an editor. If you are an experienced
programmer, then you must be already using VIM or Emacs. Needless to say, these are two of the most
powerful editors and you will be benefitted by using them to write your Python programs. I personally
use VIM for most of my programs. If you are a beginner programmer, then you can use Kate which is
one of my favorites. In case you are willing to take the time to learn VIM or Emacs, then I highly re-
commend that you do learn to use either of them as it will be very useful for you in the long run.
If you still want to explore other choices of an editor, see the comprehensive list of Python editors
[http://www.python.org/cgi-bin/moinmoin/PythonEditors] and make your choice. You can also choose
an IDE (Integrated Development Environment) for Python. See the comprehensive list of IDEs that sup-
port Python [http://www.python.org/cgi-bin/moinmoin/IntegratedDevelopmentEnvironments] for more
details. Once you start writing large Python programs, IDEs can be very useful indeed.
I repeat once again, please choose a proper editor - it can make writing Python programs more fun and
easy.
Using a Source File
Now let's get back to programming. There is a tradition that whenever you learn a new programming
language, the first program that you write and run is the 'Hello World' program - all it does is just say
'Hello World' when you run it. As Simon Cozens 1 puts it, it is the 'traditional incantation to the pro-
gramming gods to help you learn the language better' :) .
Start your choice of editor, enter the following program and save it as helloworld.py
Example 3.2. Using a Source File
#!/usr/bin/python
# Filename : helloworld.py
print 'Hello World'
(Source file: code/helloworld.py)
Run this program by opening a shell (Linux terminal or DOS prompt) and entering the command py-
thon helloworld.py. If you are using IDLE, use the menu Edit -> Run Script or the keyboard short-
cut Ctrl-F5. The output is as shown below.
Output
First Steps
7

$ python helloworld.py
Hello World
If you got the output as shown above, congratulations! - you have successfully run your first Python pro-
gram.
In case you got an error, please type the above program exactly as shown and above and run the program
again. Note that Python is case-sensitive i.e. print is not the same as Print - note the lowercase p in
the former and the uppercase P in the latter. Also, ensure there are no spaces or tabs before the first char-
acter in each line - we will see why this is important later.
How It Works
Let us consider the first two lines of the program. These are called comments - anything to the right of
the # symbol is a comment and is mainly useful as notes for the reader of the program.
Python does not use comments except for the special case of the first line here. It is called the shebang
line - whenever the first two characters of the source file are #! followed by the location of a program,
this tells your Linux/Unix system that this program should be run with this interpreter when you execute
the program. This is explained in detail in the next section. Note that you can always run the program on
any platform by specifying the interpreter directly on the command line such as the command python
helloworld.py .
Important
Use comments sensibly in your program to explain some important details of your program -
this is useful for readers of your program so that they can easily understand what the program is
doing. Remember, that person can be yourself after six months!
The comments are followed by a Python statement - this just prints the text 'Hello World'. The
print is actually an operator and 'Hello World' is referred to as a string - don't worry, we will ex-
plore these terminologies in detail later.
Executable Python programs
This applies only to Linux/Unix users but Windows users might be curious as well about the first line of
the program. First, we have to give the program executable permission using the chmod command then
run the source program.
$ chmod a+x helloworld.py
$ ./helloworld.py
Hello World
The chmod command is used here to change the mode of the file by giving execute permission to all
users of the system. Then, we execute the program directly by specifying the location of the source file.
We use the ./ to indicate that the program is located in the current directory.
To make things more fun, you can rename the file to just helloworld and run it as ./helloworld and it
First Steps
8

will still work since the system knows that it has to run the program using the interpreter whose location
is specified in the first line in the source file.
You are now able to run the program as long as you know the exact path of the program - but what if
you wanted to be able to run the program from anywhere? You can do this by storing the program in one
of the directories listed in the PATH environment variable. Whenever you run any program, the system
looks for that program in each of the directories listed in the PATH environment variable and then runs
that program. We can make this program available everywhere by simply copying this source file to one
of the directories listed in PATH.
$ echo $PATH
/opt/mono/bin:/usr/local/bin:/usr/bin:/bin:/usr/X11R6/bin:/home/swaroop/bin
$ cp helloworld.py /home/swaroop/bin/helloworld
$ helloworld
Hello World
We can display the PATH variable using the echo command and prefixing the variable name by $ to in-
dicate to the shell that we need the value of this variable. We see that /home/swaroop/bin is one of
the directories in the PATH variable where swaroop is the username I am using in my system. There
will usually be a similar directory for your username on your system. Alternatively, you can add a dir-
ectory of your choice to the PATH variable - this can be done by running
PATH=$PATH:/home/swaroop/mydir where '/home/swaroop/mydir' is the directory I want to
add to the PATH variable.
This method is very useful if you want to write useful scripts that you want to run the program anytime,
anywhere. It is like creating your own commands just like cd or any other commands that you use in the
Linux terminal or DOS prompt.
Caution
W.r.t. Python, a program or a script or software all mean the same thing.
Getting Help
If you need quick information about any function or statement in Python, then you can use the built-in
help functionality. This is very useful especially when using the interpreter prompt. For example, run
help(str) - this displays the help for the str class which is used to store all text (strings) that you
use in your program. Classes will be explained in detail in the chapter on object-oriented programming.
Note
Press q to exit the help.
Similarly, you can obtain information about almost anything in Python. Use help() to learn more
about using help itself!
In case you need to get help for operators like print, then you need to set the PYTHONDOCS environ-
ment variable appropriately. This can be done easily on Linux/Unix using the env command.
$ env PYTHONDOCS=/usr/share/doc/python-docs-2.3.4/html/ python
Python 2.3.4 (#1, Oct 26 2004, 16:42:40)
[GCC 3.4.2 20041017 (Red Hat 3.4.2-6.fc3)] on linux2
First Steps
9

Type "help", "copyright", "credits" or "license" for more information.
>>> help('print')
You will notice that I have used quotes to specify 'print' so that Python can understand that I want
to fetch help about 'print' and I am not asking it to print something.
Note that the location I have used is the location in Fedora Core 3 Linux - it may be different for differ-
ent distributions and versions.
Summary
You should now be able to write, save and run Python programs at ease. Now that you are a Python
user, let's learn some more Python concepts.
First Steps
10

Chapter 4. The Basics
Just printing 'Hello World' is not enough, is it? You want to do more than that - you want to take some
input, manipulate it and get something out of it. We can achieve this in Python using constants and vari-
ables.
Literal Constants
An example of a literal constant is a number like 5, 1.23, 9.25e-3 or a string like 'This is a
string' or "It's a string!". It is called a literal because it is literal - you use its value liter-
ally. The number 2 always represents itself and nothing else - it is a constant because its value cannot be
changed. Hence, all these are referred to as literal constants.
Numbers
Numbers in Python are of four types - integers, long integers, floating point and complex numbers.
• Examples of integers are 2 which are just whole numbers.
• Long integers are just bigger whole numbers.
• Examples of floating point numbers (or floats for short) are 3.23 and 52.3E-4. The E notation in-
dicates powers of 10. In this case, 52.3E-4 means 52.3 * 10-4.
• Examples of complex numbers are (-5+4j) and (2.3 - 4.6j)
Strings
A string is a sequence of characters. Strings are basically just a bunch of words.
I can almost guarantee that you will be using strings in almost every Python program that you write, so
pay attention to the following part. Here's how you use strings in Python:
•
Using Single Quotes (')
You can specify strings using single quotes such as 'Quote me on this' . All white space i.e.
spaces and tabs are preserved as-is.
•
Using Double Quotes (")
Strings in double quotes work exactly the same way as strings in single quotes. An example is
"What's your name?"
•
Using Triple Quotes (''' or """)
You can specify multi-line strings using triple quotes. You can use single quotes and double quotes
freely within the triple quotes. An example is
11

'''This is a multi-line string. This is the first line.
This is the second line.
"What's your name?," I asked.
He said "Bond, James Bond."
'''
•
Escape Sequences
Suppose, you want to have a string which contains a single quote ('), how will you specify this
string? For example, the string is What's your name?. You cannot specify 'What's your
name?' because Python will be confused as to where the string starts and ends. So, you will have to
specify that this single quote does not indicate the end of the string. This can be done with the help
of what is called an escape sequence. You specify the single quote as ' - notice the backslash.
Now, you can specify the string as 'What's your name?'.
Another way of specifying this specific string would be "What's your name?" i.e. using
double quotes. Similarly, you have to use an escape sequence forusing a double quote itself in a
double quoted string. Also, you have to indicate the backslash itself using the escape sequence .
What if you wanted to specify a two-line string? One way is to use a triple-quoted string as shown
above or you can use an escape sequence for the newline character - n to indicate the start of a new
line. An example is This is the first linenThis is the second line . Another
useful escape sequence to know is the tab - t. There are many more escape sequences but I have
mentioned only the most useful ones here.
One thing to note is that in a string, a single backslash at the end of the line indicates that the string
is continued in the next line, but no newline is added. For example,
"This is the first sentence.
This is the second sentence."
is equivalent to "This is the first sentence. This is the second sen-
tence."
•
Raw Strings
If you need to specify some strings where no special processing such as escape sequences are
handled, then what you need is to specify a raw string by prefixing r or R to the string. An example
is r"Newlines are indicated by n".
•
Unicode Strings
Unicode is a standard way of writing international text. If you want to write text in your native lan-
guage such as Hindi or Arabic, then you need to have a Unicode-enabled text editor. Similarly, Py-
thon allows you to handle Unicode text - all you need to do is prefix u or U. For example, u"This
is a Unicode string.".
The Basics
12

Remember to use Unicode strings when you are dealing with text files, especially when you know
that the file will contain text written in languages other than English.
•
Strings are immutable
This means that once you have created a string, you cannot change it. Although this might seem like
a bad thing, it really isn't. We will see why this is not a limitation in the various programs that we see
later on.
•
String literal concatenation
If you place two string literals side by side, they are automatically concatenated by Python. For ex-
ample, 'What's' 'your name?' is automatically converted in to "What's your
name?".
Note for C/C++ Programmers
There is no separate char data type in Python. There is no real need for it and I am sure you
won't miss it.
Note for Perl/PHP Programmers
Remember that single-quoted strings and double-quoted strings are the same - they do not dif-
fer in any way.
Note for Regular Expression Users
Always use raw strings when dealing with regular expressions. Otherwise, a lot of backwhack-
ing may be required. For example, backreferences can be referred to as '1' or r'1'.
Variables
Using just literal constants can soon become boring - we need some way of storing any information and
manipulate them as well. This is where variables come into the picture. Variables are exactly what they
mean - their value can vary i.e. you can store anything using a variable. Variables are just parts of your
computer's memory where you store some information. Unlike literal constants, you need some method
of accessing these variables and hence you give them names.
Identifier Naming
Variables are examples of identifiers. Identifiers are names given to identify something. There are some
rules you have to follow for naming identifiers:
• The first character of the identifier must be a letter of the alphabet (upper or lowercase) or an under-
score ('_').
• The rest of the identifier name can consist of letters (upper or lowercase), underscores ('_') or digits
(0-9).
• Identifier names are case-sensitive. For example, myname and myName are not the same. Note the
lowercase n in the former and the uppercase N in te latter.
The Basics
13

• Examples of valid identifier names are i, __my_name, name_23 and a1b2_c3.
• Examples of invalid identifier names are 2things, this is spaced out and my-name.
Data Types
Variables can hold values of different types called data types. The basic types are numbers and strings,
which we have already discussed. In later chapters, we will see how to create our own types using
classes.
Objects
Remember, Python refers to anything used in a program as an object. This is meant in the generic sense.
Instead of saying 'the something', we say 'the object'.
Note for Object Oriented Programming users
Python is strongly object-oriented in the sense that everything is an object including numbers,
strings and even functions.
We will now see how to use variables along with literal constants. Save the following example and run
the program.
How to write Python programs
Henceforth, the standard procedure to save and run a Python program is as follows:
1. Open your favorite editor.
2. Enter the program code given in the example.
3. Save it as a file with the filename mentioned in the comment. I follow the convention of
having all Python programs saved with the extension .py.
4. Run the interpreter with the command python program.py or use IDLE to run the pro-
grams. You can also use the executable method as explained earlier.
Example 4.1. Using Variables and Literal constants
# Filename : var.py
i = 5
print i
i = i + 1
print i
s = '''This is a multi-line string.
This is the second line.'''
print s
The Basics
14

Output
$ python var.py
5
6
This is a multi-line string.
This is the second line.
How It Works
Here's how this program works. First, we assign the literal constant value 5 to the variable i using the
assignment operator (=). This line is called a statement because it states that something should be done
and in this case, we connect the variable name i to the value 5. Next, we print the value of i using the
print statement which, unsurprisingly, just prints the value of the variable to the screen.
The we add 1 to the value stored in i and store it back. We then print it and expectedly, we get the value
6.
Similarly, we assign the literal string to the variable s and then print it.
Variables are used by just assigning them a value. No declaration or data type definition is
needed/used.
Logical and Physical Lines
A physical line is what you see when you write the program. A logical line is what Python sees as a
single statement. Python implicitly assumes that each physical line corresponds to a logical line.
An example of a logical line is a statement like print 'Hello World' - if this was on a line by it-
self (as you see it in an editor), then this also corresponds to a physical line.
Implicitly, Python encourages the use of a single statement per line which makes code more readable.
If you want to specify more than one logical line on a single physical line, then you have to explicitly
specify this using a semicolon (;) which indicates the end of a logical line/statement. For example,
i = 5
print i
is effectively same as
The Basics
15

i = 5;
print i;
and the same can be written as
i = 5; print i;
or even
i = 5; print i
However, I strongly recommend that you stick to writing a single logical line in a single physical line
only. Use more than one physical line for a single logical line only if the logical line is really long. The
idea is to avoid the semicolon as far as possible since it leads to more readable code. In fact, I have nev-
er used or even seen a semicolon in a Python program.
An example of writing a logical line spanning many physical lines follows. This is referred to as explicit
line joining.
s = 'This is a string.
This continues the string.'
print s
This gives the output:
This is a string. This continues the string.
Similarly,
print
i
is the same as
The Basics
16

print i
Sometimes, there is an implicit assumption where you don't need to use a backslash. This is the case
where the logical line uses parentheses, square brackets or curly braces. This is is called implicit line
joining. You can see this in action when we write programs using lists in later chapters.
Indentation
Whitespace is important in Python. Actually, whitespace at the beginning of the line is important.
This is called indentation. Leading whitespace (spaces and tabs) at the beginning of the logical line is
used to determine the indentation level of the logical line, which in turn is used to determine the group-
ing of statements.
This means that statements which go together must have the same indentation. Each such set of state-
ments is called a block. We will see examples of how blocks are important in later chapters.
One thing you should remember is how wrong indentation can give rise to errors. For example:
i = 5
print 'Value is', i # Error! Notice a single space at the start of the line
print 'I repeat, the value is', i
When you run this, you get the following error:
File "whitespace.py", line 4
print 'Value is', i # Error! Notice a single space at the start of the line
^
SyntaxError: invalid syntax
Notice that there is a single space at the beginning of the second line. The error indicated by Python tells
us that the syntax of the program is invalid i.e. the program was not properly written. What this means to
you is that you cannot arbitrarily start new blocks of statements (except for the main block which you
have been using all along, of course). Cases where you can use new blocks will be detailed in later
chapters such as the control flow chapter.
How to indent
Do not use a mixture of tabs and spaces for the indentation as it does not work across different
platforms properly. I strongly recommend that you use a single tab or two or four spaces for
each indentation level.
Choose any of these three indentation styles. More importantly, choose one and use it consist-
ently i.e. use that indentation style only.
The Basics
17

Summary
Now that we have gone through many nitty-gritty details, we can move on to more interesting stuff such
as control flow statements. Be sure to become comfortable with what you have read in this chapter.
The Basics
18

Chapter 5. Operators and Expressions
Introduction
Most statements (logical lines) that you write will contain expressions. A simple example of an expres-
sion is 2 + 3. An expression can be broken down into operators and operands.
Operators are functionality that do something and can be represented by symbols such as + or by special
keywords. Operators require some data to operate on and such data are called operands. In this case, 2
and 3 are the operands.
Operators
We will briefly take a look at the operators and their usage:
Tip
You can evaluate the expressions given in the examples using the interpreter interactively. For
example, to test the expression 2 + 3, use the interactive Python interpreter prompt:
>>> 2 + 3
5
>>> 3 * 5
15
>>>
Table 5.1. Operators and their usage
Operator Name Explanation Examples
+ Plus Adds the two objects 3 + 5 gives 8. 'a' +
'b' gives 'ab'.
- Minus Either gives a negative
number or gives the sub-
traction of one number
from the other
-5.2 gives a negative
number. 50 - 24
gives 26.
* Multiply Gives the multiplication
of the two numbers or
returns the string re-
peated that many times.
2 * 3 gives 6. 'la'
* 3 gives 'lalala'.
** Power Returns x to the power
of y
3 ** 4 gives 81 (i.e. 3
* 3 * 3 * 3)
/ Divide Divide x by y 4/3 gives 1 (division of
integers gives an in-
teger). 4.0/3 or
4/3.0 gives
1.33333333333333
33
19

// Floor Division Returns the floor of the
quotient
4 // 3.0 gives 1.0
% Modulo Returns the remainder of
the division
8%3 gives 2. -
25.5%2.25 gives 1.5
.
<< Left Shift Shifts the bits of the
number to the left by the
number of bits specified.
(Each number is repres-
ented in memory by bits
or binary digits i.e. 0 and
1)
2 << 2 gives 8. - 2 is
represented by 10 in
bits. Left shifting by 2
bits gives 1000 which
represents the decimal 8.
>> Right Shift Shifts the bits of the
number to the right by
the number of bits spe-
cified.
11 >> 1 gives 5 - 11
is represented in bits by
1011 which when right
shifted by 1 bit gives
101 which is nothing
but decimal 5.
& Bitwise AND Bitwise AND of the
numbers
5 & 3 gives 1.
| Bit-wise OR Bitwise OR of the num-
bers
5 | 3 gives 7
^ Bit-wise XOR 5 ^ 3 gives 6
~ Bit-wise invert The bit-wise inversion
of x is -(x+1)
~5 gives -6.
< Less Than Returns whether x is less
than y. All comparison
operators return 1 for
true and 0 for false. This
is equivalent to the spe-
cial variables True and
False respectively.
Note the capitalization
of these variables'
names.
5 < 3 gives 0 (i.e.
False) and 3 < 5
gives 1 (i.e. True).
Comparisons can be
chained arbitrarily: 3 < 5
< 7 gives True.
> Greater Than Returns whether x is
greater than y
5 < 3 returns True. If
both operands are num-
bers, they are first con-
verted to a common
type. Otherwise, it al-
ways returns False.
<= Less Than or Equal To Returns whether x is less
than or equal to y
x = 3; y = 6; x
<= y returns True.
>= Greater Than or Equal
To
Returns whether x is
greater than or equal to y
x = 4; y = 3; x >= 3 re-
turns True.
== Equal To Compares if the objects
are equal
x = 2; y = 2; x
== y returns True. x
= 'str'; y =
'stR'; x == y re-
turns False. x =
'str'; y =
'str'; x == y re-
Operators and Expressions
20

turns True.
!= Not Equal To Compares if the objects
are not equal
x = 2; y = 3; x
!= y returns True.
not Boolean NOT If x is True, it returns
False. If x is False,
it returns True.
x = True; not y
returns False.
and Boolean AND x and y returns
False if x is False,
else it returns evaluation
of y
x = False; y =
True; x and y re-
turns False since x is
False. In this case, Py-
thon will not evaluate y
since it knows that the
value of the expression
will has to be false
(since x is False). This is
called short-circuit eval-
uation.
or Boolean OR If x is True, it returns
True, else it returns eval-
uation of y
x = True; y =
False; x or y re-
turns True. Short-cir-
cuit evaluation applies
here as well.
Operator Precedence
If you had an expression such as 2 + 3 * 4, is the addition done first or the multiplication? Our high
school maths tells us that the multiplication should be done first - this means that the multiplication op-
erator has higher precedence than the addition operator.
The following table gives the operator precedence table for Python, from the lowest precedence (least
binding) to the highest precedence (most binding). This means that in a given expression, Python will
first evaluate the operators lower in the table before the operators listed higher in the table.
The following table (same as the one in the Python reference manual) is provided for the sake of com-
pleteness. However, I advise you to use parentheses for grouping of operators and operands in order to
explicitly specify the precedence and to make the program as readable as possible. For example, 2 +
(3 * 4) is definitely more clearer than 2 + 3 * 4. As with everything else, the parentheses shold
be used sensibly and should not be redundant (as in 2 + (3 + 4)).
Table 5.2. Operator Precedence
Operator Description
lambda Lambda Expression
or Boolean OR
and Boolean AND
not x Boolean NOT
in, not in Membership tests
is, is not Identity tests
<, <=, >, >=, !=, == Comparisons
21

Operator Description
| Bitwise OR
^ Bitwise XOR
& Bitwise AND
<<, >> Shifts
+, - Addition and subtraction
*, /, % Multiplication, Division and Remainder
+x, -x Positive, Negative
~x Bitwise NOT
** Exponentiation
x.attribute Attribute reference
x[index] Subscription
x[index:index] Slicing
f(arguments ...) Function call
(expressions, ...) Binding or tuple display
[expressions, ...] List display
{key:datum, ...} Dictionary display
`expressions, ...` String conversion
The operators which we have not already come across will be explained in later chapters.
Operators with the same same precedence are listed in the same row in the above table. For example, +
and - have the same precedence.
Order of Evaluation
By default, the operator precedence table decides which operators are evaluated before others. However,
if you want to change the orer in which they are evaluated, you can use parentheses. For example, if you
want addition to be evaluated before multiplication in an expression, then you can write something like
(2 + 3) * 4.
Associativity
Operators are usually associated from left to right i.e. operators with same precedence are evaluated in a
left to right manner. For example, 2 + 3 + 4 is evaluated as (2 + 3) + 4. Some operators like
assignment operators have right to left associativity i.e. a = b = c is treated as a = (b = c).
Expressions
Using Expressions
Example 5.1. Using Expressions
#!/usr/bin/python
22

# Filename: expression.py
length = 5
breadth = 2
area = length * breadth
print 'Area is', area
print 'Perimeter is', 2 * (length + breadth)
Output
$ python expression.py
Area is 10
Perimeter is 14
How It Works
The length and breadth of the rectangle are stored in variables by the same name. We use these to calcu-
late the area and perimieter of the rectangle with the help of expressions. We store the result of the ex-
pression length * breadth in the variable area and then print it using the print statement. In
the second case, we directly use the value of the expression 2 * (length + breadth) in the print
statement.
Also, notice how Python 'pretty-prints' the output. Even though we have not specified a space between
'Area is' and the variable area, Python puts it for us so that we get a clean nice output and the pro-
gram is much more readable this way (since we don't need to worry about spacing in the output). This is
an example of how Python makes life easy for the programmer.
Summary
We have seen how to use operators, operands and expressions - these are the basic building blocks of
any program. Next, we will see how to make use of these in our programs using statements.
23

Chapter 6. Control Flow
Introduction
In the programs we have seen till now, there has always been a series of statements and Python faith-
fully executes them in the same order. What if you wanted to change the flow of how it works? For ex-
ample, you want the program to take some decisions and do different things depending on different situ-
ations such as printing 'Good Morning' or 'Good Evening' depending on the time of the day?
As you might have guessed, this is achieved using control flow statements. There are three control flow
statements in Python - if, for and while.
The if statement
The if statement is used to check a condition and if the condition is true, we run a block of statements
(called the if-block), else we process another block of statements (called the else-block). The else clause
is optional.
Using the if statement
Example 6.1. Using the if statement
#!/usr/bin/python
# Filename: if.py
number = 23
guess = int(raw_input('Enter an integer : '))
if guess == number:
print 'Congratulations, you guessed it.' # New block starts here
print "(but you do not win any prizes!)" # New block ends here
elif guess < number:
print 'No, it is a little higher than that' # Another block
# You can do whatever you want in a block ...
else:
print 'No, it is a little lower than that'
# you must have guess > number to reach here
print 'Done'
# This last statement is always executed, after the if statement is executed
Output
$ python if.py
Enter an integer : 50
No, it is a little lower than that
24

Done
$ python if.py
No, it is a little higher than that
Done
$ python if.py
Congratulations, you guessed it.
(but you do not win any prizes!)
Done
How It Works
In this program, we take guesses from the user and check if it is the number that we have. We set the
variable number to any integer we want, say 23. Then, we take the user's guess using the
raw_input() function. Functions are just reusable pieces of programs. We'll read more about them in
the next chapter.
We supply a string to the built-in raw_input function which prints it to the screen and waits for input
from the user. Once we enter something and press enter, the function returns the input which in the case
of raw_input is a string. We then convert this string to an integer using int and then store it in the
variable guess. Actually, the int is a class but all you need to know right now is that you can use it to
convert a string to an integer (assuming the string contains a valid integer in the text).
Next, we compare the guess of the user with the number we have chosen. If they are equal, we print a
success message. Notice that we use indentation levels to tell Python which statements belong to which
block. This is why indentation is so important in Python. I hope you are sticking to 'one tab per indenta-
tion level' rule. Are you?
Notice how the if statement contains a colon at the end - we are indicating to Python that a block of
statements follows.
Then, we check if the guess is less than the number, and if so, we inform the user to guess a little higher
than that. What we have used here is the elif clause which actually combines two related if else-
if else statements into one combined if-elif-else statement. This makes the program easier
and reduces the amount of indentation required.
The elif and else statements must also have a colon at the end of the logical line followed by their
corresponding block of statements (with proper indentation, of course)
You can have another if statement inside the if-block of an if statement and so on - this is called a
nested if statement.
Remember that the elif and else parts are optional. A minival valid if statement is
if True:
print 'Yes, it is true'
After Python has finished executing the complete if statement along with the assocated elif and
else clauses, it moves on to the next statement in the block containing the if statement. In this case, it
is the main block where execution of the program starts and the next statement is the print 'Done'
statement. After this, Python sees the ends of the program and simply finishes up.
Control Flow
25

Although this is a very simple program, I have been pointing out a lot of things that you should notice
even in this simple program. All these are pretty straightforward (and surprisingly simple for those of
you from C/C++ backgrounds) and requires you to become aware of all these initially, but after that, you
will become comfortable with it and it'll feel 'natural' to you.
There is no switch statement in Python. You can use an if..elif..else statement to do
the same thing (and in some cases, use a dictionary to do it quickly)
The while statement
The while statement allows you to repeatedly execute a block of statements as long as a condition is
true. A while statement is an example of what is called a looping statement. A while statement can
have an optional else clause.
Using the while statement
Example 6.2. Using the while statement
#!/usr/bin/python
# Filename: while.py
number = 23
running = True
while running:
guess = int(raw_input('Enter an integer : '))
if guess == number:
print 'Congratulations, you guessed it.'
running = False # this causes the while loop to stop
elif guess < number:
print 'No, it is a little higher than that.'
else:
print 'No, it is a little lower than that.'
else:
print 'The while loop is over.'
# Do anything else you want to do here
print 'Done'
Output
$ python while.py
No, it is a little lower than that.
No, it is a little higher than that.
Control Flow
26

Congratulations, you guessed it.
The while loop is over.
Done
How It Works
In this program, we are still playing the guessing game, but the advantage is that the user is allowed to
keep guessing until he guesses correctly - there is no need to repeatedly execute the program for each
guess as we have done previously. This aptly demonstrates the use of the while statement.
We move the raw_input and if statements to inside the while loop and set the variable running
to True before the while loop. First, we check if the variable running is True and then proceed to
execute the corresponding while-block. After this block is executed, the condition is again checked
which in this case is the running variable. If it is true, we execute the while-block again, else we con-
tinue to execute the optional else-block and then continue to the next statement.
The else block is executed when the while loop condition becomes False - this may even be the
first time that the condition is checked. If there is an else clause for a while loop, it is always ex-
ecuted unless you have a while loop which loops forever without ever breaking out!
The True and False are called Boolean types and you can consider them to be equivalent to the value
1 and 0 respecitvely. It's important to use these where the condition or checking is important and not the
actual value such as 1.
The else-block is actually redundant since you can put those statements in the same block (as the while
statement) after the while statement to get the same effect.
Remember that you can have an else clause for the while loop.
The for loop
The for..in statement is another looping statement which iterates over a sequence of objects i.e. go
through each item in a sequence. We will see more about sequences in detail in later chapters. What you
need to know right now is that a sequence is just an ordered collection of items.
Using the for statement
Example 6.3. Using the for statement
#!/usr/bin/python
# Filename: for.py
for i in range(1, 5):
print i
else:
print 'The for loop is over'
Control Flow
27

Output
$ python for.py
1
2
3
4
The for loop is over
How It Works
In this program, we are printing a sequence of numbers. We generate this sequence of numbers using hte
built-in range function.
What we do here is supply it two numbers and range returns a sequence of numbers starting from the
first number and up to the second number. For example, range(1,5) gives the sequence [1, 2,
3, 4]. By default, range takes a step count of 1. If we supply a third number to range, then that be-
comes the step count. For example, range(1,5,2) gives [1,3]. Remember that the range extends
up to the second number i.e. it does not include the second number.
The for loop then iterates over this range - for i in range(1,5) is equivalent to for i in
[1, 2, 3, 4] which is like assigning each number (or object) in the sequence to i, one at a time, and
then executing the block of statements for each value of i. In this case, we just print the value in the
block of statements.
Remember that the else part is optional. When included, it is always executed once after the for loop
is over unless a break statement is encountered.
Remember that the for..in loop works for any sequence. Here, we have a list of numbers generated
by the built-in range function, but in general we can use any kind of sequence of any kind of objects!
We will explore this idea in detail in later chapters.
Note for C/C++/Java/C# Programmers
The Python for loop is radically different from the C/C++ for loop. C# programmers will
note that the for loop in Python is similar to the foreach loop in C#. Java programmers will
note that the same is similar to for (int i : IntArray) in Java 1.5 .
In C/C++, if you want to write for (int i = 0; i < 5; i++), then in Python you
write just for i in range(0,5). As you can see, the for loop is simpler, more express-
ive and less error prone in Python.
The break statement
The break statement is used to break out of a loop statement i.e. stop the execution of a looping state-
ment, even if the loop condition has not become False or the sequence of items has been completely
iterated over.
An important note is that if you break out of a for or while loop, any corresponding loop else block
is not executed.
Using the break statement
Control Flow
28

Example 6.4. Using the break statement
#!/usr/bin/python
# Filename: break.py
while True:
s = raw_input('Enter something : ')
if s == 'quit':
break
print 'Length of the string is', len(s)
print 'Done'
Output
$ python break.py
Enter something : Programming is fun
Length of the string is 18
Enter something : When the work is done
Enter something : if you wanna make your work also fun:
Enter something : use Python!
Enter something : quit
Done
How It Works
In this program, we repeatedly take the user's input and print the length of each input each time. We are
providing a special condition to stop the program by checking if the user input is 'quit'. We stop the
program by breaking out of the loop and reach the end of the program.
The length of the input string can be found out using the built-in len function.
Remember that the break statement can be used with the for loop as well.
G2's Poetic Python
The input I have used here is a mini poem I have written called G2's Poetic Python:
Programming is fun
When the work is done
if you wanna make your work also fun:
use Python!
Control Flow
29

The continue statement
The continue statement is used to tell Python to skip the rest of the statements in the current loop
block and to continue to the next iteration of the loop.
Using the continue statement
Example 6.5. Using the continue statement
#!/usr/bin/python
# Filename: continue.py
while True:
s = raw_input('Enter something : ')
if s == 'quit':
break
if len(s) < 3:
continue
print 'Input is of sufficient length'
# Do other kinds of processing here...
Output
$ python continue.py
Enter something : a
Enter something : 12
Enter something : abc
Input is of sufficient length
Enter something : quit
How It Works
In this program, we accept input from the user, but we process them only if they are at least 3 characters
long. So, we use the built-in len function to get the length and if the length is less than 3, we skip the
rest of the statements in the block by using the continue statement. Otherwise, the rest of the state-
ments in the loop are executed and we can do any kind of processing we want to do here.
Note that the continue statement works with the for loop as well.
Summary
We have seen how to use the three control flow statements - if, while and for along with their asso-
ciated break and continue statements. These are some of the most often used parts of Python and
hence, becoming comfortable with them is essential.
Control Flow
30

Next, we will see how to create and use functions.
Control Flow
31

Chapter 7. Functions
Introduction
Functions are reusable pieces of programs. They allow you to give a name to a block of statements and
you can run that block using that name anywhere in your program and any number of times. This is
known as calling the function. We have already used many built-in functions such as the len and
range.
Functions are defined using the def keyword. This is followed by an identifier name for the function
followed by a pair of parentheses which may enclose some names of variables and the line ends with a
colon. Next follows the block of statements that are part of this function. An example will show that this
is actually very simple:
Defining a Function
Example 7.1. Defining a function
#!/usr/bin/python
# Filename: function1.py
def sayHello():
print 'Hello World!' # block belonging to the function
# End of function
sayHello() # call the function
Output
$ python function1.py
Hello World!
How It Works
We define a function called sayHello using the syntax as explained above. This function takes no
parameters and hence there are no variables declared in the parentheses. Parameters to functions are just
input to the function so that we can pass in different values to it and get back corresponding results.
Function Parameters
A function can take parameters which are just values you supply to the function so that the function can
do something utilising those values. These parameters are just like variables except that the values of
32

these variables are defined when we call the function and are not assigned values within the function it-
self.
Parameters are specified within the pair of parentheses in the function definition, separated by commas.
When we call the function, we supply the values in the same way. Note the terminology used - the
names given in the function definition are called parameters whereas the values you supply in the func-
tion call are called arguments.
Using Function Parameters
Example 7.2. Using Function Parameters
#!/usr/bin/python
# Filename: func_param.py
def printMax(a, b):
if a > b:
print a, 'is maximum'
else:
print b, 'is maximum'
printMax(3, 4) # directly give literal values
x = 5
y = 7
printMax(x, y) # give variables as arguments
Output
$ python func_param.py
4 is maximum
7 is maximum
How It Works
Here, we define a function called printMax where we take two parameters called a and b. We find
out the greater number using a simple if..else statement and then print the bigger number.
In the first usage of printMax, we directly supply the numbers i.e. arguments. In the second usage, we
call the function using variables. printMax(x, y) causes value of argument x to be assigned to
parameter a and the value of argument y assigned to parameter b. The printMax function works the
same in both the cases.
Local Variables
When you declare variables inside a function definition, they are not related in any way to other vari-
Functions
33

ables with the same names used outside the function i.e. variable names are local to the function. This is
called the scope of the variable. All variables have the scope of the block they are declared in starting
from the point of definition of the name.
Using Local Variables
Example 7.3. Using Local Variables
#!/usr/bin/python
# Filename: func_local.py
def func(x):
print 'x is', x
x = 2
print 'Changed local x to', x
x = 50
func(x)
print 'x is still', x
Output
$ python func_local.py
x is 50
Changed local x to 2
x is still 50
How It Works
In the function, the first time that we use the value of the name x, Python uses the value of the parameter
declared in the function.
Next, we assign the value 2 to x. The name x is local to our function. So, when we change the value of
x in the function, the x defined in the main block remains unaffected.
In the last print statement, we confirm that the value of x in the main block is actually unaffected.
Using the global statement
If you want to assign a value to a name defined outside the function, then you have to tell Python that
the name is not local, but it is global. We do this using the global statement. It is impossible to assign
a value to a variable defined outside a function without the global statement.
You can use the values of such variables defined outside the function (assuming there is no variable with
the same name within the function). However, this is not encouraged and should be avoided since it be-
comes unclear to the reader of the program as to where that variable's definition is. Using the global
Functions
34

statement makes it amply clear that the variable is defined in an outer block.
Example 7.4. Using the global statement
#!/usr/bin/python
# Filename: func_global.py
def func():
global x
print 'x is', x
x = 2
print 'Changed global x to', x
x = 50
func()
print 'Value of x is', x
Output
$ python func_global.py
x is 50
Changed global x to 2
Value of x is 2
How It Works
The global statement is used to decare that x is a global variable - hence, when we assign a value to x
inside the function, that change is reflected when we use the value of x in the main block.
You can specify more than one global variable using the same global statement. For example, glob-
al x, y, z.
Default Argument Values
For some functions, you may want to make some of its parameters as optional and use default values if
the user does not want to provide values for such parameters. This is done with the help of default argu-
ment values. You can specify default argument values for parameters by following the parameter name
in the function definition with the assignment operator (=) followed by the default value.
Note that the default argument value should be a constant. More precisely, the default argument value
should be immutable - this is explained in detail in later chapters. For now, just remember this.
Using Default Argument Values
Functions
35

Example 7.5. Using Default Argument Values
#!/usr/bin/python
# Filename: func_default.py
def say(message, times = 1):
print message * times
say('Hello')
say('World', 5)
Output
$ python func_default.py
Hello
WorldWorldWorldWorldWorld
How It Works
The function named say is used to print a string as many times as want. If we don't supply a value, then
by default, the string is printed just once. We achieve this by specifying a default argument value of 1 to
the parameter times.
In the first usage of say, we supply only the string and it prints the string once. In the second usage of
say, we supply both the string and an argument 5 stating that we want to say the string message 5
times.
Important
Only those parameters which are at the end of the parameter list can be given default argument
values i.e. you cannot have a parameter with a default argument value before a parameter
without a default argument value in the order of parameters declared in the function parameter
list.
This is because the values are assigned to the parameters by position. For example, def
func(a, b=5) is valid, but def func(a=5, b) is not valid.
Keyword Arguments
If you have some functions with many parameters and you want to specify only some of them, then you
can give values for such parameters by naming them - this is called keyword arguments - we use the
name (keyword) instead of the position (which we have been using all along) to specify the arguments to
the function.
There are two advantages - one, using the function is easier since we do not need to worry about the or-
Functions
36

der of the arguments. Two, we can give values to only those parameters which we want, provided that
the other parameters have default argument values.
Using Keyword Arguments
Example 7.6. Using Keyword Arguments
#!/usr/bin/python
# Filename: func_key.py
def func(a, b=5, c=10):
print 'a is', a, 'and b is', b, 'and c is', c
func(3, 7)
func(25, c=24)
func(c=50, a=100)
Output
$ python func_key.py
a is 3 and b is 7 and c is 10
How It Works
The function named func has one parameter without default argument values, followed by two para-
meters with default argument values.
In the first usage, func(3, 7), the parameter a gets the value 3, the parameter b gets the value 5 and
c gets the default value of 10.
In the second usage func(25, c=24), the variable a gets the value of 25 due to the position of the
argument. Then, the parameter c gets the value of 24 due to naming i.e. keyword arguments. The vari-
able b gets the default value of 5.
In the third usage func(c=50, a=100), we use keyword arguments completely to specify the val-
ues. Notice, that we are specifying value for parameter c before that for a even though a is defined be-
fore c in the function definition.
The return statement
The return statement is used to return from a function i.e. break out of the function. We can option-
ally return a value from the function as well.
Functions
37

Using the literal statement
Example 7.7. Using the literal statement
#!/usr/bin/python
# Filename: func_return.py
def maximum(x, y):
if x > y:
return x
else:
return y
print maximum(2, 3)
Output
$ python func_return.py
3
How It Works
The maximum function returns the maximum of the parameters, in this case the numbers supplied to the
function. It uses a simple if..else statement to find the greater value and then returns that value.
Note that a return statement without a value is equivalent to return None. None is a special type
in Python that represents nothingness. For example, it is used to indicate that a variable has no value if it
has a value of None.
Every function implicitly contains a return None statement at the end unless you have written your
own return statement. You can see this by running print someFunction() where the function
someFunction does not use the return statement such as:
def someFunction():
pass
The pass statement is used in Python to indicate an empty block of statements.
DocStrings
Python has a nifty feature called documentation strings which is usually referred to by its shorter name
docstrings. DocStrings are an important tool that you should make use of since it helps to document the
Functions
38

program better and makes it more easy to understand. Amazingly, we can even get back the docstring
from, say a function, when the program is actually running!
Using DocStrings
Example 7.8. Using DocStrings
#!/usr/bin/python
# Filename: func_doc.py
def printMax(x, y):
'''Prints the maximum of two numbers.
The two values must be integers.'''
x = int(x) # convert to integers, if possible
y = int(y)
if x > y:
print x, 'is maximum'
else:
print y, 'is maximum'
printMax(3, 5)
print printMax.__doc__
Output
$ python func_doc.py
5 is maximum
Prints the maximum of two numbers.
The two values must be integers.
How It Works
A string on the first logical line of a function is the docstring for that function. Note that DocStrings also
apply to modules and classes which we will learn about in the respective chapters.
The convention followed for a docstring is a multi-line string where the first line starts with a capital let-
ter and ends with a dot. Then the second line is blank followed by any detailed explanation starting from
the third line. You are strongly advised to follow this convention for all your docstrings for all your non-
trivial functions.
We can access the docstring of the printMax function using the __doc__ (notice the double under-
scores) attribute (name belonging to) of the function. Just remember that Python treats everything as an
object and this includes functions. We'll learn more about objects in the chapter on classes.
If you have used the help() in Python, then you have already seen the usage of docstrings! What it
Functions
39

does is just fetch the __doc__ attribute of that function and displays it in a neat manner for you. You
can try it out on the function above - just include help(printMax) in your program. Remember to
press q to exit the help.
Automated tools can retrieve the documentation from your program in this manner. Therefore, I strongly
recommend that you use docstrings for any non-trivial function that you write. The pydoc command that
comes with your Python distribution works similarly to help() using docstrings.
Summary
We have seen so many aspects of functions but note that we still haven't covered all aspects of it.
However, we have already covered most of what you'll use regarding Python functions on an everyday
basis.
Next, we will see how to use as well as create Python modules.
Functions
40

Chapter 8. Modules
Introduction
You have seen how you can reuse code in your program by defining functions once. What if you wanted
to reuse a number of functions in other programs that you write? As you might have guessed, the answer
is modules. A module is basically a file containing all your functions and variables that you have
defined. To reuse the module in other programs, the filename of the module must have a .py extension.
A module can be imported by another program to make use of its functionality. This is how we can use
the Python standard library as well. First, we will see how to use the standard library modules.
Using the sys module
Example 8.1. Using the sys module
#!/usr/bin/python
# Filename: using_sys.py
import sys
print 'The command line arguments are:'
for i in sys.argv:
print i
print 'nnThe PYTHONPATH is', sys.path, 'n'
Output
$ python using_sys.py we are arguments
The command line arguments are:
using_sys.py
we
are
arguments
The PYTHONPATH is ['/home/swaroop/byte/code', '/usr/lib/python23.zip',
'/usr/lib/python2.3', '/usr/lib/python2.3/plat-linux2',
'/usr/lib/python2.3/lib-tk', '/usr/lib/python2.3/lib-dynload',
'/usr/lib/python2.3/site-packages', '/usr/lib/python2.3/site-packages/gtk-2.0']
How It Works
41

First, we import the sys module using the import statement. Basically, this translates to us telling Py-
thon that we want to use this module. The sys module contains functionality related to the Python inter-
preter and its environment.
When Python executes the import sys statement, it looks for the sys.py module in one of the dir-
ectores listed in its sys.path variable. If the file is found, then the statements in the main block of that
module is run and then the module is made available for you to use. Note that the initialization is done
only the first time that we import a module. Also, 'sys' is short for 'system'.
The argv variable in the sys module is referred to using the dotted notation - sys.argv - one of the
advantages of this approach is that the name does not clash with any argv variable used in your pro-
gram. Also, it indicates clearly that this name is part of the sys module.
The sys.argv variable is a list of strings (lists are explained in detail in later sections). Specifically,
the sys.argv contains the list of command line arguments i.e. the arguments passed to your program
using the command line.
If you are using an IDE to write and run these programs, look for a way to specify command line argu-
ments to the program in the menus.
Here, when we execute python using_sys.py we are arguments, we run the module us-
ing_sys.py with the python command and the other things that follow are arguments passed to the
program. Python stores it in the sys.argv variable for us.
Remember, the name of the script running is always the first argument in the sys.argv list. So, in this
case we will have 'using_sys.py' as sys.argv[0], 'we' as sys.argv[1], 'are' as
sys.argv[2] and 'arguments' as sys.argv[3] . Notice that Python starts counting from 0
and not 1.
The sys.path contains the list of directory names where modules are imported from. Observe that the
first string in sys.path is empty - this empty string indicates that the current directory is also part of
the sys.path which is same as the PYTHONPATH environment variable. This means that you can dir-
ectly import modules located in the current directory. Otherwise, you will have to place your module in
one of the directories listed in sys.path .
Byte-compiled .pyc files
Importing a module is a relatively costly affair, so Python does some tricks to make it faster. One way is
to create byte-compiled files with the extension .pyc which is related to the intermediate form that Py-
thon transforms the program into (remember the intro section on how Python works ?). This .pyc file
is useful when you import the module the next time from a different program - it will be much faster
since part of the processing required in importing a module is already done. Also, these byte-compiled
files are platform-independent. So, now you know what those .pyc files really are.
The from..import statement
If you want to directly import the argv variable into your program (to avoid typing the sys. everytime
for it), then you can use the from sys import argv statement. If you want to import all the names
used in the sys module, then you can use the from sys import * statement. This works for any
module. In general, avoid using the from..import statement and use the import statement instead
since your program will be much more readable and will avoid any name clashes that way.
A module's __name__
Every module has a name and statements in a module can find out the name of its module. This is espe-
Modules
42

cially handy in one particular situation - As mentioned previously, when a module is imported for the
first time, the main block in that module is run. What if we want to run the block only if the program
was used by itself and not when it was imported from another module? This can be achieved using the
__name__ attribute of the module.
Using a module's __name__
Example 8.2. Using a module's __name__
#!/usr/bin/python
# Filename: using_name.py
if __name__ == '__main__':
print 'This program is being run by itself'
else:
print 'I am being imported from another module'
Output
$ python using_name.py
This program is being run by itself
$ python
>>> import using_name
I am being imported from another module
>>>
How It Works
Every Python module has it's __name__ defined and if this is '__main__', it implies that the mod-
ule is being run standalone by the user and we can do corresponding appropriate actions.
Making your own Modules
Creating your own modules is easy, you've been doing it all along! Every Python program is also a mod-
ule. You just have to make sure it has a .py extension. The following example should make it clear.
Creating your own Modules
Example 8.3. How to create your own module
Modules
43

#!/usr/bin/python
# Filename: mymodule.py
def sayhi():
print 'Hi, this is mymodule speaking.'
version = '0.1'
# End of mymodule.py
The above was a sample module. As you can see, there is nothing particularly special about compared to
our usual Python program. We will next see how to use this module in our other Python programs.
Remember that the module should be placed in the same directory as the program that we import it in, or
the module should be in one of the directories listed in sys.path .
#!/usr/bin/python
# Filename: mymodule_demo.py
import mymodule
mymodule.sayhi()
print 'Version', mymodule.version
Output
$ python mymodule_demo.py
Hi, this is mymodule speaking.
Version 0.1
How It Works
Notice that we use the same dotted notation to access members of the module. Python makes good reuse
of the same notation to give the distinctive 'Pythonic' feel to it so that we don't have to keep learning
new ways to do things.
from..import
Here is a version utilising the from..import syntax.
#!/usr/bin/python
# Filename: mymodule_demo2.py
from mymodule import sayhi, version
# Alternative:
Modules
44

# from mymodule import *
sayhi()
print 'Version', version
The output of mymodule_demo2.py is same as the output of mymodule_demo.py.
The dir() function
You can use the built-in dir function to list the identifiers that a module defines. The identifiers are the
functions, classes and variables defined in that module.
When you supply a module name to the dir() function, it returns the list of the names defined in that
module. When no argument is applied to it, it returns the list of names defined in the current module.
Using the dir function
Example 8.4. Using the dir function
$ python
>>> import sys
>>> dir(sys) # get list of attributes for sys module
['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__',
'__stdin__', '__stdout__', '_getframe', 'api_version', 'argv',
'builtin_module_names', 'byteorder', 'call_tracing', 'callstats',
'copyright', 'displayhook', 'exc_clear', 'exc_info', 'exc_type',
'excepthook', 'exec_prefix', 'executable', 'exit', 'getcheckinterval',
'getdefaultencoding', 'getdlopenflags', 'getfilesystemencoding',
'getrecursionlimit', 'getrefcount', 'hexversion', 'maxint', 'maxunicode',
'meta_path','modules', 'path', 'path_hooks', 'path_importer_cache',
'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setdlopenflags',
'setprofile', 'setrecursionlimit', 'settrace', 'stderr', 'stdin', 'stdout',
'version', 'version_info', 'warnoptions']
>>> dir() # get list of attributes for current module
['__builtins__', '__doc__', '__name__', 'sys']
>>>
>>> a = 5 # create a new variable 'a'
>>> dir()
['__builtins__', '__doc__', '__name__', 'a', 'sys']
>>>
>>> del a # delete/remove a name
>>>
>>> dir()
['__builtins__', '__doc__', '__name__', 'sys']
>>>
How It Works
First, we see the usage of dir on the imported sys module. We can see the huge list of attributes that it
Modules
45

contains.
Next, we use the dir function without passing parameters to it - by default, it returns the list of attrib-
utes for the current module. Notice that the list of imported modules is also part of this list.
In order to observe the dir in action, we define a new variable a and assign it a value and then check
dir and we observe that there is an additional value in the list of the same name. We remove the vari-
able/attribute of the current module using the del statement and the change is reflected again in the out-
put of the dir function.
A note on del - this statement is used to delete a variable/name and after the statement has run, in this
case del a, you can no longer access the variable a - it is as if it never existed before at all.
Summary
Modules are useful because they provide services and functionality that you can reuse in other programs.
The standard library that comes with Python is an example of such a set of modules. We have seen how
to use these modules and create our own modules as well.
Next, we will learn about some interesting concepts called data structures.
Modules
46

Chapter 9. Data Structures
Introduction
Data structures are basically just that - they are structures which can hold some data together. In other
words, they are used to store a collection of related data.
There are three built-in data structures in Python - list, tuple and dictionary. We will see how to use each
of them and how they make life easier.
List
A list is a data structure that holds an ordered collection of items i.e. you can store a sequence of
items in a list. This is easy to imagine if you can think of a shopping list where you have a list of items
to buy, except that you probbly have each item on a separate line in your shopping list whereas in Py-
thon you put commas in between them.
The list of items should be enclosed in square brackets so that Python understands that you are specify-
ing a list. Once you have created a list, you can add, remove or search for items in the list. Since, we can
add and remove items, we say that a list is a mutable data type i.e. this type can be altered.
Quick introduction to Objects and Classes
Although, I've been generally delaying the discussion of objects and classes till now, a little explanation
is needed right now so that you can understand lists better. We will still explore this topic in detail in its
own chapter.
A list is an example of usage of objects and classes. When you use a variable i and assign a value to it,
say integer 5 to it, you can think of it as creating an object (instance) i of class (type) int. In fact, you
can see help(int) to understand this better.
A class can also have methods i.e. functions defined for use with respect to that class only. You can use
these pieces of functionality only when you have an object of that class. For example, Python provides
an append method for the list class which allows you to add an item to the end of the list. For ex-
ample, mylist.append('an item') will add that string to the list mylist. Note the use of dot-
ted notation for accessing methods of the objects.
A class can also have fields which are nothing but variables defined for use with respect to that class
only. You can use these variables/names only when you have an object of that class. Fields are also ac-
cessed by the dotted notation, for example, mylist.field .
Using Lists
Example 9.1. Using lists
#!/usr/bin/python
# Filename: using_list.py
# This is my shopping list
shoplist = ['apple', 'mango', 'carrot', 'banana']
47

print 'I have', len(shoplist), 'items to purchase.'
print 'These items are:', # Notice the comma at end of the line
for item in shoplist:
print item,
print 'nI also have to buy rice.'
shoplist.append('rice')
print 'My shopping list is now', shoplist
print 'I will sort my list now'
shoplist.sort()
print 'Sorted shopping list is', shoplist
print 'The first item I will buy is', shoplist[0]
olditem = shoplist[0]
del shoplist[0]
print 'I bought the', olditem
print 'My shopping list is now', shoplist
Output
$ python using_list.py
I have 4 items to purchase.
These items are: apple mango carrot banana
I also have to buy rice.
My shopping list is now ['apple', 'mango', 'carrot', 'banana', 'rice']
I will sort my list now
Sorted shopping list is ['apple', 'banana', 'carrot', 'mango', 'rice']
The first item I will buy is apple
I bought the apple
My shopping list is now ['banana', 'carrot', 'mango', 'rice']
How It Works
The variable shoplist is a shopping list for someone who is going to the market. In shoplist, we
only store strings of the names of the items to buy but remember you can add any kind of object to a list
including numbers and even other lists.
We have also used the for..in loop to iterate through the items of the list. By now, you must have
realised that a list is also a sequence. The speciality of sequences will be discussed in a later section
Notice that we use a comma at the end of the print statement to suppress the automatic printing of a
line break after every print statement. This is a bit of an ugly way of doing it, but it is simple and gets
the job done.
Next, we add an item to the list using the append method of the list object, as already discussed before.
Then, we check that the item has been indeed added to the list by printing the contents of the list by
simply passing the list to the print statement which prints it in a neat manner for us.
Then, we sort the list by using the sort method of the list. Understand that this method affects the list
Data Structures
48

itself and does not return a modified list - this is different from the way strings work. This is what we
mean by saying that lists are mutable and that strings are immutable.
Next, when we finish buying an item in the market, we want to remove it from the list. We achieve this
by using the del statement. Here, we mention which item of the list we want to remove and the del
statement removes it fromt he list for us. We specify that we want to remove the first item from the list
and hence we use del shoplist[0] (remember that Python starts counting from 0).
If you want to know all the methods defined by the list object, see help(list) for complete details.
Tuple
Tuples are just like lists except that they are immutable like strings i.e. you cannot modify tuples.
Tuples are defined by specifying items separated by commas within a pair of parentheses. Tuples are
usually used in cases where a statement or a user-defined function can safely assume that the collection
of values i.e. the tuple of values used will not change.
Using Tuples
Example 9.2. Using Tuples
#!/usr/bin/python
# Filename: using_tuple.py
zoo = ('wolf', 'elephant', 'penguin')
print 'Number of animals in the zoo is', len(zoo)
new_zoo = ('monkey', 'dolphin', zoo)
print 'Number of animals in the new zoo is', len(new_zoo)
print 'All animals in new zoo are', new_zoo
print 'Animals brought from old zoo are', new_zoo[2]
print 'Last animal brought from old zoo is', new_zoo[2][2]
Output
$ python using_tuple.py
Number of animals in the zoo is 3
Number of animals in the new zoo is 3
All animals in new zoo are ('monkey', 'dolphin', ('wolf', 'elephant', 'penguin'))
Animals brought from old zoo are ('wolf', 'elephant', 'penguin')
Last animal brought from old zoo is penguin
How It Works
The variable zoo refers to a tuple of items. We see that the len function can be used to get the length
of the tuple. This also indicates that a tuple is a sequence as well.
Data Structures
49

We are now shifting these animals to a new zoo since the old zoo is being closed. Therefore, the
new_zoo tuple contains some animals which are already there along with the animals brought over
from the old zoo. Back to reality, note that a tuple within a tuple does not lose its identity.
We can access the items in the tuple by specifying the item's position within a pair of square brackets
just like we did for lists. This is called the indexing operator. We access the third item in new_zoo by
specifying new_zoo[2] and we access the third item in the third item in the new_zoo tuple by spe-
cifying new_zoo[2][2]. This is pretty simple once you've understood the idiom.
Tuple with 0 or 1 items. An empty tuple is constructed by an empty pair of parentheses such as my-
empty = (). However, a tuple with a single item is not so simple. You have to specify it using a
comma following the first (and only) item so that Python can differentiate between a tuple and a pair of
parentheses surrounding the object in an expression i.e. you have to specify singleton = (2 , )
if you mean you want a tuple containing the item 2.
Note for Perl programmers
A list within a list does not lose its identity i.e. lists are not flattened as in Perl. The same ap-
plies to a tuple within a tuple, or a tuple within a list, or a list within a tuple, etc. As far as Py-
thon is concerned, they are just objects stored using another object, that's all.
Tuples and the print statement
One of the most common usage of tuples is with the print statement. Here is an example:
Example 9.3. Output using tuples
#!/usr/bin/python
# Filename: print_tuple.py
age = 22
name = 'Swaroop'
print '%s is %d years old' % (name, age)
print 'Why is %s playing with that python?' % name
Output
$ python print_tuple.py
Swaroop is 22 years old
Why is Swaroop playing with that python?
How It Works
The print statement can take a string using certain specifications followed by the % symbol followed
by a tuple of items matching the specification. The specifications are used to format the output in a cer-
Data Structures
50

tain way. The specification can be like %s for strings and %d for integers. The tuple must have items
corresponding to these specifications in the same order.
Observe the first usage where we use %s first and this corresponds to the variable name which is the
first item in the tuple and the second specification is %d corresponding to age which is the second item
in the tuple.
What Python does here is that it converts each item in the tuple into a string and substitutes that string
value into the place of the specification. Therefore the %s is replaced by the value of the variable name
and so on.
This usage of the print statement makes writing output extremely easy and avoids lot of string manip-
ulation to achieve the same. It also avoids using commas everywhere as we have done till now.
Most of the time, you can just use the %s specification and let Python take care of the rest for you. This
works even for numbers. However, you may want to give the correct specifications since this adds one
level of checking that your program is correct.
In the second print statement, we are using a single specification followed by the % symbol followed
by a single item - there are no pair of parentheses. This works only in the case where there is a single
specification in the string.
Dictionary
A dictionary is like an address-book where you can find the address or contact details of a person by
knowing only his/her name i.e. we associate keys (name) with values (details). Note that the key must
be unique just like you cannot find out the correct information if you have two persons with the exact
same name.
Note that you can use only immutable objects (like strings) for the keys of a dictionary but you can use
either immutable or mutable objects for the values of the dictionary. This basically translates to say that
you should use only simple objects for keys.
Pairs of keys and valus are specified in a dictionary by using the notation d = {key1 : value1,
key2 : value2 }. Notice that they key/value pairs are separated by a colon and the pairs are separ-
ated themselves by commas and all this is enclosed in a pair of curly brackets.
Remember that key/value pairs in a dictionary are not ordered in any manner. If you want a particular
order, then you will have to sort them yourself before using it.
The dictionaries that you will be using are instances/objects of the dict class.
Using Dictionaries
Example 9.4. Using dictionaries
#!/usr/bin/python
# Filename: using_dict.py
# 'ab' is short for 'a'ddress'b'ook
ab = { 'Swaroop' : 'swaroopch@byteofpython.info',
'Larry' : 'larry@wall.org',
'Matsumoto' : 'matz@ruby-lang.org',
'Spammer' : 'spammer@hotmail.com'
Data Structures
51

}
print "Swaroop's address is %s" % ab['Swaroop']
# Adding a key/value pair
ab['Guido'] = 'guido@python.org'
# Deleting a key/value pair
del ab['Spammer']
print 'nThere are %d contacts in the address-bookn' % len(ab)
for name, address in ab.items():
print 'Contact %s at %s' % (name, address)
if 'Guido' in ab: # OR ab.has_key('Guido')
print "nGuido's address is %s" % ab['Guido']
Output
$ python using_dict.py
Swaroop's address is swaroopch@byteofpython.info
There are 4 contacts in the address-book
Contact Swaroop at swaroopch@byteofpython.info
Contact Matsumoto at matz@ruby-lang.org
Contact Larry at larry@wall.org
Contact Guido at guido@python.org
Guido's address is guido@python.org
How It Works
We create the dictionary ab using the notation already discussed. We then access key/value pairs by
specifying the key using the indexing operator as discussed in the context of lists and tuples. Observe
that the syntax is very simple for dictionaries as well.
We can add new key/value pairs by simply using the indexing operator to access a key and assign that
value, as we have done for Guido in the above case.
We can delete key/value pairs using our old friend - the del statement. We simply specify the diction-
ary and the indexing operator for the key to be removed and pass it to the del statement. There is no
need to know the value corresponding to the key for this operation.
Next, we access each key/value pair of the dictionary using the items method of the dictionary which
returns a list of tuples where each tuple contains a pair of items - the key followed by the value. We re-
trieve this pair and assign it to the variables name and address correspondingly for each pair using
the for..in loop and then print these values in the for-block.
We can check if a key/value pair exists using the in operator or even the has_key method of the
dict class. You can see the documentation for the complete list of methods of the dict class using
Data Structures
52

help(dict).
Keyword Arguments and Dictionaries. On a different note, if you have used keyword arguments in
your functions, you have already used dictionaries! Just think about it - the key/value pair is specified by
you in the parameter list of the function definition and when you access variables within your function,
it is just a key access of a dictionary (which is called the symbol table in compiler design terminology).
Sequences
Lists, tuples and strings are examples of sequences, but what are sequences and what is so special about
them? Two of the main features of a sequence is the indexing operation which allows us to fetch a par-
ticular item in the sequence directly and the slicing operation which allows us to retrieve a slice of the
sequence i.e. a part of the sequence.
Using Sequences
Example 9.5. Using Sequences
#!/usr/bin/python
# Filename: seq.py
# Indexing or 'Subscription' operation
print 'Item 0 is', shoplist[0]
print 'Item -1 is', shoplist[-1]
print 'Item -2 is', shoplist[-2]
# Slicing on a list
print 'Item 1 to 3 is', shoplist[1:3]
print 'Item 2 to end is', shoplist[2:]
print 'Item 1 to -1 is', shoplist[1:-1]
print 'Item start to end is', shoplist[:]
# Slicing on a string
name = 'swaroop'
print 'characters 1 to 3 is', name[1:3]
print 'characters 2 to end is', name[2:]
print 'characters 1 to -1 is', name[1:-1]
print 'characters start to end is', name[:]
Output
$ python seq.py
Item 0 is apple
Item 1 is mango
Item 2 is carrot
Item 3 is banana
Data Structures
53

Item -1 is banana
Item -2 is carrot
Item 1 to 3 is ['mango', 'carrot']
Item 2 to end is ['carrot', 'banana']
Item 1 to -1 is ['mango', 'carrot']
Item start to end is ['apple', 'mango', 'carrot', 'banana']
characters 1 to 3 is wa
characters 2 to end is aroop
characters 1 to -1 is waroo
characters start to end is swaroop
How It Works
First, we see how to use indexes to get individual items of a sequence. This is also referred to as the sub-
scription operation. Whenever you specify a number to a sequence within square brackets as shown
above, Python will fetch you the item corresponding to that position in the sequence. Remember that Py-
thon starts counting numbers from 0. Hence, shoplist[0] fetches the first item and shoplist[3]
fetches the fourth item in the shoplist sequence.
The index can also be a negative number, in which case, the position is calculated from the end of the
sequence. Therefore, shoplist[-1] refers to the last item in the sequence and shoplist[-2]
fetches the second last item in the sequence.
The slicing operation is used by specifying the name of the sequence followed by an optional pair of
numbers separated by a colon within square brackets. Note that this is very very similar to the indexing
operation you have been using til lnow. Remember the numbers are optional but the colon isn't.
The first number (before the colon) in the slicing operation refers to the position from where the slice
starts and the second number (after the colon) indicates where the slice will stop at. If the first number is
not specified, Python will start at the beginning of the sequence. If the second number is left out, Python
will stop at the end of the sequence. Note that the slice returned starts at the start position and will end
just before the end position i.e. the start position is included but the end position is excluded from the se-
quence slice.
Thus, shoplist[1:3] returns a slice of the sequence starting at position 1, includes position 2 but
stops at position 3 and therefore a slice of two items is returned. Similarly, shoplist[:] returns a
copy of the whole sequence.
You can also do slicing with negative positions. Negative numbers are used for positions from the end of
the sequence. For example, shoplist[:-1] will return a slice of the sequence which excludes the
last item of the sequence but contains everything else.
Try various combinations of such slice specifications using the Python interpreter interactively i.e. the
prompt so that you can see the results immediately. The great thing about sequences is that you can ac-
cess tuples, lists and strings all in the same way!
References
When you create an object and assign it to a variable, the variable only refers to the object and does not
represent the object itself! That is, the variable name points to that part of your computer's memory
where the object is stored. This is called as binding of the name to the object.
Generally, you don't need to be worried about this, but there is a subtle effect due to references which
you need to be aware of. This is demonstrated by the following example.
Data Structures
54

Objects and References
Example 9.6. Objects and References
#!/usr/bin/python
# Filename: reference.py
print 'Simple Assignment'
mylist = shoplist # mylist is just another name pointing to the same object!
del shoplist[0] # I purchased the first item, so I remove it from the list
print 'shoplist is', shoplist
print 'mylist is', mylist
# notice that both shoplist and mylist both print the same list without
# the 'apple' confirming that they point to the same object
print 'Copy by making a full slice'
mylist = shoplist[:] # make a copy by doing a full slice
del mylist[0] # remove first item
print 'shoplist is', shoplist
print 'mylist is', mylist
# notice that now the two lists are different
Output
$ python reference.py
Simple Assignment
shoplist is ['mango', 'carrot', 'banana']
mylist is ['mango', 'carrot', 'banana']
Copy by making a full slice
shoplist is ['mango', 'carrot', 'banana']
mylist is ['carrot', 'banana']
How It Works
Most of the explanation is available in the comments itself. What you need to remember is that if you
want to make a copy of a list or such kinds of sequences or complex objects (not simple objects such as
integers), then you have to use the slicing operation to make a copy. If you just assign the variable name
to another name, both of them will refer to the same object and this could lead to all sorts of trouble if
you are not careful.
Note for Perl programmers
Remember that an assignment statement for lists does not create a copy. You have to use sli-
cing operation to make a copy of the sequence.
Data Structures
55

More about Strings
We have already discussed strings in detail earlier. What more can there be to know? Well, did you
know that strings are also objects and have methods which do everything from checking part of a string
to stripping spaces!
The strings that you use in program are all objects of the class str. Some useful methods of this class
are demonstrated in the next example. For a complete list of such methods, see help(str).
String Methods
Example 9.7. String Methods
#!/usr/bin/python
# Filename: str_methods.py
name = 'Swaroop' # This is a string object
if name.startswith('Swa'):
print 'Yes, the string starts with "Swa"'
if 'a' in name:
print 'Yes, it contains the string "a"'
if name.find('war') != -1:
print 'Yes, it contains the string "war"'
delimiter = '_*_'
mylist = ['Brazil', 'Russia', 'India', 'China']
print delimiter.join(mylist)
Output
$ python str_methods.py
Yes, the string starts with "Swa"
Yes, it contains the string "a"
Yes, it contains the string "war"
Brazil_*_Russia_*_India_*_China
How It Works
Here, we see a lot of the string methods in action. The startswith method is used to find out wheth-
er the string starts with the given string. The in operator is used to check if a given string is a part of the
string.
The find method is used to do find the position of the given string in the string or returns -1 if it is not
successful to find the substring. The str class also has a neat method to join the items of a sequence
Data Structures
56

with the string acting as a delimiter between each item of the sequence and returns a bigger string gener-
ated from this.
Summary
We have explored the various built-in data structures of Python in detail. These data structures will be
essential for writing programs of reasonable size.
Now that we have a lot of the basics of Python in place, we will next see how to design and write a real-
world Python program.
Data Structures
57

Chapter 10. Problem Solving - Writing a
Python Script
We have explored various parts of the Python language and now we will take a look at how all these
parts fit together, by designing and writing a program which does something useful.
The Problem
The problem is 'I want a program which creates a backup of all my important files'.
Although, this is a simple problem, there is not enough information for us to get started with the solu-
tion. A little more analysis is required. For example, how do we specify which files are to be backed up?
Where is the backup stored? How are they stored in the backup?
After analyzing the problem properly, we design our program. We make a list of things about how our
program should work. In this case, I have created the following list on how I want it to work. If you do
the design, you may not come up with the same kind of problem - every person has their own way of do-
ing things, this is ok.
1. The files and directories to be backed up are specified in a list.
2. The backup must be stored in a main backup directory.
3. The files are backed up into a zip file.
4. The name of the zip archive is the current date and time.
5. We use the standard zip command available by default in any standard Linux/Unix distribution.
Windows users can use the Info-Zip program. Note that you can use any archiving command you
want as long as it has a command line interface so that we can pass arguments to it from our script.
The Solution
As the design of our program is now stable, we can write the code which is an implementation of our
solution.
First Version
Example 10.1. Backup Script - The First Version
#!/usr/bin/python
# Filename: backup_ver1.py
import os
import time
# 1. The files and directories to be backed up are specified in a list.
source = ['/home/swaroop/byte', '/home/swaroop/bin']
58

# If you are using Windows, use source = [r'C:Documents', r'D:Work'] or something
# 2. The backup must be stored in a main backup directory
target_dir = '/mnt/e/backup/' # Remember to change this to what you will be using
# 3. The files are backed up into a zip file.
# 4. The name of the zip archive is the current date and time
target = target_dir + time.strftime('%Y%m%d%H%M%S') + '.zip'
# 5. We use the zip command (in Unix/Linux) to put the files in a zip archive
zip_command = "zip -qr '%s' %s" % (target, ' '.join(source))
# Run the backup
if os.system(zip_command) == 0:
print 'Successful backup to', target
else:
print 'Backup FAILED'
Output
$ python backup_ver1.py
Successful backup to /mnt/e/backup/20041208073244.zip
Now, we are in the testing phase where we test that our program works properly. If it doesn't behave as
expected, then we have to debug our program i.e. remove the bugs (errors) from the program.
How It Works
You will notice how we have converted our design into code in a step-by-step manner.
We make use of the os and time modules and so we import them. Then, we specify the files and dir-
ectories to be backed up in the source list. The target directory is where store all the backup files and
this is specified in the target_dir variable. The name of the zip archive that we are going to create is
the current date and time which we fetch using the time.strftime() function. It will also have the
.zip extension and will be stored in the target_dir directory.
The time.strftime() function takes a specification such as the one we have used in the above pro-
gram. The %Y specification will be replaced by the year without the cetury. The %m specification will be
replaced by the month as a decimal number between 01 and 12 and so on. The complete list of such
specifications can be found in the [Python Reference Manual] that comes with your Python distribution.
Notice that this is similar to (but not same as) the specification used in print statement (using the %
followed by tuple).
We create the name of the target zip file using the addition operator which concatenates the strings i.e. it
joins the two strings together and returns a new one. Then, we create a string zip_command which
contains the command that we are going to execute. You can check if this command works by running it
on the shell (Linux terminal or DOS prompt).
The zip command that we are using has some options and parameters passed. The -q option is used to
indicate that the zip command should work quietly. The -r option specifies that the zip command
should work recursively for directories i.e. it should include subdirectories and files within the subdir-
Problem Solving - Writing a Python Script
59

ectories as well. The two options are combined and specified in a shorter way as -qr. The options are
followed by the name of the zip archive to create followed by the list of files and directories to backup.
We convert the source list into a string using the join method of strings which we have already seen
how to use.
Then, we finally run the command using the os.system function which runs the command as if it was
run from the system i.e. in the shell - it returns 0 if the command was successfully, else it returns an er-
ror number.
Depending on the outcome of the command, we print the appropriate message that the backup has failed
or succeeded and that's it, we have created a script to take a backup of our important files!
Note to Windows Users
You can set the source list and target directory to any file and directory names but you
have to be a little careful in Windows. The problem is that Windows uses the backslash () as
the directory separator character but Python uses backslashes to represent escape sequences!
So, you have to represent a backslash itself using an escape sequence or you have to use raw
strings. For example, use 'C:Documents' or r'C:Documents' but do not use
'C:Documents' - you are using an unknown escape sequence D !
Now that we have a working backup script, we can use it whenever we want to take a backup of the
files. Linux/Unix users are advised to use the executable method as discussed earlier so that they can run
the backup script anytime anywhere. This is called the operation phase or the deployment phase of the
software.
The above program works properly, but (usually) first programs do not work exactly as you expect. For
example, there might be problems if you have not designed the program properly or if you have made a
mistake in typing the code, etc. Appropriately, you will have to go back to the design phase or you will
have to debug your program.
Second Version
The first version of our script works. However, we can make some refinements to it so that it can work
better on a daily basis. This is called the maintenance phase of the software.
One of the refinements I felt was useful is a better file-naming mechanism - using the time as the name
of the file within a directory with the current date as a directory within the main backup directory. One
advantage is that your backups are stored in a hierarchical manner and therefore it is much easier to
manage. Another advantage is that the length of the filenames are much shorter this way. Yet another
advantage is that separate directories will help you to easily check if you have taken a backup for each
day since the directory would be created only if you have taken a backup for that day.
Example 10.2. Backup Script - The Second Version
#!/usr/bin/python
import os
import time
60

# 4. The current day is the name of the subdirectory in the main directory
today = target_dir + time.strftime('%Y%m%d')
# The current time is the name of the zip archive
now = time.strftime('%H%M%S')
# Create the subdirectory if it isn't already there
if not os.path.exists(today):
os.mkdir(today) # make directory
print 'Successfully created directory', today
# The name of the zip file
target = today + os.sep + now + '.zip'
# Run the backup
else:
Output
Successfully created directory /mnt/e/backup/20041208
Successful backup to /mnt/e/backup/20041208/080020.zip
How It Works
Most of the program remains the same. The changes is that we check if there is a directory with the cur-
rent day as name inside the main backup directory using the os.exists function. If it doesn't exist,
we create it using the os.mkdir function.
Notice the use of os.sep variable - this gives the directory separator according to your operating sys-
tem i.e. it will be '/' in Linux, Unix, it will be '' in Windows and ':' in Mac OS. Using os.sep
instead of these characters directly will make our program portable and work across these systems.
Third Version
The second version works fine when I do many backups, but when there are lots of backups, I am find-
ing it hard to differentiate what the backups were for! For example, I might have made some major
changes to a program or presentation, then I want to associate what those changes are with the name of
61

the zip archive. This can be easily achieved by attaching a user-supplied comment to the name of the zip
archive.
Example 10.3. Backup Script - The Third Version (does not work!)
#!/usr/bin/python
import os
import time
# Take a comment from the user to create the name of the zip file
comment = raw_input('Enter a comment --> ')
if len(comment) == 0: # check if a comment was entered
else:
target = today + os.sep + now + '_' +
comment.replace(' ', '_') + '.zip'
# Run the backup
else:
Output
File "backup_ver3.py", line 25
^
62

How This (does not) Work
This program does not work!. Python says there is a syntax error which means that the script does not
satisfy the structure that Python expects to see. When we observe the error given by Python, it also tells
us the place where it detected the error as well. So we start debugging our program from that line.
On careful observation, we see that the single logical line has been split into two physical lines but we
have not specified that these two physical lines belong together. Basically, Python has found the addi-
tion operator (+) without any operand in that logical line and hence it doesn't know how to continue. Re-
member that we can specify that the logical line continues in the next physical line by the use of a back-
slash at the end of the physical line. So, we make this correction to our program. This is called bug fix-
ing.
Fourth Version
Example 10.4. Backup Script - The Fourth Version
#!/usr/bin/python
import os, time
# Take a comment from the user to create the name of the zip file
comment = raw_input('Enter a comment --> ')
if len(comment) == 0: # check if a comment was entered
else:
comment.replace(' ', '_') + '.zip'
# Notice the backslash!
# Run the backup
63

else:
Output
Enter a comment --> added new examples
Successful backup to /mnt/e/backup/20041208/082156_added_new_examples.zip
Enter a comment -->
How It Works
This program now works! Let us go through the actual enhancements that we had made in version 3. We
take in the user's comments using the raw_input function and then check if the user actually entered
something by finding out the length of the input using the len function. If the user has just pressed
enter for some reason (maybe it was just a routine backup or no special changes were made), then we
proceed as we have done before.
However, if a comment was supplied, then this is attached to the name of the zip archive just before the
.zip extension. Notice that we are replacing spaces in the comment with underscores - this is because
managing such filenames are much easier.
More Refinements
The fourth version is a satisfactorily working script for most users, but there is always room for im-
provement. For example, you can include a verbosity level for the program where you can specify a -v
option to make your program become more talkative.
Another possible enhancement would be to allow extra files and directories to be passed to the script at
the command line. We will get these from the sys.argv list and we can add them to our source list
using the extend method provided by the list class.
One refinement I prefer is the use of the tar command instead of the zip command. One advantage is
that when you use the tar command along with gzip, the backup is much faster and the backup created
is also much smaller. If I need to use this archive in Windows, then WinZip handles such .tar.gz
files easily as well. The tar command is available by default on most Linux/Unix systems. Windows
users can download [http://gnuwin32.sourceforge.net/packages/tar.htm] and install it as well.
The command string will now be:
tar = 'tar -cvzf %s %s -X /home/swaroop/excludes.txt' % (target, ' '.join(srcdir))
64

The options are explained below.
• -c indicates creation of an archive.
• -v indicates verbose i.e. the command should be more talkative.
• -z indicates the gzip filter should be used.
• -f indicates force in creation of archive i.e. it should replace if there is a file by the same name
already.
• -X indicates a file which contains a list of filenames which must be excluded from the backup. For
example, you can specify *~ in this file to not include any filenames ending with ~ in the backup.
Important
The most preferred way of creating such kind of archives would be using the zipfile or
tarfile module respectively. They are part of the Python Standard Library and available for
you to use already. Using these libraries also avoids the use of the os.system which is gen-
erally not advisable to use because it is very easy to make costly mistakes using it.
However, I have been using the os.system way of creating a backup purely for pedagogical
purposes, so that the example is simple enough to be understood by everybody but real enough
to be useful.
The Software Development Process
We have now gone through the various phases in the process of writing a software. These phases can be
summarised as follows:
1. What (Analysis)
2. How (Design)
3. Do It (Implementation)
4. Test (Testing and Debugging)
5. Use (Operation or Deployment)
6. Maintain (Refinement)
Important
A recommended way of writing programs is the procedure we have followed in creating the
backup script - Do the analysis and design. Start implementing with a simple version. Test and
debug it. Use it to ensure that it works as expected. Now, add any features that you want and
continue to repeat the Do It-Test-Use cycle as many times as required. Remember, 'Software is
grown, not built'.
Summary
65

We have seen how to create our own Python programs/scripts and the various stages involved in writing
such programs. You may find it useful to create your own program just like we did in this chapter so that
you become comfortable with Python as well as problem-solving.
Next, we will discuss object-oriented programming.
66

Chapter 11. Object-Oriented
Programming
Introduction
In all our programs till now, we have designed our program around functions or blocks of statements
which manipulate data. This is called the procedure-oriented way of programming. There is another way
of organizing your program which is to combine data and functionality and wrap it inside what is called
an object. This is called the object oriented programming paradigm. Most of the time you can use pro-
cedural programming but sometimes when you want to write large programs or have a solution that is
better suited to it, you can use object oriented programming techniques.
Classes and objects are the two main aspecs of object oriented programming. A class creates a new type
where objects are instances of the class. An analogy is that you can have variables of type int which
translates to saying that variables that store integers are variables which are instances (objects) of the
int class.
Note for C/C++/Java/C# Programmers
Note that even integers are treated as objects (of the int class). This is unlike C++ and Java
(before version 1.5) where integers are primitive native types. See help(int) for more de-
tails on the class.
C# and Java 1.5 programmers will be familiar with this concept since it is similar to the boxing
and unboxing concept.
Objects can store data using ordinary variables that belong to the object. Variables that belong to an ob-
ject or class are called as fields. Objects can also have functionality by using functions that belong to a
class. Such functions are called methods of the class. This terminology is important because it helps us
to differentiate between functions and variables which are separate by itself and those which belong to a
class or object. Collectively, the fields and methods can be referred to as the attributes of that class.
Fields are of two types - they can belong to each instance/object of the class or they can belong to the
class itself. They are called instance variables and class variables respectively.
A class is created using the class keyword. The fields and methods of the class are listed in an inden-
ted block.
The self
Class methods have only one specific difference from ordinary functions - they must have an extra first
name that has to be added to the beginning of the parameter list, but you do do not give a value for this
parameter when you call the method, Python will provide it. This particular variable refers to the object
itself, and by convention, it is given the name self.
Although, you can give any name for this parameter, it is strongly recommended that you use the name
self - any other name is definitely frowned upon. There are many advantages to using a standard name
- any reader of your program will immediately recognize it and even specialized IDEs (Integrated De-
velopment Environments) can help you if you use self.
Note for C++/Java/C# Programmers
The self in Python is equivalent to the self pointer in C++ and the this reference in Java
67

and C#.
You must be wondering how Python gives the value for self and why you don't need to give a value
for it. An example will make this clear. Say you have a class called MyClass and an instance of this
class called MyObject. When you call a method of this object as MyObject.method(arg1,
arg2), this is automatically converted by Python into MyClass.method(MyObject, arg1,
arg2 - this is what the special self is all about.
This also means that if you have a method which takes no arguments, then you still have to define the
method to have a self argument.
Classes
The simplest class possible is shown in the following example.
Creating a Class
Example 11.1. Creating a Class
#!/usr/bin/python
# Filename: simplestclass.py
class Person:
pass # An empty block
p = Person()
print p
Output
$ python simplestclass.py
<__main__.Person instance at 0xf6fcb18c>
How It Works
We create a new class using the class statement followed by the name of the class. This follows an in-
dented block of statements which form the body of the class. In this case, we have an empty block which
is indicated using the pass statement.
Next, we create an object/instance of this class using the name of the class followed by a pair of paren-
theses. (We will learn more about instantiation in the next section). For our verification, we confirm the
type of the variable by simply printing it. It tells us that we have an instance of the Person class in the
__main__ module.
Notice that the address of the computer memory where your object is stored is also printed. The address
will have a different value on your computer since Python can store the object wherever it finds space.
Object-Oriented Programming
68

object Methods
We have already discussed that classes/objects can have methods just like functions except that we have
an extra self variable. We will now see an example.
Using Object Methds
Example 11.2. Using Object Methods
#!/usr/bin/python
# Filename: method.py
class Person:
def sayHi(self):
print 'Hello, how are you?'
p = Person()
p.sayHi()
# This short example can also be written as Person().sayHi()
Output
$ python method.py
Hello, how are you?
How It Works
Here we see the self in action. Notice that the sayHi method takes no parameters but still has the
self in the function definition.
The __init__ method
There are many method names which have special significance in Python classes. We will see the signi-
ficance of the __init__ method now.
The __init__ method is run as soon as an object of a class is instantiated. The method is useful to do
any initialization you want to do with your object. Notice the double underscore both in the beginning
and at the end in the name.
Using the __init__ method
Example 11.3. Using the __init__ method
69

#!/usr/bin/python
# Filename: class_init.py
class Person:
def __init__(self, name):
self.name = name
def sayHi(self):
print 'Hello, my name is', self.name
p = Person('Swaroop')
p.sayHi()
# This short example can also be written as Person('Swaroop').sayHi()
Output
$ python class_init.py
Hello, my name is Swaroop
How It Works
Here, we define the __init__ method as taking a parameter name (along with the usual self). Here,
we just create a new field also called name. Notice these are two different variables even though they
have the same name. The dotted notation allows us to differentiate between them.
Most importantly, notice that we do not explicitly call the __init__ method but pass the arguments in
the parentheses following the class name when creating a new instance of the class. This is the special
significance of this method.
Now, we are able to use the self.name field in our methods which is demonstrated in the sayHi
method.
The __init__ method is analogous to a constructor in C++, C# or Java.
Class and Object Variables
We have already discussed the functionality part of classes and objects, now we'll see the data part of it.
Actually, they are nothing but ordinary variables which are bound to the classes and objects namespaces
i.e. the names are valid within the context of these classes and objects only.
There are two types of fields - class variables and object variables which are classified depending on
whether the class or the object owns the variables respectively.
Class variables are shared in the sense that they are accessed by all objects (instances) of that class.
There is only copy of the class variable and when any one object makes a change to a class variable, the
change is reflected in all the other instances as well.
70

Object variables are owned by each individual object/instance of the class. In this case, each object has
its own copy of the field i.e. they are not shared and are not related in any way to the field by the samen
name in a different instance of the same class. An example will make this easy to understand.
Using Class and Object Variables
Example 11.4. Using Class and Object Variables
#!/usr/bin/python
# Filename: objvar.py
class Person:
'''Represents a person.'''
population = 0
def __init__(self, name):
'''Initializes the person's data.'''
self.name = name
print '(Initializing %s)' % self.name
# When this person is created, he/she
# adds to the population
Person.population += 1
def __del__(self):
'''I am dying.'''
print '%s says bye.' % self.name
Person.population -= 1
if Person.population == 0:
print 'I am the last one.'
else:
print 'There are still %d people left.' % Person.population
def sayHi(self):
'''Greeting by the person.
Really, that's all it does.'''
print 'Hi, my name is %s.' % self.name
def howMany(self):
'''Prints the current population.'''
if Person.population == 1:
print 'I am the only person here.'
else:
print 'We have %d persons here.' % Person.population
swaroop = Person('Swaroop')
swaroop.sayHi()
swaroop.howMany()
kalam = Person('Abdul Kalam')
kalam.sayHi()
kalam.howMany()
swaroop.sayHi()
swaroop.howMany()
71

Output
$ python objvar.py
(Initializing Swaroop)
Hi, my name is Swaroop.
I am the only person here.
(Initializing Abdul Kalam)
Hi, my name is Abdul Kalam.
We have 2 persons here.
Hi, my name is Swaroop.
We have 2 persons here.
Abdul Kalam says bye.
There are still 1 people left.
Swaroop says bye.
I am the last one.
How It Works
This is a long example but helps demonstrate the nature of class and object variables. Here, popula-
tion belongs to the Person class and hence is a class variable. The name variable belongs to the ob-
ject (it is assigned using self) and hence is an object variable.
Thus, we refer to the population class variable as Person.population and not as
self.population. Note that an object variable with the same name as a class variable will hide the
class variable! We refer to the object variable name using self.name notation in the methods of that
object. Remember this simple difference between class and object variables.
Observe that the __init__ method is used to initialize the Person instance with a name. In this
method, we increase the population count by 1 since we have one more person being added. Also
observe that the values of self.name is specific to each object which indicates the nature of object
variables.
Remember, that you must refer to the variables and methods of the same object using the self variable
only. This is called an attribute reference.
In this program, we also see the use of docstrings for classes as well as methods. We can access the
class docstring at runtime using Person.__doc__ and the method docstring as Per-
son.sayHi.__doc__
Just like the __init__ method, there is another special method __del__ which is called when an ob-
ject is going to die i.e. it is no longer being used and is being returned to the system for reusing that
piece of memory. In this method, we simply decrease the Person.population count by 1.
The __del__ method is run when the object is no longer in use and there is no guarantee when that
method will be run. If you want to explicitly do this, you just have to use the del statement which we
have used in previous examples.
72

All class members (including the data members) are public and all the methods are virtual in
Python.
One exception: If you use data members with names using the double underscore prefix such as
__privatevar, Python uses name-mangling to effectively make it a private variable.
Thus, the convention followed is that any variable that is to be used only within the class or ob-
ject should begin with an underscore and all other names are public and can be used by other
classes/objects. Remember that this is only a convention and is not enforced by Python (except
for the double underscore prefix).
Also, note that the __del__ method is analogous to the concept of a destructor.
Inheritance
One of the major benefits of object oriented programming is reuse of code and one of the ways this is
achieved is through the inheritance mechanism. Inheritance can be best imagined as implementing a
type and subtype relationship between classes.
Suppose you want to write a program which has to keep track of the teachers and students in a college.
They have some common characteristics such as name, age and address. They also have specific charac-
teristics such as salary, courses and leaves for teachers and, marks and fees for students.
You can create two independent classes for each type and process them but adding a new common char-
acteristic would mean adding to both of these independent classes. This quickly becomes unwieldy.
A better way would be to create a common class called SchoolMember and then have the teacher and
student classes inherit from this class i.e. they will become sub-types of this type (class) and then we can
add specific characteristics to these sub-types.
There are many advantages to this approach. If we add/change any functionality in SchoolMember,
this is automatically reflected in the subtypes as well. For example, you can add a new ID card field for
both teachers and students by simply adding it to the SchoolMember class. However, changes in the sub-
types do not affect other subtypes. Another advantage is that if you can refer to a teacher or student ob-
ject as a SchoolMember object which could be useful in some situations such as counting of the num-
ber of school members. This is called polymorphism where a sub-type can be substituted in any situ-
ation where a parent type is expected i.e. the object can be treated as an instance of the parent class.
Also observe that we reuse the code of the parent class and we do not need to repeat it in the different
classes as we would have had to in case we had used independent classes.
The SchoolMember class in this situation is known as the base class or the superclass. The Teacher
and Student classes are called the derived classes or subclasses.
We will now see this example as a program.
Using Inheritance
Example 11.5. Using Inheritance
#!/usr/bin/python
# Filename: inherit.py
73

class SchoolMember:
'''Represents any school member.'''
def __init__(self, name, age):
self.name = name
self.age = age
print '(Initialized SchoolMember: %s)' % self.name
def tell(self):
'''Tell my details.'''
print 'Name:"%s" Age:"%s"' % (self.name, self.age),
class Teacher(SchoolMember):
'''Represents a teacher.'''
def __init__(self, name, age, salary):
SchoolMember.__init__(self, name, age)
self.salary = salary
print '(Initialized Teacher: %s)' % self.name
def tell(self):
SchoolMember.tell(self)
print 'Salary: "%d"' % self.salary
class Student(SchoolMember):
'''Represents a student.'''
def __init__(self, name, age, marks):
SchoolMember.__init__(self, name, age)
self.marks = marks
print '(Initialized Student: %s)' % self.name
def tell(self):
SchoolMember.tell(self)
print 'Marks: "%d"' % self.marks
t = Teacher('Mrs. Shrividya', 40, 30000)
s = Student('Swaroop', 22, 75)
print # prints a blank line
members = [t, s]
for member in members:
member.tell() # works for both Teachers and Students
Output
$ python inherit.py
(Initialized SchoolMember: Mrs. Shrividya)
(Initialized Teacher: Mrs. Shrividya)
(Initialized SchoolMember: Swaroop)
(Initialized Student: Swaroop)
Name:"Mrs. Shrividya" Age:"40" Salary: "30000"
Name:"Swaroop" Age:"22" Marks: "75"
How It Works
74

To use inheritance, we specify the base class names in a tuple following the class name in the class
definition. Next, we observe that the __init__ method of the base class is explicitly called using the
self variable so that we can initialize the base class part of the object. This is very important to re-
member - Python does not automatically call the constructor of the base class, you have to explicitly call
it yourself.
We also observe that we can call methods of the base class by prefixing the class name to the method
call and then pass in the self variable along with any arguments.
Notice that we can treat instances of Teacher or Student as just instances of the SchoolMember
when we use the tell method of the SchoolMember class.
Also, observe that the tell method of the subtype is called and not the tell method of the School-
Member class. One way to understand this is that Python always starts looking for methods in the type,
which in this case it does. If it could not find the method, it starts looking at the methods belonging to its
base classes one by one in the order they are specified in the tuple in the class definition.
A note on terminology - if more than one class is listed in the inheritance tuple, then it is called multiple
inheritance.
Summary
We have now explored the various aspects of classes and objects as well as the various terminologies as-
sociated with it. We have also seen the benefits and pitfalls of object-oriented programming. Python is
highly object-oriented and understanding these concepts carefully will help you a lot in the long run.
Next, we will learn how to deal with input/output and how to access files in Python.
75

Chapter 12. Input/Output
There will be lots of times when you want your program to interact with the user (which could be your-
self). You would want to take input from the user and then print some results back. We can achieve this
using the raw_input and print statements respectively. For output, we can also use the various
methods of the str (string) class. For example, you can use the rjust method to get a string which is
right justified to a specified width. See help(str) for more details.
Another common type of input/output is dealing with files. The ability to create, read and write files is
essential to many programs and we will explore this aspect in this chapter.
Files
You can open and use files for reading or writing by creating an object of the file class and using its
read, readline or write methods appropriately to read from or write to the file. The ability to read
or write to the file depends on the mode you have specified for the file opening. Then finally, when you
are finished with the file, you call the close method to tell Python that we are done using the file.
Using file
Example 12.1. Using files
#!/usr/bin/python
# Filename: using_file.py
poem = '''
Programming is fun
use Python!
'''
f = file('poem.txt', 'w') # open for 'w'riting
f.write(poem) # write text to file
f.close() # close the file
f = file('poem.txt') # if no mode is specified, 'r'ead mode is assumed by default
while True:
line = f.readline()
if len(line) == 0: # Zero length indicates EOF
break
print line, # Notice comma to avoid automatic newline added by Python
f.close() # close the file
Output
$ python using_file.py
76

Programming is fun
use Python!
How It Works
First, we create an instance of the file class by specifying the name of the file and the mode in which
we want to open the file. The mode can be a read mode ('r'), write mode ('w') or append mode
('a'). There are actually many more modes available and help(file) will give you more details
about them.
We first open the file in write mode and use the write method of the file class to write to the file
and then we finally close the file.
Next, we open the same file again for reading. If we don't specify a mode, then the read mode is the de-
fault one. We read in each line of the file using the readline method, in a loop. This method returns a
complete line including the newline character at the end of the line. So, when an empty string is re-
turned, it indicates that the end of the file has been reached and we stop the loop.
Notice that we use a comma with the print statement to suppress the automatic newline that the
print statement adds because the line that is read from the file already ends with a newline character.
Then, we finally close the file.
Now, see the contents of the poem.txt file to confirm that the program has indeed worked properly.
Pickle
Python provides a standard module called pickle using which you can store any Python object in a
file and then get it back later intact. This is called storing the object persistently.
There is another module called cPickle which functions exactly same as the pickle module except
that it is written in the C language and is (upto 1000 times) faster. You can use either of these modules,
although we will be using the cPickle module here. Remember though, that we refer to both these
modules as simply the pickle module.
Pickling and Unpickling
Example 12.2. Pickling and Unpickling
#!/usr/bin/python
# Filename: pickling.py
import cPickle as p
#import pickle as p
shoplistfile = 'shoplist.data' # the name of the file where we will store the objec
shoplist = ['apple', 'mango', 'carrot']
# Write to the file
Input/Output
77

f = file(shoplistfile, 'w')
p.dump(shoplist, f) # dump the object to a file
f.close()
del shoplist # remove the shoplist
# Read back from the storage
f = file(shoplistfile)
storedlist = p.load(f)
print storedlist
Output
$ python pickling.py
['apple', 'mango', 'carrot']
How It Works
First, notice that we use the import..as syntax. This is handy since we can use a shorter name for a
module. In this case, it even allows us to switch to a different module (cPickle or pickle) by
simply changing one line! In the rest of the program, we simply refer to this module as p.
To store an object in a file, first we open a file object in write mode and store the object into the open
file by calling the dump function of the pickle module. This process is called pickling.
Next, we retrieve the object using the load function of the pickle module which returns the object.
This process is called unpickling.
Summary
We have discussed various types of input/output and also file handling and using the pickle module.
Next, we will explore the concept of exceptions.
Input/Output
78

Chapter 13. Exceptions
Exceptions occur when certain exceptional situations occur in your program. For example, what if you
are going to read a file and the file does not exist? Or what if you accidentally deleted it when the pro-
gram was running? Such situations are handled using exceptions.
What if your program had some invalid statements? This is handled by Python which raises its hands
and tells you there is an error.
Errors
Consider a simple print statement. What if we misspelt print as Print? Note the capitalization. In
this case, Python raises a syntax error.
>>> Print 'Hello World'
File "<stdin>", line 1
Print 'Hello World'
^
>>> print 'Hello World'
Hello World
Observe that a SyntaxError is raised and also the location where the error was detected is printed.
This is what an error handler for this error does.
Try..Except
We will try to read input from the user. Press Ctrl-d and see what happens.
>>> s = raw_input('Enter something --> ')
Enter something --> Traceback (most recent call last):
File "<stdin>", line 1, in ?
EOFError
Python raises an error called EOFError which basically means it found an end of file when it did not
expect to (which is represented by Ctrl-d)
Next, we will see how to handle such errors.
Handling Exceptions
We can handle exceptions using the try..except statement. We basically put our usual statements
within the try-block and put all our error handlers in the except-block.
79

Example 13.1. Handling Exceptions
#!/usr/bin/python
# Filename: try_except.py
import sys
try:
s = raw_input('Enter something --> ')
except EOFError:
print 'nWhy did you do an EOF on me?'
sys.exit() # exit the program
except:
print 'nSome error/exception occurred.'
# here, we are not exiting the program
print 'Done'
Output
$ python try_except.py
Enter something -->
Why did you do an EOF on me?
$ python try_except.py
Enter something --> Python is exceptional!
Done
How It Works
We put all the statements that might raise an error in the try block and then handle all the errors and
exceptions in the except clause/block. The except clause can handle a single specified error or ex-
ception, or a parenthesized list of errors/exceptions. If no names of errors or exceptions are supplied, it
will handle all errors and exceptions. There has to be at least one except clause associated with every
try clause.
If any error or exception is not handled, then the default Python handler is called which just stops the ex-
ecution of the program and prints a message. We have already seen this in action.
You can also have an else clause associated with a try..catch block. The else clause is executed
if no exception occurs.
We can also get the exception object so that we can retrieve additional information about the exception
which has occurred. This is demonstrated in the next example.
Raising Exceptions
Exceptions
80

You can raise exceptions using the raise statement. You also have to specify the name of the error/
exception and the exception object that is to be thrown along with the exception. The error or exception
that you can arise should be class which directly or indirectly is a derived class of the Error or Ex-
ception class respectively.
How To Raise Exceptions
Example 13.2. How to Raise Exceptions
#!/usr/bin/python
# Filename: raising.py
class ShortInputException(Exception):
'''A user-defined exception class.'''
def __init__(self, length, atleast):
Exception.__init__(self)
self.length = length
self.atleast = atleast
try:
s = raw_input('Enter something --> ')
if len(s) < 3:
raise ShortInputException(len(s), 3)
# Other work can continue as usual here
except EOFError:
print 'nWhy did you do an EOF on me?'
except ShortInputException, x:
print 'ShortInputException: The input was of length %d,
was expecting at least %d' % (x.length, x.atleast)
else:
print 'No exception was raised.'
Output
$ python raising.py
Enter something -->
Why did you do an EOF on me?
$ python raising.py
Enter something --> ab
ShortInputException: The input was of length 2, was expecting at least 3
$ python raising.py
Enter something --> abc
No exception was raised.
How It Works
Exceptions
81

Here, we are creating our own exception type although we could've used any predefined exception/error
for demonstration purposes. This new exception type is the ShortInputException class. It has two
fields - length which is the length of the given input, and atleast which is the minimum length that
the program was expecting.
In the except clause, we mention the class of error as well as the variable to hold the corresponding er-
ror/exception object. This is analogous to parameters and arguments in a function call. Within this par-
ticular except clause, we use the length and atleast fields of the exception object to print an ap-
propriate message to the user.
Try..Finally
What if you were reading a file and you wanted to close the file whether or not an exception was raised?
This can be done using the finally block. Note that you can use an except clause along with a fi-
nally block for the same corresponding try block. You will have to embed one within another if you
want to use both.
Using Finally
Example 13.3. Using Finally
#!/usr/bin/python
# Filename: finally.py
import time
try:
f = file('poem.txt')
while True: # our usual file-reading idiom
line = f.readline()
if len(line) == 0:
break
time.sleep(2)
print line,
finally:
f.close()
print 'Cleaning up...closed the file'
Output
$ python finally.py
Programming is fun
Cleaning up...closed the file
Traceback (most recent call last):
File "finally.py", line 12, in ?
time.sleep(2)
KeyboardInterrupt
Exceptions
82

How It Works
We do the usual file-reading stuff, but I've arbitrarily introduced a way of sleeping for 2 seconds before
printing each line using the time.sleep method. The only reason is so that the program runs slowly
(Python is very fast by nature). When the program is still running, press Ctrl-c to interrupt/cancel the
program.
Observe that a KeyboardInterrupt exception is thrown and the program exits, but before the pro-
gram exits, the finally clause is executed and the file is closed.
Summary
We have discussed the usage of the try..except and try..finally statements. We have seen
how to create our own exception types and how to raise exceptions as well.
Next, we will explore the Python Standard Library.
Exceptions
83

Chapter 14. The Python Standard
Library
Introduction
The Python Standard Library is available with every Python installation. It contains a huge number of
very useful modules. It is important that you become familiar with the Python Standard Library since
most of your problems can be solved more easily and quickly if you are familiar with this library of
modules.
We will explore some of the commonly used modules in this library. You can find complete details for
all of the modules in the Python Standard Library in the 'Library Reference' section in the documenta-
tion that comes with your Python installation.
The sys module
The sys module contains system-specific functionality. we have already seen that the sys.argv list
contains the command-line arguments.
Command Line Arguments
Example 14.1. Using sys.argv
#!/usr/bin/python
# Filename: cat.py
import sys
def readfile(filename):
'''Print a file to the standard output.'''
f = file(filename)
while True:
line = f.readline()
if len(line) == 0:
break
print line, # notice comma
f.close()
# Script starts from here
if len(sys.argv) < 2:
print 'No action specified.'
sys.exit()
if sys.argv[1].startswith('--'):
option = sys.argv[1][2:]
# fetch sys.argv[1] but without the first two characters
if option == 'version':
print 'Version 1.2'
elif option == 'help':
print '''
This program prints files to the standard output.
84

Any number of files can be specified.
Options include:
--version : Prints the version number
--help : Display this help'''
else:
print 'Unknown option.'
sys.exit()
else:
for filename in sys.argv[1:]:
readfile(filename)
Output
$ python cat.py
No action specified.
$ python cat.py --help
This program prints files to the standard output.
Any number of files can be specified.
Options include:
--version : Prints the version number
--help : Display this help
$ python cat.py --version
Version 1.2
$ python cat.py --nonsense
Unknown option.
$ python cat.py poem.txt
Programming is fun
use Python!
How It Works
This program tries to mimic the cat command familiar to Linux/Unix users. You just speicfy the names
of some text files and it will print them to the output.
When a Python program is run i.e. not an interactive mode, there is always at least one item in the
sys.argv list which is the name of the current program being run and is available as sys.argv[0]
since Python starts counting from 0. Other command line arguments follow this item.
To make the program user-friendly we have supplied certain options that the user can specify to learn
more about the program. We use the first argument to check if any options have been specified to our
program. If the --version option is used, the version number of the program is printed. Similarly,
when the --help option is specified, we give a bit of explanation about the program. We make use of
the sys.exit function to exit the running program. As always, see help(sys.exit) for more de-
tails.
When no options are specified and filenames are passed to the program, it simply prints out each line of
The Python Standard Library
85

each file, one after the other in the order specified on the command line.
As an aside, the name cat is short for concatenate which is basically what this program does - it can
print out a file or attach/concatenate two or more files together in the output.
More sys
The sys.version string gives you information about the version of Python that you have installed.
The sys.version_info tuple gives an easier way of enabling Python-version specific parts of your
program.
[swaroop@localhost code]$ python
>>> import sys
>>> sys.version
'2.3.4 (#1, Oct 26 2004, 16:42:40) n[GCC 3.4.2 20041017 (Red Hat 3.4.2-6.fc3)]'
>>> sys.version_info
(2, 3, 4, 'final', 0)
For experienced programmers, other items of interest in the sys module include sys.stdin,
sys.stdout and sys.stderr which correspond to the standard input, standard output and standard
error streams of your program respectively.
The os module
This module represents generic operating system functionality. This module is especially important if
you want to make your programs platform-independent i.e. it allows the program to be written such that
it will run on Linux as well as Windows without any problems and without requiring changes. An ex-
ample of this is using the os.sep variable instead of the operation system-specific path separator.
Some of the more useful parts of the os module are listed below Most of them are self-explanatory.
• The os.name string specifies which platform you are using, such as 'nt' for Windows and
'posix' for Linux/Unix users.
• The os.getcwd() function gets the current working directory i.e. the path of the directory from
which the curent Python script is working.
• The os.getenv() and os.putenv() functions are used to get and set environment variables
respectively.
• The os.listdir() function returns the name of all files and directories in the specified directory.
• The os.remove() function is used to delete a file.
• The os.system() function is used to run a shell command.
• The os.linesep string gives the line terminator used in the current platform. For example, Win-
dows uses 'rn', Linux uses 'n' and Mac uses 'r'.
• The os.path.split() function returns the directory name and file name of the path.
86

>>> os.path.split('/home/swaroop/byte/code/poem.txt')
('/home/swaroop/byte/code', 'poem.txt')
• The os.path.isfile() and the os.path.isdir() functions check if the given path refers
to a file or directory respectively. Similarly, the os.path.exists() function is used to check if
a given path actually exists.
You can explore the Python Standard Documentation for more details on these functions and variables.
You can use help(sys), etc. as well.
Summary
We have seen some of the functionality of the sys module and sys modules in the Python Standard
Library. You should explore the Python Standard Documentation to find out more about these and other
modules as well.
Next, we will cover various aspects of Python that will make our tour of Python more complete.
87

Chapter 15. More Python
Till now, we have covered majority of the various aspects of Python that you will use. In this chapter,
we will cover some more aspects that will make our knowledge of Python more complete.
Special Methods
There are certain special methods which have special significance in classes such as the __init__ and
__del__ methods whose significance we have already seen.
Generally, special methods are used to mimic certain behavior. For example, if you want to use the
x[key] indexing operation for your class (just like you use for lists and tuples) then just implement the
__getitem__() method and your job is done. If you think about it, this is what Python does for the
list class itself!
Some useful special methods are listed in the following table. If you want to know about all the special
methods, then a huge list is available in the Python Reference Manual.
Table 15.1. Some Special Methods
Name Explanation
__init__(self, ...) This method is called just before the newly created
object is returned for usage.
__del__(self) Called just before the object is destroyed
__str__(self) Called when we use the print statement with the
object or when str() is used.
__lt__(self, other) Called when the less than operator ( < ) is used.
Similarly, there are special methods for all the op-
erators (+, >, etc.)
__getitem__(self, key) Called when x[key] indexing operation is used.
__len__(self) Called when the built-in len() function is used
for the sequence object.
Single Statement Blocks
By now, you should have firmly understood that each block of statements is set apart from the rest by its
own indentation level. Well, this is true for the most part but it is not 100% accurate. If your block of
statements contains only one single statement, then you can specify it on the same line of, say, a condi-
tional statement or looping statement. The following example should make this clear:
>>> flag = True
>>> if flag: print 'Yes'
...
Yes
As we can see, the single statement is used in-place and not as a separate block. Although, you can use
88

this for making your program smaller, I strongly recommend that you do not use this short-cut method
except for error checking, etc. One major reason is that it will be much easier to add an extra statement if
you are using proper indentation.
Also notice that when the Python interpreter is used in interactive mode, it helps you enter the state-
ments by changing prompts appropriately. In the aboe case, after you entered the keyword if, it
changes the prompt to ... to indicate that the statement is not yet complete. When we do complete the
statement in this manner, we press enter to confirm that the statement is complete. Then, Python fin-
ishes executing the whole statement and returns to the old prompt waiting for the next input.
List Comprehension
List comprehensions are used to derive a new list from an existing list. For example, you have a list of
numbers and you want to get a corresponding list with all the numbers multiplied by 2 but only when the
number itself is greater than 2. List comprehensions are ideal for such situations.
Using List Comprehensions
Example 15.1. Using List Comprehensions
#!/usr/bin/python
# Filename: list_comprehension.py
listone = [2, 3, 4]
listtwo = [2*i for i in listone if i > 2]
print listtwo
Output
$ python list_comprehension.py
[6, 8]
How It Works
Here, we derive a new list by specifying the manipulation to be done (2*i) when some condition is sat-
isfied (if i > 2). Note that the original list remains unmodified. Many a time, we use loops to pro-
cess each element of a list, the same can be achieved using list comprehensions in a more precise, com-
pact and explicit manner.
Receiving Tuples and Lists in Functions
There is a special way of receiving parameters to a function as a tuple or a dictionary using the * or **
prefix respectively. This is useful when taking variable number of arguments in the function.
More Python
89

>>> def powersum(power, *args):
... '''Return the sum of each argument raised to specified power.'''
... total = 0
... for i in args:
... total += pow(i, power)
... return total
...
>>> powersum(2, 3, 4)
25
>>> powersum(2, 10)
100
Due to the * prefix on the args variable, all extra arguments passed to the function are stored in args
as a tuple. If a ** prefix had been used instead, the extra parameters would be considered to be key/
value pairs of a dictionary.
Lambda Forms
A lambda statement is used to create new function objects and then return them at runtime.
Using Lambda Forms
Example 15.2. Using Lambda Forms
#!/usr/bin/python
# Filename: lambda.py
def make_repeater(n):
return lambda s: s * n
twice = make_repeater(2)
print twice('word')
print twice(5)
Output
$ python lambda.py
wordword
10
More Python
90

How It Works
Here, we use a function make_repeater to create new function objects at runtime and return it. A
lambda statement is used to create the function object. Essentially, the lambda takes a parameter fol-
lowed by a single expression only which becomes the body of the function and the value of this expres-
sion is returned by the new function. Note that even a print statement cannot be used inside a lambda
form, only expressions.
The exec and eval statements
The exec statement is used to execute Python statements which are stored in a string or file. For ex-
ample, we can generate a string containing Python code at runtime and then execute these statements us-
ing the exec statement. A simple example is shown below.
>>> exec 'print "Hello World"'
Hello World
The eval statement is used to evaluate valid Python expressions which are stored in a string. A simple
example is shown below.
>>> eval('2*3')
6
The assert statement
The assert statement is used to assert that something is true. For example, if you are very sure that
you will have at least one element in a list you are using and want to check this, and raise an error if it is
not true, then assert statement is ideal in this situation. When the assert statement fails, an Asser-
tionError is raised.
>>> mylist = ['item']
>>> assert len(mylist) >= 1
>>> mylist.pop()
'item'
>>> assert len(mylist) >= 1
Traceback (most recent call last):
File "<stdin>", line 1, in ?
AssertionError
The repr function
The reprt function is used to obtain a canonical string representation of the object. Backticks (also
More Python
91

called conversion or reverse quotes) do the same thing. Note that you will have ev-
al(repr(object)) == object most of the time.
>>> i = []
>>> i.append('item')
>>> `i`
"['item']"
>>> repr(i)
"['item']"
Basically, the repr function or the backticks are used to obtain a printable representation of the object.
you can control what your objects return for the repr function by defining the __repr__ method in
your class.
Summary
We have covered some more features of Python in this chapter and yet you can be sure we haven't
covered all the features of Python. However, at this stage, we have covered most of what you are ever
going to use in practice. This is sufficient for you to get started with whatever programs you are going to
create.
Next, we will discuss how to explore Python further.
More Python
92

Chapter 16. What Next?
If you have read this book thoroughly till now and practiced writing a lot of programs, then you must
have become comfortable and familiar with Python. You have probably created some Python programs
to try out stuff and to exercise your Python skills as well. If you have not done it already, you should.
The question now is 'What Next?'.
I would suggest that you tackle this problem: create your own command-line address-book program us-
ing which you can add, modify, delete or search for your contacts such as friends, family and colleagues
and their information such as email address and/or phone number. Details must be stored for later re-
trieval.
This is fairly easy if you think about it in terms of all the various stuff that we have come across till now.
If you still want directions on how to proceed, then here's a hint.
Hint. (You shouldn't be reading this). Create a class to represent the person's information. Use a dic-
tionary to store person objects with their name as the key. Use the cPickle module to store the objects
persistently on your hard disk. Use the dictionary built-in methods to add, delete and modify the per-
sons.
Once you are able to do this, you can claim to be a Python programmer. Now, immediately send me a
mail thanking me for this great book ;-) . This step is optional but recommended.
Here are some ways to continue your journey with Python:
Graphical Software
GUI Libraries using Python - you need these to create your own graphical programs using Python. You
can create your own IrfanView or Kuickshow or anything like that using the GUI libraries with their Py-
thon bindings. Bindings are what allow you to write programs in Python and use the libraries which are
themselves written in C or C++ or other languages.
There are lots of choices for GUI using Python:
• PyQt. This is the Python binding for the Qt toolkit which is the foundation upon which the KDE is
built. Qt is extremely easy to use and very powerful especially due to the Qt Designer and the amaz-
ing Qt documentation. You can use it for free on Linux but you will have to pay for it if you want to
use it on Windows. PyQt is free if you want to create free (GPL'ed) software on Linux/Unix and paid
if you want to create proprietary software. A good resource on PyQt is 'GUI Programming with Py-
thon: Qt Edition' [http://www.opendocs.org/pyqt/]. See the official homepage
[http://www.riverbankcomputing.co.uk/pyqt/index.php] for more details.
• PyGTK. This is the Python binding for the GTK+ toolkit which is the foundation upon which
GNOME is built. GTK+ has many quirks in usage but once you become comfortable, you can create
GUI apps fast. The Glade graphical interface designer is indispensable. The documentation is yet to
improve. GTK+ works well on Linux but its port to Windows is incomplete. You can create both
free as well as proprietary software using GTK+. See the official homepage [http://www.pygtk.org/]
for more details.
• wxPython. This is the Python bindings for the wxWidgets toolkit. wxPython has a learning curve
associated with it. However, it is very portable and runs on Linux, Windows, Mac and even embed-
ded platforms. There are many IDEs available for wxPython which include GUI designers as well
such as SPE (Stani's Python Editor) [http://spe.pycs.net/] and the wxGlade
[http://wxglade.sourceforge.net/] GUI builder. You can create free as well as proprietary software
using wxPython. See the official homepage [http://www.wxpython.org/] for more details.
93

• TkInter. This is one of the oldest GUI toolkits in existence. If you have used IDLE, you have seen
a TkInter program at work. The documentation for TkInter at PythonWare.org
[http://www.pythonware.com/library/tkinter/introduction/index.htm] is comprehensive. TkInter is
portable and works on both Linux/Unix as well as Windows. Importantly, TkInter is part of the
standard Python distribution.
• For more choices, see the GuiProgramming wiki page at Python.org
[http://www.python.org/cgi-bin/moinmoin/GuiProgramming]
Summary of GUI Tools
Unfortunately, there is no one standard GUI tool for Python. I suggest that you choose one of the above
tools depending on your situation. The first factor is whether you are willing to pay to use any of the
GUI tools. The second factor is whether you want the program to run on Linux or Windows or both. The
third factor is whether you are a KDE or GNOME user on Linux.
Future Chapters
I am contemplating writing 1 or 2 chapters for this book on GUI Programming. I will be prob-
ably be choosing wxPython as the choice of toolkit. If you would like to present your views on
the subject, please join the byte-of-python mailing list
[http://lists.ibiblio.org/mailman/listinfo/byte-of-python] where readers discuss with me on what
improvements can be made to the book.
Explore More
• The Python Standard Library is an extensive library. Most of the time, this library will have what
you are looking for. This is referred to as the 'batteries included' philosophy of Python. I highly re-
commend that you go through the Python Standard Documentation [http://docs.python.org/] before
you proceed to start writing large Python programs.
• Python.org [http://www.python.org/] - the official homepage of the Python programming language.
You will find the latest versions of the Python language and interpreter here. There are also various
mailing lists where active discussions on various aspects of Python take place.
• comp.lang.python is the usenet newsgroup where discussion about this language takes place. You
can post your doubts and queries to this newsgroup. You can access this online using Google Groups
[http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&group=comp.lang.python] or join the
mailing list [http://mail.python.org/mailman/listinfo/python-list] which is just a mirror of the news-
group.
• Python Cookbook [http://aspn.activestate.com/ASPN/Python/Cookbook/] is an extremely valuable
collection of recipes or tips on how to solve certain kinds of problems using Python. This is a must-
read for every Python user.
• Charming Python [http://gnosis.cx/publish/tech_index_cp.html] is an excellent series of Python-re-
lated articles by David Mertz.
• Dive Into Python [http://www.diveintopython.org/] is a very good book for experienced Python pro-
grammers. If you have thoroughly read the current book you are reading, then I would highly recom-
mend that you read 'Dive Into Python' next. It covers a range of topics including XML Processing,
Unit Testing and Functional Programming.
• Jython [http://www.jython.org/] is an implementation of the Python interpreter in the Java language.
This means that you can write programs in Python and use the Java libraries as well! Jython is a
What Next?
94

stable and mature software. If you are a Java programmer as well, I highly recommend that you give
Jython a try.
• IronPython [http://www.ironpython.com/] is an implementation of the Python interpreter in C# lan-
guage and can run on the .NET / Mono / DotGNU platform. This means that you can write programs
in Python and use the .NET Libraries and other libraries provided by these 3 platforms as well! Iron-
Python is still pre-alpha software and is suitable only for experimenting as of now. Jim Hugunin,
who wrote IronPython has joined Microsoft and will be working towards a full version of IronPy-
thon in future.
• Lython [http://www.caddr.com/code/lython/] is a Lisp frontend to the Python language. It is similar
to Common Lisp and compiles directly to Python bytecode which means that it will interoperate
with our usual Python code.
• There are many many more resources on Python. Interesting ones are Daily Python-URL!
[http://www.pythonware.com/daily/] which keeps you up to date on the latest Python happenings,
Vaults of Parnassus [http://www.vex.net/parnassus/], ONLamp.com Python DevCenter
[http://www.onlamp.com/python/], dirtSimple.org [http://dirtsimple.org/], Python Notes
[http://pythonnotes.blogspot.com/] and many many more.
Summary
We have now come to the end of this book but, as they say, this is the the beginning of the end!. You are
now an avid Python user and you are no doubt ready to solve many problems using Python. You can
start automating your computer to do all kinds of previously unimaginable things or write your own
games and much much more. So, get started!
What Next?
95

Appendix A. Free/Libré and Open
Source Software (FLOSS)
FLOSS is based on the concept of a community, which itself is based on the concept of sharing, and par-
ticularly the sharing of knowledge. FLOSS are free for usage, modification and redistribution.
If you have already read this book, then you are familiar with FLOSS as well since you have been using
Python all along!
If you want to know more about FLOSS, you can explore the following list. I have listed some big
FLOSS as well as those FLOSS which are cross-platform (i.e. work on Linux, Windows, etc.) so that
you can try using these software without the need to switch to Linux immediately although you eventu-
ally will ;-)
• Linux. This is a FLOSS operating system that the whole world is slowly embracing! It was started
by Linus Torvalds as a student. Now, it is giving competition to Microsoft Windows. The latest 2.6
kernel is a major breakthrough w.r.t. speed, stability and scalability. [ Linux Kernel
[http://www.kernel.org] ]
• Knoppix. This is a distribution of Linux which runs off just the CD! There is no installation re-
quired - you can just reboot your computer, pop the CD in the drive and start using a full-featured
Linux distribution! You can use all the various FLOSS that comes with a standard Linux distribution
such as running Python programs, compiling C programs, watching movies, etc. Then, reboot your
computer again, remove the CD and use your existing OS, as if nothing happened at all. [ Knoppix
[http://www.knopper.net] ]
• Fedora. This is a community-driven distribution, sponsored by Red Hat and is one of the most pop-
ular Linux distributions. It contains the Linux kernel, the KDE, GNOME and XFCE desktops, and
the plethora of FLOSS available and all this in an easy-to-use and easy-to-install manner.
If you care a complete beginner to Linux, then I would recommend that you try Mandrake Linux .
The newly released Mandrake 10.1 is just awesome. [ Fedora Linux [http://fedora.redhat.com], Man-
drake Linux [http://www.mandrakelinux.com] ]
• OpenOffice.org. This is an excellent office suite based on Sun Microsystems' StarOffice software.
OpenOffice has writer, presentation, spreadsheet and drawing components among other things. It
can even open and edit MS Word and MS PowerPoint files with ease. It runs on almost all platforms.
The upcoming OpenOffice 2.0 has some radical improvements. [ OpenOffice
[http://www.openoffice.org] ]
• Mozilla Firefox. This is the next generation web browser which is predicted to beat Internet Ex-
plorer (in terms of market share only ;-) in a few years. It is blazingly fast and has gained critical ac-
claim for its sensible and impressive features. The extensions concept allows any kind of functional-
ity to be added to it.
It's companion product Thunderbird is an excellent email client that makes reading email a snap. [
Mozilla Firefox [http://www.mozilla.org/products/firefox], Mozilla Thunderbird
[http://www.mozilla.org/products/thunderbird] ]
• Mono. This is an open source implementation of the Microsoft .NET platform. It allows .NET ap-
plications to be created and run on Linux, Windows, FreeBSD, Mac OS and many other platforms as
well. Mono implements the ECMA standards of the CLI and C# which Microsoft, Intel and HP have
submitted for standardization and they have now become open standards. This is a step in the direc-
tion of ISO standardization for the same.
96

Currently, there is a complete C# mcs (which itself is written in C#!), a feature-complete ASP.NET
implementation, many ADO.NET providers for databases and many many more features that are be-
ing improved and added everyday. [ Mono [http://www.mono-project.com], ECMA
[http://www.ecma-international.org], Microsoft .NET [http://www.microsoft.com/net] ]
• Apache web server. This is the popular open source web server. In fact, it is the most popular web
server on the planet! It runs nearly 60% of the websites out there. Yes, that's right - Apache handles
more websites than all the competition (including Microsoft IIS) combined. [ Apache
[http://www.apache.org] ]
• MySQL. This is an extremely popular open source database server. It is most famous for it's blazing
speed. More features are being added to it's latest versions. [ MySQL [http://www.mysql.com] ]
• MPlayer. This is a video player that can play anything from DivX to MP3 to Ogg to VCDs and
DVDs to ... who says open source ain't fun? ;-) [ MPlayer [http://www.mplayerhq.hu] ]
• Movix. This is a Linux distribution which is based on Knoppix and runs off the CD but is designed
to play movies! You can create Movix CDs which are just bootable CDs and when you reboot the
computer and pop in the CD, the movie starts playing by itself! You don't even need a hard disk to
watch a movie using Movix. [ Movix [http://movix.sourceforge.net] ]
This list is just intended to give you a brief idea - there are many more excellent FLOSS out there, such
as the Perl language, PHP language, Drupal content management system for websites, PostgreSQL data-
base server, TORCS racing game, KDevelop IDE, Anjuta IDE, Xine - the movie player, VIM editor,
Quanta+ editor, XMMS audio player, GIMP image editing program, ... this list could go on forever.
Visit the following websites for more information on FLOSS:
• SourceForge [http://www.sourceforge.net]
• FreshMeat [http://www.freshmeat.net]
• KDE [http://www.kde.org]
• GNOME [http://www.gnome.org]
To get the latest buzz in the FLOSS world, check out the following websites:
• OSNews [http://www.osnews.com]
• LinuxToday [http://www.linuxtoday.com]
• NewsForge [http://www.newsforge.com]
• SwaroopCH's blog [http://www.swaroopch.info/blog]
So, go ahead and explore the vast, free and open world of FLOSS!
Free/Libré and Open Source Software
(FLOSS)
97

Appendix B. About
Colophon
Almost all of the software that I have used in the creation of this book are free and open source
software. In the first draft of this book, I had used Red Hat 9.0 Linux as the foundation of my setup and
now for this sixth draft, I am using Fedora Core 3 Linux as the basis of my setup.
Initially, I was using KWord to write the book (as explained in the History Lesson in the preface). Later,
I switched to DocBook XML using Kate but I found it too tedious. So, I switched to OpenOffice which
was just excellent with the level of control it provided for formatting as well as the PDF generation, but
it produced very sloppy HTML from the document. Finally, I discovered XEmacs and I rewrote the
book from scratch in DocBook XML (again) after I decided that this format was the long term solution.
In this new sixth draft, I decided to use Quanta+ to do all the editing.
The standard XSL stylesheets that came with Fedora Core 3 Linux are being used. The standard default
fonts are used as well. The standard fonts are used as well. However, I have written a CSS document to
give color and style to the HTML pages. I have also written a crude lexical analyzer, in Python of
course, which automatically provides syntax highlighting to all the program listings.
About the Author
Swaroop C H loves his job which is being a software developer at Yahoo! in the Bangalore office in In-
dia. His interests on the technological side include FLOSS such as Linux, DotGNU, Qt and MySQL,
great languages like Python and C#, writing stuff like this book and any software he can create in his
spare time, as well as writing his blog. His other interests include coffee, reading Robert Ludlum novels,
trekking and politics.
If you are still to interested to know more about this guy, check out his blog at www.swaroopch.info
[http://www.swaroopch.info] .
98

Appendix C. Revision History
Timestamp
This document was generated on January 13, 2005 at 00:05
Revision History
Revision 1.20 13/01/2005
Complete rewrite using Quanta+ on FC3 with lot of corrections and updates. Many new examples. Re-
wrote my DocBook setup from scratch.
Revision 1.15 28/03/2004
Minor revisions
Revision 1.12 16/03/2004
Additions and corrections.
Revision 1.10 09/03/2004
More typo corrections, thanks to many enthusiastic and helpful readers.
Revision 1.00 08/03/2004
After tremendous feedback and suggestions from readers, I have made significant revisions to the con-
tent along with typo corrections.
Revision 0.99 22/02/2004
Added a new chapter on modules. Added details about variable number of arguments in functions.
Revision 0.98 16/02/2004
Wrote a Python script and CSS stylesheet to improve XHTML output, including a crude-yet-functional
lexical analyzer for automatic VIM-like syntax highlighting of the program listings.
Revision 0.97 13/02/2004
Another completely rewritten draft, in DocBook XML (again). Book has improved a lot - it is more co-
herent and readable.
Revision 0.93 25/01/2004
Added IDLE talk and more Windows-specific stuff
Revision 0.92 05/01/2004
Changes to few examples.
Revision 0.91 30/12/2003
Corrected typos. Improvised many topics.
Revision 0.90 18/12/2003
Added 2 more chapters. OpenOffice format with revisions.
Revision 0.60 21/11/2003
Fully rewritten and expanded.
Revision 0.20 20/11/2003
Corrected some typos and errors.
Revision 0.15 20/11/2003
Converted to DocBook XML.
Revision 0.10 14/11/2003
Initial draft using KWord.
99

Swaroop c h a byte of python

More Related Content

Similar to Swaroop c h a byte of python (20)

Recently uploaded (20)

Swaroop c h a byte of python