A Byte of Python



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A Byte of Python Swaroop C H 25 Jan 2013 Contents 1 A Byte of Python8 1.1 Who Reads A Byte of Python?...................8 1.2 Academic Courses.......................... 11 1.3 License................................. 12 1.4 Read Now............................... 12 1.5 Buy the Book............................. 12 1.6 Download............................... 12 1.7 Read the book in your native language............... 13 2 Preface 13 2.1 Who This Book Is For........................ 13 2.2 History Lesson............................ 13 2.3 Status Of The Book......................... 14 2.4 Official Website............................ 14 2.5 Something To Think About..................... 14 3 Introduction 15 3.1 Features of Python.......................... 15 3.1.1 Simple............................. 15 3.1.2 Easy to Learn......................... 15 3.1.3 Free and Open Source.................... 15 3.1.4 High-level Language..................... 16 1 3.1.5 Portable............................ 16 3.1.6 Interpreted.......................... 16 3.1.7 Object Oriented....................... 16 3.1.8 Extensible........................... 17 3.1.9 Embeddable.......................... 17 3.1.10 Extensive Libraries...................... 17 3.2 Python 2 versus 3.......................... 17 3.3 What Programmers Say....................... 18 4 Installation 18 4.1 Installation on Windows....................... 18 4.1.1 DOS Prompt......................... 18 4.1.2 Running Python prompt on Windows........... 20 4.2 Installation on Mac OS X...................... 20 4.3 Installation on Linux......................... 20 4.4 Summary............................... 21 5 First Steps 21 5.1 Using The Interpreter Prompt.................... 21 5.2 Choosing An Editor......................... 22 5.3 Using A Source File......................... 23 5.3.1 Executable Python Programs................ 25 5.4 Getting Help............................. 27 5.5 Summary............................... 27 6 Basics 27 6.1 Comments............................... 27 6.2 Literal Constants........................... 28 6.3 Numbers................................ 28 6.4 Strings................................. 29 6.4.1 Single Quote......................... 29 6.4.2 Double Quotes........................ 29 2 6.4.3 Triple Quotes......................... 29 6.4.4 Strings Are Immutable.................... 29 6.4.5 The format method..................... 30 6.5 Variable................................ 31 6.6 Identifier Naming........................... 31 6.7 Data Types.............................. 32 6.8 Object................................. 32 6.9 How to write Python programs................... 32 6.10 Example: Using Variables And Literal Constants......... 32 6.10.1 Logical And Physical Line.................. 33 6.10.2 Indentation.......................... 35 6.11 Summary............................... 35 7 Operators and Expressions 36 7.1 Operators............................... 36 7.1.1 Shortcut for math operation and assignment....... 38 7.2 Evaluation Order........................... 39 7.3 Changing the Order Of Evaluation................. 40 7.4 Associativity............................. 40 7.5 Expressions.............................. 40 7.6 Summary............................... 41 8 Control Flow 41 8.1 The if statement........................... 41 8.2 The while Statement......................... 44 8.3 The for loop.............................. 45 8.4 The break Statement......................... 46 8.4.1 Swaroop’s Poetic Python.................. 47 8.5 The continue Statement....................... 47 8.6 Summary............................... 48 3 9 Functions 48 9.1 Function Parameters......................... 49 9.2 Local Variables............................ 50 9.3 Using The global Statement..................... 51 9.4 Default Argument Values...................... 52 9.5 Keyword Arguments......................... 53 9.6 VarArgs parameters......................... 54 9.7 Keyword-only Parameters...................... 55 9.8 The return Statement........................ 56 9.9 DocStrings.............................. 57 9.10 Summary............................... 58 10 Modules 58 10.1 Byte-compiled .pyc files....................... 60 10.2 The from . . . import statement................... 60 10.3 A module’s name .......................... 61 10.4 Making Your Own Modules..................... 61 10.5 The dir function........................... 63 10.6 Packages................................ 64 10.7 Summary............................... 65 11 Data Structures 65 11.1 List.................................. 65 11.1.1 Quick Introduction To Objects And Classes........ 66 11.2 Tuple................................. 68 11.3 Dictionary............................... 69 11.4 Sequence................................ 71 11.5 Set................................... 73 11.6 References............................... 74 11.7 More About Strings......................... 75 11.8 Summary............................... 76 4 12 Problem Solving 76 12.1 The Problem............................. 77 12.2 The Solution............................. 77 12.3 Second Version............................ 80 12.4 Third Version............................. 81 12.5 Fourth Version............................ 83 12.6 More Refinements.......................... 84 12.7 The Software Development Process................. 85 12.8 Summary............................... 85 13 Object Oriented Programming 85 13.1 The self................................ 86 13.2 Classes................................. 87 13.3 Object Methods............................ 88 13.4 The init method........................... 88 13.5 Class And Object Variables..................... 89 13.6 Inheritance.............................. 92 13.7 Summary............................... 95 14 Input Output 95 14.1 Input from user............................ 95 14.2 Files.................................. 97 14.3 Pickle................................. 98 14.4 Summary............................... 99 15 Exceptions 99 15.1 Errors................................. 99 15.2 Exceptions.............................. 100 15.3 Handling Exceptions......................... 100 15.4 Raising Exceptions.......................... 101 15.5 Try .. Finally............................. 102 15.6 The with statement......................... 103 15.7 Summary............................... 104 5 16 Standard Library 104 16.1 sys module.............................. 105 16.2 logging module............................ 106 16.3 Module of the Week Series...................... 107 16.4 Summary............................... 107 17 More 107 17.1 Passing tuples around........................ 108 17.2 Special Methods........................... 108 17.3 Single Statement Blocks....................... 109 17.4 Lambda Forms............................ 109 17.5 List Comprehension......................... 110 17.6 Receiving Tuples and Dictionaries in Functions.......... 110 17.7 The assert statement......................... 111 17.8 Escape Sequences........................... 111 17.8.1 Raw String.......................... 112 17.9 Summary............................... 112 18 What Next 113 18.1 Example Code............................ 113 18.2 Questions and Answers........................ 114 18.3 Tutorials................................ 114 18.4 Videos................................. 114 18.5 Discussion............................... 114 18.6 News.................................. 114 18.7 Installing libraries.......................... 114 18.8 Graphical Software.......................... 115 18.8.1 Summary of GUI Tools................... 115 18.9 Various Implementations....................... 116 18.10Functional Programming (for advanced readers).......... 116 18.11Summary............................... 117 6 19 FLOSS 117 20 Colophon 118 20.1 Birth of the Book........................... 119 20.2 Teenage Years............................. 119 20.3 Now.................................. 119 20.4 About The Author.......................... 119 21 Revision History 119 22 Translations 122 22.1 Arabic................................. 122 22.2 Brazilian Portuguese......................... 122 22.3 Catalan................................ 122 22.4 Chinese................................ 123 22.5 Chinese Traditional.......................... 123 22.6 French................................. 124 22.7 German................................ 124 22.8 Greek................................. 125 22.9 Indonesian............................... 125 22.10Italian................................. 126 22.11Japanese................................ 126 22.12Mongolian............................... 126 22.13Norwegian (bokmål)......................... 126 22.14Polish................................. 127 22.15Portuguese.............................. 127 22.16Romanian............................... 127 22.17Russian and Ukranian........................ 128 22.18Slovak................................. 128 22.19Spanish................................ 128 22.20Swedish................................ 129 22.21Turkish................................ 129 7 23 Translation Howto 129 1 A Byte of Python ‘A Byte of Python’ is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you. This book is written for the latest Python 3, even though Python 2 is the commonly found version of Python today (read more about it in Python 2 versus 3 section). 1.1 Who Reads A Byte of Python? Here are what people are saying about the book: The best thing i found was “A Byte of Python”, which is simply a brilliant book for a beginner. It’s well written, the concepts are well explained with self evident examples. – Syed Talal (19 years old) This is the best beginner’s tutorial I’ve ever seen! Thank you for your effort. – Walt Michalik (wmich50-at-theramp-dot-net) You’ve made the best Python tutorial I’ve found on the Net. Great work. Thanks! – Joshua Robin (joshrob-at-poczta-dot-onet-dot-pl) Excellent gentle introduction to programming #Python for beginners – Shan Rajasekaran 8 Hi, I’m from Dominican Republic. My name is Pavel, recently I read your book ‘A Byte of Python’ and I consider it excellent!! :). I learnt much from all the examples. Your book is of great help for newbies like me. . . – Pavel Simo (pavel-dot-simo-at-gmail-dot-com) I recently finished reading Byte of Python, and I thought I really ought to thank you. I was very sad to reach the final pages as I now have to go back to dull, tedious oreilly or etc. manuals for learning about python. Anyway, I really appreciate your book. – Samuel Young (sy-one-three-seven-at-gmail-dot-com) Dear Swaroop, I am taking a class from an instructor that has no interest in teaching. We are using Learning Python, second edition, by O’Reilly. It is not a text for beginner without any programming knowledge, and an instructor that should be working in another field. Thank you very much for your book, without it I would be clueless about Python and programming. Thanks a million, you are able to ‘break the message down’ to a level that beginners can understand and not everyone can. – Joseph Duarte (jduarte1-at-cfl-dot-rr-dot-com) I love your book! It is the greatest Python tutorial ever, and a very useful reference. Brilliant, a true masterpiece! Keep up the good work! – Chris-André Sommerseth I’m just e-mailing you to thank you for writing Byte of Python online. I had been attempting Python for a few months prior to stumbling across your book, and although I made limited success with pyGame, I never completed a program. Thanks to your simplification of the categories, Python actually seems a reachable goal. It seems like I have finally learned the foundations and I can continue into my real goal, game development. 9 ... Once again, thanks VERY much for placing such a structured and helpful guide to basic programming on the web. It shoved me into and out of OOP with an understanding where two text books had failed. – Matt Gallivan (m-underscore-gallivan12-at-hotmail-dot-com) I would like to thank you for your book ‘A byte of python’ which i myself find the best way to learn python. I am a 15 year old i live in egypt my name is Ahmed. Python was my second programming language i learn visual basic 6 at school but didn’t enjoy it, however i really enjoyed learning python. I made the addressbook program and i was sucessful. i will try to start make more programs and read python programs (if you could tell me source that would be helpful). I will also start on learning java and if you can tell me where to find a tutorial as good as yours for java that would help me a lot. Thanx. – Ahmed Mohammed (sedo-underscore-91-at-hotmail-dot-com) A wonderful resource for beginners wanting to learn more about Python is the 110-page PDF tutorial A Byte of Python by Swaroop C H. It is well-written, easy to follow, and may be the best introduction to Python programming available. – Drew Ames in an article on Scripting Scribus published on Linux.com Yesterday I got through most of Byte of Python on my Nokia N800 and it’s the easiest and most concise introduction to Python I have yet encountered. Highly recommended as a starting point for learning Python. – Jason Delport on his weblog Byte of Vim and Python by @swaroopch is by far the best works in technical writing to me. Excellent reads #FeelGoodFactor – Surendran says in a tweet 10 “Byte of python” best one by far man (in response to the question “Can anyone suggest a good, inexpensive resource for learning the basics of Python?”) – Justin LoveTrue says in a Facebook community page “The Book Byte of python was very helpful ..Thanks bigtime :)” – Chinmay Always been a fan of A Byte of Python - made for both new and experienced programmers. – Patrick Harrington, in a StackOverflow answer Even NASA The book is even used by NASA! It is being used in their Jet Propulsion Laboratory with their Deep Space Network project. 1.2 Academic Courses This book is/was being used as instructional material in various educational institutions: •‘Principles of Programming Languages’ course at Vrije Universiteit, Ams- terdam •‘Basic Concepts of Computing’ course at University of California, Davis •‘Programming With Python’ course at Harvard University •‘Introduction to Programming’ course at University of Leeds •‘Introduction to Application Programming’ course at Boston University •‘Information Technology Skills for Meteorology’ course at University of Oklahoma •‘Geoprocessing’ course at Michigan State University •‘Multi Agent Semantic Web Systems’ course at the University of Edinburgh 11 1.3 License This book is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license. This means: • You are free to Share i.e. to copy, distribute and transmit this book • You are free to Remix i.e. to adapt this book • You are free to use it for commercial purposes Please note: • Please do not sell electronic or printed copies of the book unless you have clearly and prominently mentioned in the description that these are not from the original author of this book. • Attribution must be shown in the introductory description and front page of the document by linking back to http://www.swaroopch.com/notes/ Python and clearly indicating that the original text can be fetched from this location. • All the code/scripts provided in this book is licensed under the 3-clause BSD License unless otherwise noted. 1.4 Read Now You can read the book online. 1.5 Buy the Book A printed hardcopy of the book can be purchased for your offline reading pleasure, and to support the continued development and improvement of this book. 1.6 Download • PDF • Full source If you wish to support the continued development of this book, please consider buying a hardcopy. 12 1.7 Read the book in your native language If you are interested in reading or contributing translations of this book to other human languages, please see the Translations page. 2 Preface Python is probably one of the few programming languages which is both simple and powerful. This is good for beginners as well as for 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’. 2.1 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 Python and your favorite programming language - I have highlighted many such differences. A little warning though, Python is soon going to become your favorite programming language! 2.2 History Lesson I first started with Python when I needed to write an installer for software I had written called ‘Diamond’ 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 by Eric S. Raymond, a famous and respected hacker, where he talked about how Python had become his favorite programming language. I also found out that the PyQt bindings were more mature compared 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. 13 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. 2.3 Status Of The Book This book has been reformatted in October 2012 using Pandoc to allow generation of ebooks as requested by several users, along with errata fixes and updates. Changes in December 2008 edition (from the earlier major revision in March 2005) was updating for the Python 3.0 release. The book needs the help of its readers such as yourselves to point out any parts of the book which are not good, not comprehensible or are simply wrong. Please write to the main author or the respective translators with your comments and suggestions. 2.4 Official Website The official website of the book is http://www.swaroopch.com/notes/Python where you can read the whole book online, download the latest versions of the book, buy a printed hard copy, and also send me feedback. 2.5 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 14 3 Introduction Python is one of those rare languages which can claim to be both simple and powerful. You will find yourself pleasantly surprised to see 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. Story behind the name Guido van Rossum, the creator of the Python lan- guage, 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. 3.1 Features of Python 3.1.1 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 allows you to concentrate on the solution to the problem rather than the language itself. 3.1.2 Easy to Learn As you will see, Python is extremely easy to get started with. Python has an extraordinarily simple syntax, as already mentioned. 3.1.3 Free and Open Source Python is an example of a FLOSS (Free/Libré and Open Source Software). In simple terms, you can freely distribute copies of this software, read its source code, make changes to it, and use pieces of it in new free programs. 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 constantly improved by a community who just want to see a better Python. 15 3.1.4 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. 3.1.5 Portable Due to its open-source nature, Python has been ported to (i.e. changed to make it work on) 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, Windows CE and even PocketPC! You can even use a platform like Kivy to create games for iOS (iPhone, iPad) and Android. 3.1.6 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 running 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. This also makes your Python programs much more portable, since you can just copy your Python program onto another computer and it just works! 3.1.7 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 16 data and functionality. Python has a very powerful but simplistic way of doing OOP, especially when compared to big languages like C++ or Java. 3.1.8 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 program in C or C++ and then use it from your Python program. 3.1.9 Embeddable You can embed Python within your C/C++ programs to give ‘scripting’ capa- bilities for your program’s users. 3.1.10 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 interfaces), and other system-dependent stuff. Remember, all this is always available wherever Python is installed. This is called the Batteries Included philosophy of Python. Besides the standard library, there are various other high-quality libraries which you can find at the Python Package Index. 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. 3.2 Python 2 versus 3 You can ignore this section if you’re not interested in the difference between Python 2 and Python 3. But please do be aware of which version you are using. This book was rewritten in 2008 for Python 3. It was one of the first books to use Python 3. This, unfortunately, resulted in confusion for readers who would try to use Python 2 with the Python 3 version of the book and vice-versa. But slowly, the world is still migrating to Python 3. So, yes, you will be learning to use Python 3 in this book, even if you want to ultimately use Python 2. Remember that once you have properly understood and learn to use either of them, you can easily learn the changes between the two versions and adapt easily. The hard part is learning programming and 17 understanding the core Python language itself. That is our goal in this book, and once you have achieved that goal, you can easily use Python 2 or Python 3 depending on your situation. For details on differences between Python 2 to Python 3, see the Python/3 page on the Ubuntu wiki. 3.3 What Programmers Say You may find it interesting to read what great hackers like ESR have to say about Python: (1) 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. This article was the real inspiration for my first brush with Python. (2) 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 for more details. (3) 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 page which lists Python knowledge as a requirement for software engineers. 4 Installation 4.1 Installation on Windows Visit http://www.python.org/download/ and download the latest version. The installation is just like any other Windows-based software. Caution When you are given the option of unchecking any “optional” compo- nents, don’t uncheck any. 4.1.1 DOS Prompt If you want to be able to use Python from the Windows command line i.e. the DOS prompt, then you need to set the PATH variable appropriately. 18 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:\Python33 (please verify that this folder exists, it will be different for newer versions of Python) to the end of what is already there. Of course, use the appropriate directory name. For older versions of Windows, open the file C:\AUTOEXEC.BAT and add the line ‘PATH=%PATH%;C:\Python33’ (without the quotes) and restart the system. For Windows NT, use the AUTOEXEC.NT file. For Windows Vista: 1. Click Start and choose Control Panel 2. Click System, on the right you’ll see “View basic information about your computer” 3. On the left is a list of tasks, the last of which is “Advanced system settings.” Click that. 4. The Advanced tab of the System Properties dialog box is shown. Click the Environment Variables button on the bottom right. 5. In the lower box titled “System Variables” scroll down to Path and click the Edit button. 6. Change your path as need be. 7. Restart your system. Vista didn’t pick up the system path environment variable change until I restarted. For Windows 7: 1. Right click on Computer from your desktop and select properties or Click Start and choose Control Panel — System and Security — System. Click on Advanced system settings on the left and then click on the Advanced tab. At the bottom click on Environment Variables and under System variables, look for the PATH variable, select and then press Edit. 2. Go to the end of the line under Variable value and append ;C:\Python33. 3. If the value was %SystemRoot%\system32; It will now become %SystemRoot%\system32;C:\Python33 4. Click ok and you are done. No restart is required. 19 4.1.2 Running Python prompt on Windows For Windows users, you can run the interpreter in the command line if you have set the PATH variable appropriately. To open the terminal in Windows, click the start button and click ‘Run’. In the dialog box, type cmd and press enter key. Then, type python3 -V and ensure there are no errors. 4.2 Installation on Mac OS X For Mac OS X users, open the terminal by pressing Command+Space keys (to open Spotlight search), type Terminal and press enter key. Install Homebrew by running: ruby -e "$(curl -fsSkL raw.github.com/mxcl/homebrew/go)" Then install Python 3 using: brew install python3 Now, run python3 -V and ensure there are no errors. 4.3 Installation on Linux For Linux users, open the terminal by opening the Terminal application or by pressing Alt + F2 and entering gnome-terminal. If that doesn’t work, please refer the documentation or forums of your particular Linux distribution. Next, we have to install the python3 package. For example, on Ubuntu, you can use sudo apt-get install python3. Please check the documentation or forums of the Linux distribution that you have installed for the correct package manager command to run. Once you have finished the installation, run the python3 -V command in a shell and you should see the version of Python on the screen: $ python3 -V Python 3.3.0 Note $ is the prompt of the shell. It will be different for you depending on the settings of the operating system on your computer, hence I will indicate the prompt by just the $ symbol. Default in new versions of your distribution? Newer distributions such as Ubuntu 12.10 are making Python 3 the default version, so check if it is already installed. 20 4.4 Summary From now on, we will assume that you have Python 3 installed on your system. Next, we will write our first Python 3 program. 5 First Steps 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 using a source file. We will now see how to use both of these methods. 5.1 Using The Interpreter Prompt Open the terminal in your operating system (as discussed previously in the Installation chapter) and then open the Python prompt by typing python3 and pressing enter key. Once you have started python3, you should see >>> where you can start typing stuff. This is called the Python interpreter prompt. At the Python interpreter prompt, type print(’Hello World’) followed by the enter key. You should see the words Hello World as output. Here is an example of what you should be seeing, when using a Mac OS X computer. The details about the Python software will differ based on your computer, but the part from the prompt (i.e. from >>> onwards) should be the same regardless of the operating system. $ python3 Python 3.3.0 (default, Oct 22 2012, 12:20:36) [GCC 4.2.1 Compatible Apple Clang 4.0 ((tags/Apple/clang-421.0.60))] on darwin 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 Python 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. 21 How to Quit the Interpreter Prompt If you are using a Linux or Unix shell, you can exit the interpreter prompt by pressing ctrl-d or entering exit() (note: remember to include the parentheses, ‘()’) followed by the enter key. If you are using the Windows command prompt, press ctrl-z followed by the enter key. 5.2 Choosing An Editor We cannot type out our program at the interpreter prompt every time we want to run something, so we have to save them in files and can run our programs any number of times. To create our Python source files, we need an editor software where you can type and save. A good programmer’s editor will make your life easier in writing the source files. Hence, 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. 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 have no idea where to start, I would recommend using Komodo Edit software which is available on Windows, Mac OS X and Linux. If you are using Windows, do not 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 Komodo Edit will automatically do this. 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 benefit from using them to write your Python programs. I personally use both for most of my programs, and have even written an entire book on Vim. In case you are willing to take the time to learn Vim or Emacs, then I highly recommend that you do learn to use either of them as it will be very useful for you in the long run. However, as I mentioned before, beginners can start with Komodo Edit and focus the learning on Python rather than the editor at this moment. To reiterate, please choose a proper editor - it can make writing Python programs more fun and easy. For Vim users There is a good introduction on how to make Vim a powerful Python IDE by John M Anderson. Also recommended is the jedi-vim plugin and my own dotvim configuration. 22 For Emacs users There is a good introduction on how to make Emacs a pow- erful Python IDE by Pedro Kroger. Also recommended is BG’s dotemacs configuration. 5.3 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 (the author of the amazing ‘Beginning Perl’ book) puts it, it is the “traditional incantation to the programming gods to help you learn the language better.” Start your choice of editor, enter the following program and save it as hello.py. If you are using Komodo Edit, click on File — New — New File, type the lines: print(‚Hello World‚) In Komodo Edit, do File — Save to save to a file. Where should you save the file? To any folder for which you know the location of the folder. If you don’t understand what that means, create a new folder and use that location to save and run all your Python programs: • C:\\py on Windows •/tmp/py on Linux •/tmp/py on Mac OS X To create a folder, use the mkdir command in the terminal, for example, mkdir /tmp/py. Important Always ensure that you give it the file extension of .py, for example, foo.py. In Komodo Edit, click on Tools — Run Command, type python3 hello.py and click on Run and you should see the output printed like in the screenshot below. The best way, though, is to type it in Komodo Edit but to use a terminal: 1. Open a terminal as explained in the Installation chapter. 2. Change directory where you saved the file, for example, cd /tmp/py 23 Figure 1: Screenshot of Komodo Edit with the Hello World program 24 3. Run the program by entering the command python3 hello.py. The output is as shown below. $ python3 hello.py Hello World If you got the output as shown above, congratulations! - you have successfully run your first Python program. You have successfully crossed the hardest part of learning programming, which is, getting started with your first program! In case you got an error, please type the above program exactly as shown 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 character in each line - we will see why this is important later. How It Works A Python program is composed of statements. In our first program, we have only one statement. In this statement, we call the print function which just prints the text ’Hello World’. We will learn about functions in detail in a later chapter - what you should understand now is that whatever you supply in the parentheses will be printed back to the screen. In this case, we supply the text ’Hello World’. 5.3.1 Executable Python Programs This applies only to Linux and Unix users but Windows users should know this as well. Every time, you want to run a Python program, we have to explicitly call python3 foo.py, but why can’t we run it just like any other program on our computer? We can achieve that by using something called the hashbang line. Add the below line as the first line of your program: #!/usr/bin/env python3 So, your program should look like this now: #!/usr/bin/env python3 print(‚Hello World‚) 25 Second, we have to give the program executable permission using the chmod command then run the source program. The chmod command is used here to change the mode of the file by giving execute permission to all users of the system. $ chmod a+x hello.py Now, we can run our program directly because our operating system calls /usr/bin/env which in turn will find our Python 3 software and hence knows how to run our source file: $ ./hello.py Hello World We use the ./ to indicate that the program is located in the current folder. To make things more fun, you can rename the file to just hello and run it as ./hello and it 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. So far, we have been able to run our program as long as we know the exact path. What if we wanted to be able to run the program from folder? You can do this by storing the program in one of the folders listed in the PATH environment variable. Whenever you run any program, the system looks for that program in each of the folders 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 /usr/local/bin:/usr/bin:/bin:/usr/X11R6/bin:/home/swaroop/bin $ cp hello.py /home/swaroop/bin/hello $ hello Hello World We can display the PATH variable using the echo command and prefixing the variable name by $ to indicate to the shell that we need the value of this “environment 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. If you want to add a directory of your choice to the PATH variable - this can be done by running export PATH=$PATH:/home/swaroop/mydir where ’/home/swaroop/mydir’ is the directory I want to add to the PATH variable. 26 This method is very useful if you want to write commands you can run anytime, anywhere. It is like creating your own commands just like cd or any other commands that you use in the terminal. 5.4 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(print) - this displays the help for the print function which is used to print things to the screen. 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 return, then you need to put those inside quotes such as help(’return’) so that Python doesn’t get confused on what we’re trying to do. 5.5 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. 6 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 variables, and we’ll learn some other concepts as well in this chapter. 6.1 Comments Comments are any text to the right of the # symbol and is mainly useful as notes for the reader of the program. For example: print(‚Hello World‚)# Note that print is a function 27 or: # Note that print is a function print(‚Hello World‚) Use as many useful comments as you can in your program to: • explain assumptions • explain important decisions • explain important details • explain problems you’re trying to solve • explain problems you’re trying to overcome in your program, etc. Code tells you how, comments should tell you why. 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! 6.2 Literal Constants An example of a literal constant is a number like 5, 1.23, 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 literally. 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. 6.3 Numbers Numbers are mainly of two types - integers and floats. An examples of an integer is 2 which is just a whole number. Examples of floating point numbers (or floats for short) are 3.23 and 52.3E-4. The E notation indicates powers of 10. In this case, 52.3E-4 means 52.3 * 10ˆ-4ˆ. Note for Experienced Programmers There is no separate long type. The int type can be an integer of any size. 28 6.4 Strings A string is a sequence of characters. Strings are basically just a bunch of words. You will be using strings in almost every Python program that you write, so pay attention to the following part. 6.4.1 Single Quote 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. 6.4.2 Double Quotes Strings in double quotes work exactly the same way as strings in single quotes. An example is "What’s your name?" 6.4.3 Triple Quotes You can specify multi-line strings using triple quotes - (""" or ”’). You can use single quotes and double quotes freely within the triple quotes. An example is: ‚‚‚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." ‚‚‚ 6.4.4 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. 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 differ in any way. 29 6.4.5 The format method Sometimes we may want to construct strings from other information. This is where the format() method is useful. Save the following lines as a file str_format.py: age = 20 name = ‚Swaroop‚ print(‚{0} was {1} years old when he wrote this book‚.format(name, age)) print(‚Why is {0} playing with that python?‚.format(name)) Output: $ python3 str_format.py Swaroop was 20 years old when he wrote this book Why is Swaroop playing with that python? How It Works: A string can use certain specifications and subsequently, the format method can be called to substitute those specifications with corresponding arguments to the format method. Observe the first usage where we use {0} and this corresponds to the variable name which is the first argument to the format method. Similarly, the second specification is {1} corresponding to age which is the second argument to the format method. Note that Python starts counting from 0 which means that first position is at index 0, second position is at index 1, and so on. Notice that we could have achieved the same using string concatenation: name + ’ is ’ + str(age) + ’ years old’ but that is much uglier and error-prone. Second, the conversion to string would be done automatically by the format method instead of the explicit conversion to strings needed in this case. Third, when using the format method, we can change the message without having to deal with the variables used and vice-versa. Also note that the numbers are optional, so you could have also written as: age = 20 name = ‚Swaroop‚ print(‚{} was {} years old when he wrote this book‚.format(name, age)) print(‚Why is {} playing with that python?‚.format(name)) 30 which will give the same exact output as the previous program. What Python does in the format method is that it substitutes each argument value into the place of the specification. There can be more detailed specifications such as: decimal (.) precision of3 for float ‚0.333‚ >>> ‚{0:.3}‚.format(1/3) fill with underscores (_) with the text centered (^) to 11 width ‚___hello___‚ >>> ‚{0:_^11}‚.format(‚hello‚) keyword-based ‚Swaroop wrote A Byte of Python‚ >>> ‚{name} wrote {book}‚.format(name=‚Swaroop‚, book=‚A Byte of Python‚) 6.5 Variable 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 the name implies - 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. 6.6 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 (up- percase ASCII or lowercase ASCII or Unicode character) or an underscore (‘_’). • The rest of the identifier name can consist of letters (uppercase ASCII or lowercase ASCII or Unicode character), 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 the latter. • Examples of valid identifier names are i,__my_name, name_23. Examples of ‘’invalid” identifier names are 2things, this is spaced out, my-name, >a1b2_c3 and "this_is_in_quotes". 31 6.7 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. 6.8 Object 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 functions. We will now see how to use variables along with literal constants. Save the following example and run the program. 6.9 How to write Python programs Henceforth, the standard procedure to save and run a Python program is as follows: 1. Open your editor of choice, such as Komodo Edit. 2. Type the program code given in the example. 3. Save it as a file with the filename mentioned. 4. Run the interpreter with the command python3 program.py to run the program. 6.10 Example: 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) 32 Output: $ python3 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 function which, unsurprisingly, just prints the value of the variable to the screen. Then 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. Note for static language programmers Variables are used by just assigning them a value. No declaration or data type definition is needed/used. 6.10.1 Logical And Physical Line 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 itself (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 33 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 maximum of a single logical line on each single physical line. The idea is that you should never use the semicolon. In fact, I have never used or even seen a semicolon in a Python program. There is one kind of situation where this concept is really useful : if you have a long line of code, you can break it into multiple physical lines by using the backslash. 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 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 has a starting parentheses, starting square brackets or a starting curly braces but not an ending one. This is called implicit line joining. You can see this in action when we write programs using lists in later chapters. 34 6.10.2 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 grouping of statements. This means that statements which go together must have the same indentation. Each such set of statements is called a block. We will see examples of how blocks are important in later chapters. One thing you should remember is that 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 ^ IndentationError: unexpected indent 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 default 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. How to indent Use only spaces for indentation, with a tab stop of 4 spaces. Good editors like Komodo Edit will automatically do this for you. Make sure you use a consistent number of spaces for indentation, otherwise your program will show errors. Note to static language programmers Python will always use indentation for blocks and will never use braces. Run from __future__ import braces to learn more. 6.11 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. 35 7 Operators and Expressions Most statements (logical lines) that you write will contain expressions. A simple example of an expression 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 is called operands. In this case, 2 and 3 are the operands. 7.1 Operators We will briefly take a look at the operators and their usage: Note that 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 >>> + (plus) Adds two objects 3 + 5 gives 8.’a’ + ’b’ gives ’ab’. -(minus) Gives the subtraction of one number from the other; if the first operand is absent it is assumed to be zero. -5.2 gives a negative number and 50 - 24 gives 26. *(multiply) Gives the multiplication of the two numbers or returns the string repeated 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 1.3333333333333333. // (floor division) Returns the floor of the quotient 4 // 3 gives 1. 36 %(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 represented 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 specified. 11 >> 1 gives 5. 11 is represented in bits by 1011 which when right shifted by 1 bit gives 101which is the decimal 5. &(bit-wise AND) Bit-wise AND of the numbers 5 & 3 gives 1. | (bit-wise OR) Bitwise OR of the numbers 5 | 3 gives 7 ˆ (bit-wise XOR) Bitwise XOR of the numbers 5 ˆ 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 True or False. Note the capitalization of these names. 5 < 3 gives False and 3 < 5 gives 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 numbers, they are first converted to a common type. Otherwise, it always 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 returns True. 37 == (equal to) Compares if the objects are equal x = 2; y = 2; x == y returns True. x = ’str’; y = ’stR’; x == y returns False. x = ’str’; y = ’str’; x == y returns 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 x 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 returns False since x is False. In this case, Python will not evaluate y since it knows that the left hand side of the ‘and’ expression is False which implies that the whole expression will be False irrespective of the other values. This is called short-circuit evaluation. or (boolean OR) If x is True, it returns True, else it returns evaluation of y x = True; y = False; x or y returns True. Short-circuit evaluation applies here as well. 7.1.1 Shortcut for math operation and assignment It is common to run a math operation on a variable and then assign the result of the operation back to the variable, hence there is a shortcut for such expressions: You can write: a =2 a = a *3 as: a =2 a *=3 Notice that var = var operation expression becomes var operation= expression. 38 7.2 Evaluation Order 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 operator has higher precedence than the addition operator. The following table gives the 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 and expressions lower in the table before the ones listed higher in the table. The following table, taken from the Python reference manual, is provided for the sake of completeness. It is far better to use parentheses to group operators and operands appropriately in order to explicitly specify the precedence. This makes the program more readable. See Changing the Order of Evaluation below for details. lambda Lambda Expression or Boolean OR and Boolean AND not x Boolean NOT in, not in Membership tests is, is not Identity tests <, <=, >, >=, !=, == Comparisons | Bitwise OR ˆ Bitwise XOR & Bitwise AND <<, >> Shifts +, - Addition and subtraction *, /, //, % Multiplication, Division, Floor Division and Remainder +x, -x Positive, Negative ~x Bitwise NOT ** Exponentiation x.attribute Attribute reference 39 x[index] Subscription x[index1:index2] Slicing f(arguments ...) Function call (expressions, ...) Binding or tuple display [expressions, ...] List display {key:datum, ...} Dictionary display The operators which we have not already come across will be explained in later chapters. Operators with the same precedence are listed in the same row in the above table. For example, + and - have the same precedence. 7.3 Changing the Order Of Evaluation To make the expressions more readable, we can use parentheses. For example, 2 + (3 * 4) is definitely easier to understand than 2 + 3 * 4 which requires knowledge of the operator precedences. As with everything else, the parentheses should be used reasonably (do not overdo it) and should not be redundant, as in (2 + (3 * 4)). There is an additional advantage to using parentheses - it helps us to change the order of evaluation. For example, if you want addition to be evaluated before multiplication in an expression, then you can write something like (2 + 3) * 4. 7.4 Associativity Operators are usually associated from left to right. This means that operators with the 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). 7.5 Expressions Example (save as expression.py): length =5 breadth =2 area = length * breadth print(‚Area is‚, area) print(‚Perimeter is‚,2 * (length + breadth)) 40 Output: $ python3 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 calculate the area and perimeter of the rectangle with the help of expressions. We store the result of the expression length * breadth in the variable area and then print it using the print function. In the second case, we directly use the value of the expression 2 * (length + breadth) in the print function. 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 program is much more readable this way (since we don’t need to worry about spacing in the strings we use for output). This is an example of how Python makes life easy for the programmer. 7.6 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. 8 Control Flow In the programs we have seen till now, there has always been a series of statements faithfully executed by Python in exact top-down order. What if you wanted to change the flow of how it works? For example, you want the program to take some decisions and do different things depending on different situations, 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. 8.1 The if statement The if statement is used to check a condition: 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. Example (save as if.py): 41 number = 23 guess = int(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 guessed > number to reach here print(‚Done‚) # This last statement is always executed, after the if statement is executed Output: $ python3 if.py Enter an integer : 50 No, it is a little lower than that Done $ python3 if.py Enter an integer : 22 No, it is a little higher than that Done $ python3 if.py Enter an integer : 23 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 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 input function which prints it to the screen and waits for input from the user. Once we enter something and press enter key, the input() function returns what we entered, as 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 42 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 the “consistent indentation” 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 that they must 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 minimal valid if statement is: if True: print(‚Yes, it is true‚) After Python has finished executing the complete if statement along with the associated 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. Even though this is a very simple program, I have been pointing out a lot of things that you should notice. All these are pretty straightforward (and surprisingly simple for those of you from C/C++ backgrounds). You will need to become aware of all these things initially, but after some practice you will become comfortable with them, and it will all feel ‘natural’ to you. Note for C/C++ Programmers 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) 43 8.2 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. Example (save as while.py): number = 23 running = True while running: guess = int(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: $ python3 while.py Enter an integer : 50 No, it is a little lower than that. Enter an integer : 22 No, it is a little higher than that. Enter an integer : 23 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 run the program for each guess, as we have done in the previous section. This aptly demonstrates the use of the while statement. 44 We move the 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 continue 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 executed unless you break out of the loop with a break statement. The True and False are called Boolean types and you can consider them to be equivalent to the value 1 and 0respectively. Note for C/C++ Programmers Remember that you can have an else clause for the while loop. 8.3 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. Example (save as for.py): for i in range(1,5): print(i) else: print(‚The for loop is over‚) Output: $ python3 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 the built-in range function. 45 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 becomes 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. Note that range() generates a sequence of numbers, but it will generate only one number at a time, when the for loop requests for the next item. If you want to see the full sequence of numbers immediately, use list(range()). Lists are explained in the [data structures chapter]. 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][#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 radi- cally 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 pro- grammers 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 expressive and less error prone in Python. 8.4 The break Statement The break statement is used to break out of a loop statement i.e. stop the execution of a looping statement, even if the loop condition has not become False or the sequence of items has not been completely iterated over. An important note is that if you break out of a foror while loop, any corre- sponding loop else block is not executed. Example (save as break.py): while True: s = input(‚Enter something : ‚) 46 if s == ‚quit‚: break print(‚Length of the string is‚, len(s)) print(‚Done‚) Output: $ python3 break.py Enter something : Programming is fun Length of the string is 18 Enter something : When the work is done Length of the string is 21 Enter something : if you wanna make your work also fun: Length of the string is 37 Enter something : use Python! Length of the string is 12 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. 8.4.1 Swaroop’s Poetic Python The input I have used here is a mini poem I have written called Swaroop’s Poetic Python: Programming is fun When the work is done if you wanna make your work also fun: use Python! 8.5 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. Example (save as continue.py): 47 while True: s = input(‚Enter something : ‚) if s == ‚quit‚: break if len(s) <3: print(‚Too small‚) continue print(‚Input is of sufficient length‚) # Do other kinds of processing here... Output: $ python3 continue.py Enter something : a Too small Enter something : 12 Too small 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 the input string only if it is 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 statements in the loop are executed, doing any kind of processing we want to do here. Note that the continue statement works with the forloop as well. 8.6 Summary We have seen how to use the three control flow statements - if, while and for along with their associated break and continue statements. These are some of the most commonly used parts of Python and hence, becoming comfortable with them is essential. Next, we will see how to create and use functions. 9 Functions Functions are reusable pieces of programs. They allow you to give a name to a block of statements, allowing you to run that block using the specified name 48 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 len and range. The function concept is probably the most important building block of any non-trivial software (in any programming language), so we will explore various aspects of functions in this chapter. Functions are defined using the def keyword. After this keyword comes an identifier name for the function, followed by a pair of parentheses which may enclose some names of variables, and by the final colon that ends the line. Next follows the block of statements that are part of this function. An example will show that this is actually very simple: Example (save as function1.py): def sayHello(): print(‚Hello World!‚)# block belonging to the function # End of function sayHello() # call the function sayHello() # call the function again Output: $ python3 function1.py Hello World! 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. Notice that we can call the same function twice which means we do not have to write the same code again. 9.1 Function Parameters A function can take parameters, which are 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 these variables are defined when we call the function and are already assigned values when the function runs. 49 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 function call are called arguments. Example (save as func_param.py): def printMax(a, b): if a > b: print(a, ‚is maximum‚) elif a == b: print(a, ‚is equal to‚, b) else: print(b, ‚is maximum‚) printMax(3,4)# directly give literal values x =5 y =7 printMax(x, y) # give variables as arguments Output: $ python3 func_param.py 4 is maximum 7 is maximum How It Works: Here, we define a function called printMax that uses two parameters called a and b. We find out the greater number using a simple if..else statement and then print the bigger number. The first time we call the function printMax, we directly supply the numbers as arguments. In the second case, we call the function with variables as arguments. printMax(x, y) causes the value of argument x to be assigned to parameter a and the value of argument y to be assigned to parameter b. The printMax function works the same way in both cases. 9.2 Local Variables When you declare variables inside a function definition, they are not related in any way to other variables with the same names used outside the function 50 - 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. Example (save as func_local.py): x = 50 def func(x): print(‚x is‚, x) x =2 print(‚Changed local x to‚, x) func(x) print(‚x is still‚, x) Output: $ python3 func_local.py x is 50 Changed local x to 2 x is still 50 How It Works: The first time that we print the value of the name x with the first line in the function’s body, Python uses the value of the parameter declared in the main block, above the function definition. 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. With the last print function call, we display the value of x as defined in the main block, thereby confirming that it is actually unaffected by the local assignment within the previously called function. 9.3 Using The global Statement If you want to assign a value to a name defined at the top level of the program (i.e. not inside any kind of scope such as functions or classes), 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 51 not encouraged and should be avoided since it becomes unclear to the reader of the program as to where that variable’s definition is. Using the global statement makes it amply clear that the variable is defined in an outermost block. Example (save as func_global.py): x = 50 def func(): global x print(‚x is‚, x) x =2 print(‚Changed global x to‚, x) func() print(‚Value of x is‚, x) Output: $ python3 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 declare 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 e.g. global x, y, z. 9.4 Default Argument Values For some functions, you may want to make some parameters optional and use default values in case the user does not want to provide values for them. This is done with the help of default argument values. You can specify default argument values for parameters by appending to the parameter name in the function definition 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. Example (save as func_default.py): 52 def say(message, times =1): print(message * times) say(‚Hello‚) say(‚World‚,5) Output: $ python3 func_default.py Hello WorldWorldWorldWorldWorld How It Works: The function named say is used to print a string as many times as specified. 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 preceding a parameter without a default argument value in the function’s 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. 9.5 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 order of the arguments. Two, we can give values to only those parameters to which we want to, provided that the other parameters have default argument values. Example (save as func_key.py): 53 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: $ python3 func_key.py a is 3 and b is 7 and c is 10 a is 25 and b is 5 and c is 24 a is 100 and b is 5 and c is 50 How It Works: The function named func has one parameter without a default argument value, followed by two parameters with default argument values. In the first usage, func(3, 7), the parameter a gets the value 3, the parameter b gets the value 7 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 variable b gets the default value of 5. In the third usage func(c=50, a=100), we use keyword arguments for all speci- fied values. Notice that we are specifying the value for parameter c before that for a even though a is defined before c in the function definition. 9.6 VarArgs parameters Sometimes you might want to define a function that can take any number of parameters, this can be achieved by using the stars (save as total.py): def total(initial=5, *numbers, **keywords): count = initial for number in numbers: count += number for key in keywords: count += keywords[key] return count print(total(10,1,2,3, vegetables=50, fruits=100)) Output: 54 $ python3 total.py 166 How It Works: When we declare a starred parameter such as *param, then all the positional arguments from that point till the end are collected as a tuple called ‘param’. Similarly, when we declare a double-starred parameter such as **param, then all the keyword arguments from that point till the end are collected as a dictionary called ‘param’. We will explore tuples and dictionaries in a later chapter. 9.7 Keyword-only Parameters If we want to specify certain keyword parameters to be available as keyword-only and not as positional arguments, they can be declared after a starred parameter (save as keyword_only.py): def total(initial=5, *numbers, extra_number): count = initial for number in numbers: count += number count += extra_number print(count) total(10,1,2,3, extra_number=50) total(10,1,2,3) # Raises error because we have not supplied a default argument value for ‚extra_number‚ Output: $ python3 keyword_only.py 66 Traceback (most recent call last): File "keyword_only.py", line 12, in total(10, 1, 2, 3) TypeError: total() needs keyword-only argument extra_number How It Works: Declaring parameters after a starred parameter results in keyword-only arguments. If these arguments are not supplied a default value, then calls to the function will raise an error if the keyword argument is not supplied, as seen above. 55 Notice the use of += which is a shortcut operator, so instead of saying x = x + y, you can say x += y. If you want to have keyword-only arguments but have no need for a starred parameter, then simply use an empty star without using any name such as def total(initial=5, *, extra_number). 9.8 The return Statement The return statement is used to return from a function i.e. break out of the function. We can optionally return a value from the function as well. Example (save as func_return.py): def maximum(x, y): if x > y: return x elif x == y: return ‚The numbers are equal‚ else: return y print(maximum(2,3)) Output: $ python3 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 56 The pass statement is used in Python to indicate an empty block of statements. Note There is a built-in function called max that already implements the ‘find maximum’ functionality, so use this built-in function whenever possible. 9.9 DocStrings Python has a nifty feature called documentation strings, 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 program better and makes it easier to understand. Amazingly, we can even get the docstring back from, say a function, when the program is actually running! Example (save as 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: $ python3 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 letter and ends with a dot. Then the second line is 57 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 underscores) 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 help() in Python, then you have already seen the usage of docstrings! What it 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 the q key to exit 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. 9.10 Summary We have seen so many aspects of functions but note that we still haven’t covered all aspects of them. 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. 10 Modules 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. There are various methods of writing modules, but the simplest way is to create a file with a .py extension that contains functions and variables. Another method is to write the modules in the native language in which the Python interpreter itself was written. For example, you can write modules in the C programming language and when compiled, they can be used from your Python code when using the standard Python interpreter. 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. Example (save as using_sys.py): 58 import sys print(‚The command line arguments are:‚) for i in sys.argv: print(i) print(‚\n\nThe PYTHONPATH is‚, sys.path,‚\n‚) Output: $ python3 using_sys.py we are arguments The command line arguments are: using_sys.py we are arguments The PYTHONPATH is [’’, ’C:\\Windows\\system32\\python30.zip’, ’C:\\Python30\\DLLs’, ’C:\\Python30\\lib’, ’C:\\Python30\\lib\\plat-win’, ’C:\\Python30’, ’C:\\Python30\\lib\\site-packages’] How It Works: First, we import the sys module using the import statement. Basically, this translates to us telling Python that we want to use this module. The sys module contains functionality related to the Python interpreter and its environment i.e. the system. When Python executes the import sys statement, it looks for the sys module. In this case, it is one of the built-in modules, and hence Python knows where to find it. If it was not a compiled module i.e. a module written in Python, then the Python interpreter will search for it in the directories listed in its sys.path variable. If the module is found, then the statements in the body of that module are run and the module is made available for you to use. Note that the initialization is done only the first time that we import a module. The argv variable in the sys module is accessed using the dotted notation i.e. sys.argv. It clearly indicates that this name is part of the sys module. Another advantage of this approach is that the name does not clash with any argv variable used in your program. The sys.argv variable is a list of strings (lists are explained in detail in a later chapter). Specifically, the sys.argv contains the list of command line arguments i.e. the arguments passed to your program using the command line. 59 If you are using an IDE to write and run these programs, look for a way to specify command line arguments to the program in the menus. Here, when we execute python using_sys.py we are arguments, we run the module using_sys.py with the python command and the other things that follow are arguments passed to the program. Python stores the command line arguments in the sys.argv variable for us to use. 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 directly import modules located in the current directory. Otherwise, you will have to place your module in one of the directories listed in sys.path. Note that the current directory is the directory from which the program is launched. Run import os; print(os.getcwd()) to find out the current direc- tory of your program. 10.1 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 an intermediate form that Python transforms the program into (remember the introduction 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 a portion of the processing required in importing a module is already done. Also, these byte-compiled files are platform-independent. Note These .pyc files are usually created in the same directory as the corre- sponding .py files. If Python does not have permission to write to files in that directory, then the .pyc files will not be created. 10.2 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. In general, you should avoid using this statement and use the import statement instead since your program will avoid name clashes and will be more readable. Example: 60 from math import sqrt print("Square root of 16 is", sqrt(16)) 10.3 A module’s name Every module has a name and statements in a module can find out the name of their module. This is handy for the particular purpose of figuring out whether the module is being run standalone or being imported. As mentioned previously, when a module is imported for the first time, the code it contains gets executed. We can use this to make the module behave in different ways depending on whether it is being used by itself or being imported from another module. This can be achieved using the __name__ attribute of the module. Example (save as using_name.py): if __name__ == ‚__main__‚: print(‚This program is being run by itself‚) else: print(‚I am being imported from another module‚) Output: $ python3 using_name.py This program is being run by itself $ python3 >>> import using_name I am being imported from another module >>> How It Works: Every Python module has its __name__ defined. If this is ’__main__’, that implies that the module is being run standalone by the user and we can take appropriate actions. 10.4 Making Your Own Modules Creating your own modules is easy, you’ve been doing it all along! This is because every Python program is also a module. You just have to make sure it has a .py extension. The following example should make it clear. Example (save as mymodule.py): 61 def sayhi(): print(‚Hi, this is mymodule speaking.‚) __version__ = ‚0.1‚ The above was a sample module. As you can see, there is nothing particularly special about it 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 either in the same directory as the program from which we import it, or in one of the directories listed in sys.path. Another module (save as mymodule_demo.py): import mymodule mymodule.sayhi() print (‚Version‚, mymodule.__version__) Output: $ python3 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. Here is a version utilising the from..import syntax (save as mymodule_demo2.py): from mymodule import sayhi, __version__ sayhi() print(‚Version‚, __version__) The output of mymodule_demo2.py is same as the output of mymodule_demo.py. Notice that if there was already a __version__ name declared in the module that imports mymodule, there would be a clash. This is also likely because it is common practice for each module to declare it’s version number using this name. Hence, it is always recommended to prefer the import statement even though it might make your program a little longer. You could also use: 62 from mymodule import* This will import all public names such as sayhi but would not import __version__ because it starts with double underscores. Zen of Python One of Python’s guiding principles is that “Explicit is better than Implicit”. Run import this to learn more and see this StackOverflow discussion which lists examples for each of the principles. 10.5 The dir function You can use the built-in dir function to list the identifiers that an object defines. For example, for a module, the identifiers include the functions, classes and variables defined in that module. When you supply a module name to thedir() 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. Example: $ python3 >>> import sys # get list of attributes, in this case, for the sys module >>> dir(sys) [’__displayhook__’, ’__doc__’, ’__excepthook__’, ’__name__’, ’__package__’, ’__s tderr__’, ’__stdin__’, ’__stdout__’, ’_clear_type_cache’, ’_compact_freelists’, ’_current_frames’, ’_getframe’, ’api_version’, ’argv’, ’builtin_module_names’, ’ byteorder’, ’call_tracing’, ’callstats’, ’copyright’, ’displayhook’, ’dllhandle’ , ’dont_write_bytecode’, ’exc_info’, ’excepthook’, ’exec_prefix’, ’executable’, ’exit’, ’flags’, ’float_info’, ’getcheckinterval’, ’getdefaultencoding’, ’getfil esystemencoding’, ’getprofile’, ’getrecursionlimit’, ’getrefcount’, ’getsizeof’, ’gettrace’, ’getwindowsversion’, ’hexversion’, ’intern’, ’maxsize’, ’maxunicode ’, ’meta_path’, ’modules’, ’path’, ’path_hooks’, ’path_importer_cache’, ’platfor m’, ’prefix’, ’ps1’, ’ps2’, ’setcheckinterval’, ’setprofile’, ’setrecursionlimit ’, ’settrace’, ’stderr’, ’stdin’, ’stdout’, ’subversion’, ’version’, ’version_in fo’, ’warnoptions’, ’winver’] >>> dir() # get list of attributes for current module [’__builtins__’, ’__doc__’, ’__name__’, ’__package__’, ’sys’] >>> a = 5 # create a new variable ’a’ >>> dir() 63 [’__builtins__’, ’__doc__’, ’__name__’, ’__package__’, ’a’, ’sys’] >>> del a # delete/remove a name >>> dir() [’__builtins__’, ’__doc__’, ’__name__’, ’__package__’, ’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 contains. Next, we use the dir function without passing parameters to it. By default, it returns the list of attributes 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 dirand we observe that there is an additional value in the list of the same name. We remove the variable/attribute of the current module using the del statement and the change is reflected again in the output 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. Note that the dir() function works on any object. For example, run dir(’print’) to learn about the attributes of the print function, or dir(str) for the attributes of the str class. 10.6 Packages By now, you must have started observing the hierarchy of organizing your programs. Variables usually go inside functions. Functions and global variables usually go inside modules. What if you wanted to organize modules? That’s where packages come into the picture. Packages are just folders of modules with a special __init__.py file that indicates to Python that this folder is special because it contains Python modules. Let’s say you want to create a package called ‘world’ with subpackages ‘asia’, ‘africa’, etc. and these subpackages in turn contain modules like ‘india’, ‘mada- gascar’, etc. This is how you would structure the folders: 64 - / - world/ - __init__.py - asia/ - __init__.py - india/ - __init__.py - foo.py - africa/ - __init__.py - madagascar/ - __init__.py - bar.py Packages are just a convenience to hierarchically organize modules. You will see many instances of this in the standard library. 10.7 Summary Just like functions are reusable parts of programs, modules are reusable programs. Packages are another hierarchy to organize modules. The standard library that comes with Python is an example of such a set of packages and modules. We have seen how to use these modules and create our own modules. Next, we will learn about some interesting concepts called data structures. 11 Data Structures 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 four built-in data structures in Python - list, tuple, dictionary and set. We will see how to use each of them and how they make life easier for us. 11.1 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 probably have each item on a separate line in your shopping list whereas in Python you put commas in between them. The list of items should be enclosed in square brackets so that Python understands that you are specifying a list. Once you have created a list, you can add, remove 65 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. 11.1.1 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 explore this topic in detail in a later chapter. A list is an example of usage of objects and classes. When we use a variable i and assign a value to it, say integer 5 to it, you can think of it as creating an object (i.e. instance) i of class (i.e. type) int. In fact, you can read 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 example, mylist.append(’an item’) will add that string to the list mylist. Note the use of dotted 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 accessed by the dotted notation, for example, mylist.field. Example (save as using_list.py): # This is my shopping list shoplist = [‚apple‚, ‚mango‚, ‚carrot‚, ‚banana‚] print(‚I have‚, len(shoplist), ‚items to purchase.‚) print(‚These items are:‚, end=‚‚) for item in shoplist: print(item, end=‚‚) 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] 66 del shoplist[0] print(‚I bought the‚, olditem) print(‚My shopping list is now‚, shoplist) Output: $ python3 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 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 the use of the end keyword argument to the print function to indicate that we want to end the output with a space instead of the usual line break. 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 neatly. Then, we sort the list by using the sort method of the list. It is important to understand that this method affects the list 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 from the 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 details. 67 11.2 Tuple Tuples are used to hold together multiple objects. Think of them as similar to lists, but without the extensive functionality that the list class gives you. One major feature of tuples is that they are immutable like strings i.e. you cannot modify tuples. Tuples are defined by specifying items separated by commas within an optional 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. Example (save as using_tuple.py): zoo = (‚python‚, ‚elephant‚, ‚penguin‚)# remember the parentheses are optional print(‚Number of animals in the zoo is‚, len(zoo)) new_zoo = ‚monkey‚, ‚camel‚, zoo print(‚Number of cages 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]) print(‚Number of animals in the new zoo is‚, len(new_zoo)-1+len(new_zoo[2])) Output: $ python3 using_tuple.py Number of animals in the zoo is 3 Number of cages in the new zoo is 3 All animals in new zoo are (’monkey’, ’camel’, (’python’, ’elephant’, ’penguin’)) Animals brought from old zoo are (’python’, ’elephant’, ’penguin’) Last animal brought from old zoo is penguin Number of animals in the new zoo is 5 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. 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. 68 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 within the third item in the new_zoo tuple by specifying new_zoo[2][2]. This is pretty simple once you’ve understood the idiom. Parentheses Although the parentheses are optional, I prefer always having them to make it obvious that it is a tuple, especially because it avoids ambiguity. For example, print(1,2,3) and print( (1,2,3) ) mean two different things - the former prints three numbers whereas the latter prints a tuple (which contains three numbers). Tuple with 0 or 1 items An empty tuple is constructed by an empty pair of parentheses such as myempty = (). 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 applies to a tuple within a tuple, or a tuple within a list, or a list within a tuple, etc. As far as Python is concerned, they are just objects stored using another object, that’s all. 11.3 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 values are specified in a dictionary by using the notation d = {key1 : value1, key2 : value2 }. Notice that the key-value pairs are separated by a colon and the pairs are separated themselves by commas and all this is enclosed in a pair of curly braces. 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. 69 The dictionaries that you will be using are instances/objects of the dict class. Example (save as using_dict.py): # ‚ab‚ is short for ‚a‚ddress‚b‚ook ab = { ‚Swaroop‚: ‚swaroop@swaroopch.com‚, ‚Larry‚: ‚larry@wall.org‚, ‚Matsumoto‚: ‚matz@ruby-lang.org‚, ‚Spammer‚: ‚spammer@hotmail.com‚ } print("Swaroop‚s address is", ab[‚Swaroop‚]) # Deleting a key-value pair del ab[‚Spammer‚] print(‚\nThere are {0} contacts in the address-book\n‚.format(len(ab))) for name, address in ab.items(): print(‚Contact {0} at {1}‚.format(name, address)) # Adding a key-value pair ab[‚Guido‚] = ‚guido@python.org‚ if ‚Guido‚ in ab: print("\nGuido‚s address is", ab[‚Guido‚]) Output: $ python3 using_dict.py Swaroop’s address is swaroop@swaroopch.com There are 3 contacts in the address-book Contact Swaroop at swaroop@swaroopch.com Contact Matsumoto at matz@ruby-lang.org Contact Larry at larry@wall.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 the simple syntax. 70 We can delete key-value pairs using our old friend - the del statement. We simply specify the dictionary 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 retrieve 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 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 check if a key-value pair exists using the in operator. For the list of methods of the dict class, see help(dict). Keyword Arguments and Dictionaries On a different note, if you have used keyword arguments in your functions, you have already used dictio- naries! 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 tablein compiler design terminology). 11.4 Sequence Lists, tuples and strings are examples of sequences, but what are sequences and what is so special about them? The major features are membership tests, (i.e. the in and not in expressions) and indexing operations, which allow us to fetch a particular item in the sequence directly. The three types of sequences mentioned above - lists, tuples and strings, also have a slicing operation which allows us to retrieve a slice of the sequence i.e. a part of the sequence. Example (save as seq.py): shoplist = [‚apple‚, ‚mango‚, ‚carrot‚, ‚banana‚] name = ‚swaroop‚ # Indexing or ‚Subscription‚ operation print(‚Item 0 is‚, shoplist[0]) print(‚Item 1 is‚, shoplist[1]) print(‚Item 2 is‚, shoplist[2]) print(‚Item 3 is‚, shoplist[3]) 71 print(‚Item -1 is‚, shoplist[-1]) print(‚Item -2 is‚, shoplist[-2]) print(‚Character 0 is‚, name[0]) # 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 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: $ python3 seq.py Item 0 is apple Item 1 is mango Item 2 is carrot Item 3 is banana Item -1 is banana Item -2 is carrot Character 0 is s 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 subscription 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 Python starts counting numbers from 0. Hence, shoplist[0] fetches the first item and shoplist[3] fetches the fourth item in the shoplistsequence. 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. 72 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 similar to the indexing operation you have been using till now. 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 sequence 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. You can also provide a third argument for the slice, which is the step for the slicing (by default, the step size is 1): >>> shoplist = [’apple’, ’mango’, ’carrot’, ’banana’] >>> shoplist[::1] [’apple’, ’mango’, ’carrot’, ’banana’] >>> shoplist[::2] [’apple’, ’carrot’] >>> shoplist[::3] [’apple’, ’banana’] >>> shoplist[::-1] [’banana’, ’carrot’, ’mango’, ’apple’] Notice that when the step is 2, we get the items with position 0, 2, . . . When the step size is 3, we get the items with position 0, 3, etc. 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 access tuples, lists and strings all in the same way! 11.5 Set Sets are unordered collections of simple objects. These are used when the existence of an object in a collection is more important than the order or how many times it occurs. 73 Using sets, you can test for membership, whether it is a subset of another set, find the intersection between two sets, and so on. >>> bri = set([’brazil’, ’russia’, ’india’]) >>> ’india’ in bri True >>> ’usa’ in bri False >>> bric = bri.copy() >>> bric.add(’china’) >>> bric.issuperset(bri) True >>> bri.remove(’russia’) >>> bri & bric # OR bri.intersection(bric) {’brazil’, ’india’} How It Works: The example is pretty much self-explanatory because it involves basic set theory mathematics taught in school. 11.6 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 binding 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: Example (save as reference.py): print(‚Simple Assignment‚) shoplist = [‚apple‚, ‚mango‚, ‚carrot‚, ‚banana‚] 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 74 del mylist[0]# remove first item print(‚shoplist is‚, shoplist) print(‚mylist is‚, mylist) # notice that now the two lists are different Output: $ python3 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. Remember 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 be 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 slicing operation to make a copy of the sequence. 11.7 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). Example (save as str_methods.py): name = ‚Swaroop‚ # This is a string object if name.startswith(‚Swa‚): 75 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: $ python3 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 whether 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 locate the position of the given substring within the string; find returns -1 if it is unsuccessful in finding the substring. The str class also has a neat method to join the items of a sequence with the string acting as a delimiter between each item of the sequence and returns a bigger string generated from this. 11.8 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. 12 Problem Solving 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 idea is to learn how to write a Python script on your own. 76 12.1 The Problem The problem we want to solve 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 solution. A little more analysis is required. For example, how do we specify which files are to be backed up? How are they stored? Where are they stored? 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 analysis since every person has their own way of doing things, so that is perfectly okay. • The files and directories to be backed up are specified in a list. • The backup must be stored in a main backup directory. • The files are backed up into a zip file. • The name of the zip archive is the current date and time. • We use the standard zip command available by default in any standard Linux/Unix distribution. Windows users can install from the GnuWin32 project page and add C:\Program Files\GnuWin32\bin to your system PATH environment variable, similar to what we did for recognizing the python command itself. Note that you can use any archiving command you want as long as it has a command line 12.2 The Solution As the design of our program is now reasonably stable, we can write the code which is an implementation of our solution. Save as backup_ver1.py: import os import time # 1. The files and directories to be backed up are specified in a list. source = [‚"C:\\My Documents"‚, ‚C:\\Code‚] # Notice we had to use double quotes inside the string for names with spaces in it. # 2. The backup must be stored in a main backup directory target_dir = ‚E:\\Backup‚ # Remember to change this to what you will be using 77 # 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 + os.sep + time.strftime(‚%Y%m%d%H%M%S‚) + ‚.zip‚ # 5. We use the zip command to put the files in a zip archive zip_command = "zip -qr {0} {1}".format(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 E:\Backup\20080702185040.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. If the above program does not work for you, put a print(zip_command) just before the os.system call and run the program. Now copy/paste the printed zip_command to the shell prompt and see if it runs properly on its own. If this command fails, check the zip command manual on what could be wrong. If this command succeeds, then check the Python program if it exactly matches the program written above. 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 by first importing them. Then, we specify the files and directories to be backed up in the source list. The target directory is where we 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 generate using the time.strftime() function. It will also have the .zip extension and will be stored in the target_dir directory. Notice the use of the os.sep variable - this gives the directory separator according to your operating system i.e. it will be ’/’ in Linux and 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 all of these systems. 78 The time.strftime() function takes a specification such as the one we have used in the above program. The %Y specification will be replaced by the year with the century. 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. 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 in 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 all the subdirectories and files. The two options are combined and specified in a shortcut 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 error number. Depending on the outcome of the command, we print the appropriate message that the backup has failed or succeeded. That’s it, we have created a script to take a backup of our important files! Note to Windows Users Instead of double backslash escape sequences, you can also use raw strings. For example, use ’C:\\Documents’ or r’C:\Documents’. However, do not use ’C:\Documents’ since you end up 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 when typing the code, etc. Appropriately, you will have to go back to the design phase or you will have to debug your program. 79 12.3 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. The first advantage is that your backups are stored in a hierarchical manner and therefore it is much easier to manage. The second advantage is that the filenames are much shorter. The third advantage is that separate directories will help you check if you have made a backup for each day since the directory would be created only if you have made a backup for that day. Save as backup_ver2.py: import os import time # 1. The files and directories to be backed up are specified in a list. source = [‚"C:\\My Documents"‚, ‚C:\\Code‚] # Notice we had to use double quotes inside the string for names with spaces in it. # 2. The backup must be stored in a main backup directory target_dir = ‚E:\\Backup‚ # Remember to change this to what you will be using # 3. The files are backed up into a zip file. # 4. The current day is the name of the subdirectory in the main directory today = target_dir + os.sep + 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‚ # 5. We use the zip command to put the files in a zip archive zip_command = "zip -qr {0} {1}".format(target,‚‚.join(source)) # Run the backup if os.system(zip_command) ==0: print(‚Successful backup to‚, target) 80 else: print(‚Backup FAILED‚) Output: $ python3 backup_ver2.py Successfully created directory E:\Backup\20080702 Successful backup to E:\Backup\20080702\202311.zip $ python3 backup_ver2.py Successful backup to E:\Backup\20080702\202325.zip How It Works: Most of the program remains the same. The changes are that we check if there is a directory with the current day as its name inside the main backup directory using the os.path.exists function. If it doesn’t exist, we create it using the os.mkdir function. 12.4 Third Version The second version works fine when I do many backups, but when there are lots of backups, I am finding 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 the zip archive. This can be easily achieved by attaching a user-supplied comment to the name of the zip archive. Note The following program does not work, so do not be alarmed, please follow along because there’s a lesson in here. Save as backup_ver3.py: import os import time # 1. The files and directories to be backed up are specified in a list. source = [‚"C:\\My Documents"‚, ‚C:\\Code‚] # Notice we had to use double quotes inside the string for names with spaces in it. # 2. The backup must be stored in a main backup directory target_dir = ‚E:\\Backup‚ # Remember to change this to what you will be using # 3. The files are backed up into a zip file. 81 # 4. The current day is the name of the subdirectory in the main directory today = target_dir + os.sep + time.strftime(‚%Y%m%d‚) # The current time is the name of the zip archive now = time.strftime(‚%H%M%S‚) # Take a comment from the user to create the name of the zip file comment = input(‚Enter a comment --> ‚) if len(comment) ==0:# check if a comment was entered target = today + os.sep + now + ‚.zip‚ else: target = today + os.sep + now + ‚_‚+ comment.replace(‚‚, ‚_‚) + ‚.zip‚ # 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) # 5. We use the zip command to put the files in a zip archive zip_command = "zip -qr {0} {1}".format(target,‚‚.join(source)) # Run the backup if os.system(zip_command) ==0: print(‚Successful backup to‚, target) else: print(‚Backup FAILED‚) Output: $ python3 backup_ver3.py File "backup_ver3.py", line 25 target = today + os.sep + now + ’_’ + ^ SyntaxError: invalid syntax 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 addition operator (+) without any operand in that logical line and hence it doesn’t know how to continue. Remember 82 that we can specify that the logical line continues in the next physical line by the use of a backslash at the end of the physical line. So, we make this correction to our program. This correction of the program when we find errors is called bug fixing. 12.5 Fourth Version Save as backup_ver4.py: import os import time # 1. The files and directories to be backed up are specified in a list. source = [‚"C:\\My Documents"‚, ‚C:\\Code‚] # Notice we had to use double quotes inside the string for names with spaces in it. # 2. The backup must be stored in a main backup directory target_dir = ‚E:\\Backup‚ # Remember to change this to what you will be using # 3. The files are backed up into a zip file. # 4. The current day is the name of the subdirectory in the main directory today = target_dir + os.sep + time.strftime(‚%Y%m%d‚) # The current time is the name of the zip archive now = time.strftime(‚%H%M%S‚) # Take a comment from the user to create the name of the zip file comment = input(‚Enter a comment --> ‚) if len(comment) ==0:# check if a comment was entered target = today + os.sep + now + ‚.zip‚ else: target = today + os.sep + now + ‚_‚+\ comment.replace(‚‚, ‚_‚) + ‚.zip‚ # 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) # 5. We use the zip command to put the files in a zip archive zip_command = "zip -qr {0} {1}".format(target,‚‚.join(source)) # Run the backup if os.system(zip_command) ==0: print(‚Successful backup to‚, target) 83 else: print(‚Backup FAILED‚) Output: $ python3 backup_ver4.py Enter a comment --> added new examples Successful backup to E:\Backup\20080702\202836_added_new_examples.zip $ python3 backup_ver4.py Enter a comment --> Successful backup to E:\Backup\20080702\202839.zip 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 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 without entering anything (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 filenames without spaces is much easier. 12.6 More Refinements The fourth version is a satisfactorily working script for most users, but there is always room for improvement. 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 can get these names from the sys.argv list and we can add them to our source list using the extendmethod provided by the list class. The most important refinement would be to not use the os.system way of creating archives and instead using the zipfile or tarfile built-in module to create these archives. They are part of the standard library and available already for you to use without external dependencies on the zip program to be available on your computer. However, I have been using the os.system way of creating a backup in the above examples purely for pedagogical purposes, so that the example is simple enough to be understood by everybody but real enough to be useful. 84 Can you try writing the fifth version that uses the zipfile module instead of the os.system call? 12.7 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) 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. 12.8 Summary 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. 13 Object Oriented Programming In all the programs we wrote till now, we have designed our program around functions i.e. 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 something called an object. This is called the object oriented programming paradigm. Most of the time you can use procedural programming, but when 85 writing large programs or have a problem that is better suited to this method, you can use object oriented programming techniques. Classes and objects are the two main aspects 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 Static Language 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 details on the class. C# and Java 1.5 programmers will find this similar to the boxing and unboxing concept. Objects can store data using ordinary variables that belong to the object. Vari- ables that belong to an object or class are referred to 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 independent 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 indented block. 13.1 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 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 Development Environments) can help you if you use self. Note for C++/Java/C# Programmers The self in Python is equivalent to the this pointer in C++ and the this reference in Java and C#. 86 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 all the special self is about. This also means that if you have a method which takes no arguments, then you still have to have one argument - the self. 13.2 Classes The simplest class possible is shown in the following example (save as simplestclass.py). class Person: pass # An empty block p = Person() print(p) Output: $ python3 simplestclass.py <__main__.Person object at 0x019F85F0> How It Works: We create a new class using the class statement and the name of the class. This is followed by an indented 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 parentheses. (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. 87 13.3 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 (save as 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: $ python3 method.py Hello, how are you? How It Works: Here we see the self in action. Notice that the sayHi method takes no parame- ters but still has the self in the function definition. 13.4 The init method There are many method names which have special significance in Python classes. We will see the significance 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 underscores both at the beginning and at the end of the name. Example (save as 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() 88 Output: $ python3 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 are both called ‘name’. There is no problem because the dotted notation self.name means that there is something called “name” that is part of the object called “self” and the other name is a local variable. Since we explicitly indicate which name we are referring to, there is no confusion. 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. 13.5 Class And Object Variables We have already discussed the functionality part of classes and objects (i.e. meth- ods), now let us learn about the data part. The data part, i.e. fields, are nothing but ordinary variables that are bound to the namespaces of the classes and objects. This means that these names are valid within the context of these classes and objects only. That’s why they are called name spaces. 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 - they can be accessed by all instances of that class. There is only one copy of the class variable and when any one object makes a change to a class variable, that change will be seen by all the other instances. 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 same name in a different instance. An example will make this easy to understand (save as objvar.py): class Robot: ‚‚‚Represents a robot, with a name.‚‚‚ # A class variable, counting the number of robots 89 population =0 def __init__(self, name): ‚‚‚Initializes the data.‚‚‚ self.name = name print(‚(Initializing {0})‚.format(self.name)) # When this person is created, the robot # adds to the population Robot.population +=1 def __del__(self): ‚‚‚I am dying.‚‚‚ print(‚{0} is being destroyed!‚.format(self.name)) Robot.population -=1 if Robot.population ==0: print(‚{0} was the last one.‚.format(self.name)) else: print(‚There are still {0:d} robots working.‚.format(Robot.population)) def sayHi(self): ‚‚‚Greeting by the robot. Yeah, they can do that.‚‚‚ print(‚Greetings, my masters call me {0}.‚.format(self.name)) def howMany(): ‚‚‚Prints the current population.‚‚‚ print(‚We have {0:d} robots.‚.format(Robot.population)) howMany = staticmethod(howMany) droid1 = Robot(‚R2-D2‚) droid1.sayHi() Robot.howMany() droid2 = Robot(‚C-3PO‚) droid2.sayHi() Robot.howMany() print("\nRobots can do some work here.\n") print("Robots have finished their work. So let‚s destroy them.") del droid1 del droid2 90 Robot.howMany() Output: $ python3 objvar.py (Initializing R2-D2) Greetings, my masters call me R2-D2. We have 1 robots. (Initializing C-3PO) Greetings, my masters call me C-3PO. We have 2 robots. Robots can do some work here. Robots have finished their work. So let’s destroy them. R2-D2 is being destroyed! There are still 1 robots working. C-3PO is being destroyed! C-3PO was the last one. We have 0 robots. How It Works: This is a long example but helps demonstrate the nature of class and object variables. Here, population belongs to theRobot class and hence is a class variable. The name variable belongs to the object (it is assigned using self) and hence is an object variable. Thus, we refer to the population class variable as Robot.population and not as self.population. 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. Also note that an object variable with the same name as a class variable will hide the class variable! The howMany is actually a method that belongs to the class and not to the object. This means we can define it as either a classmethod or a staticmethod depending on whether we need to know which class we are part of. Since we don’t need such information, we will go for staticmethod . We could have also achieved the same using decorators: @staticmethod def howMany(): ‚‚‚Prints the current population.‚‚‚ print(‚We have {0:d} robots.‚.format(Robot.population)) 91 Decorators can be imagined to be a shortcut to calling an explicit statement, as we have seen in this example. Observe that the __init__ method is used to initialize the Robot instance with a name. In this method, we increase the population count by 1 since we have one more robot 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 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 Robot.__doc__ and the method docstring as Robot.sayHi.__doc__ Just like the __init__ method, there is another special method __del__ which is called when an object is going to die i.e. it is no longer being used and is being returned to the computer system for reusing that piece of memory. In this method, we simply decrease the Robot.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 see it in action, we have to use the del statement which is what we have done here. All class members are public. 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 object 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). Note for C++/Java/C# Programmers All class members (including the data members) are public and all the methods are virtual in Python. 13.6 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 characteristics such as salary, courses and leaves for teachers and, marks and fees for students. 92 You can create two independent classes for each type and process them but adding a new common characteristic 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 subtypes do not affect other subtypes. Another advantage is that if you can refer to a teacher or student object as a SchoolMember object which could be useful in some situations such as counting of the number of school members. This is called polymorphism where a sub-type can be substituted in any situation 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 (save as inherit.py): class SchoolMember: ‚‚‚Represents any school member.‚‚‚ def __init__(self, name, age): self.name = name self.age = age print(‚(Initialized SchoolMember: {0})‚.format(self.name)) def tell(self): ‚‚‚Tell my details.‚‚‚ print(‚Name:"{0}" Age:"{1}"‚.format(self.name, self.age), end="") class Teacher(SchoolMember): ‚‚‚Represents a teacher.‚‚‚ def __init__(self, name, age, salary): SchoolMember.__init__(self, name, age) self.salary = salary print(‚(Initialized Teacher: {0})‚.format(self.name)) 93 def tell(self): SchoolMember.tell(self) print(‚Salary: "{0:d}"‚.format(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: {0})‚.format(self.name)) def tell(self): SchoolMember.tell(self) print(‚Marks: "{0:d}"‚.format(self.marks)) t = Teacher(‚Mrs. Shrividya‚, 40, 30000) s = Student(‚Swaroop‚, 25, 75) print() # prints a blank line members = [t, s] for member in members: member.tell() # works for both Teachers and Students Output: $ python3 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:"25" Marks: "75" How It Works: 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 remember - 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. 94 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 SchoolMember class. One way to understand this is that Python always starts looking for methods in the actual 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. The end parameter is used in the tell() method to change a new line to be started at the end of the print() call to printing spaces. 13.7 Summary We have now explored the various aspects of classes and objects as well as the various terminologies associated 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. 14 Input Output There will be situations where your program has to interact with the user. For example, you would want to take input from the user and then print some results back. We can achieve this using the input() and print() functions 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. 14.1 Input from user Save this program as user_input.py: 95 def reverse(text): return text[::-1] def is_palindrome(text): return text == reverse(text) something = input(‚Enter text: ‚) if (is_palindrome(something)): print("Yes, it is a palindrome") else: print("No, it is not a palindrome") Output: $ python3 user_input.py Enter text: sir No, it is not a palindrome $ python3 user_input.py Enter text: madam Yes, it is a palindrome $ python3 user_input.py Enter text: racecar Yes, it is a palindrome How It Works: We use the slicing feature to reverse the text. We’ve already seen how we can make slices from sequences using the seq[a:b] code starting from position a to position b. We can also provide a third argument that determines the step by which the slicing is done. The default step is 1 because of which it returns a continuous part of the text. Giving a negative step, i.e., -1 will return the text in reverse. The input() function takes a string as argument and displays it to the user. Then it waits for the user to type something and press the return key. Once the user has entered and pressed the return key, the input() function will then return that text the user has entered. We take that text and reverse it. If the original text and reversed text are equal, then the text is a palindrome. Homework exercise Checking whether a text is a palindrome should also ignore punctuation, spaces and case. For example, “Rise to vote, sir.” is also a palindrome but our current program doesn’t say it is. Can you improve the above program to recognize this palindrome? 96 Hint (Don’t read) below Use a tuple (you can find a list of all punctuation marks here punctuation) to hold all the forbidden characters, then use the membership test to determine whether a character should be removed or not, i.e. forbidden = (’!’, ’?’, ’.’, . . . ). 14.2 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. Example (save as using_file.py): poem = ‚‚‚\ Programming is fun When the work is done if you wanna make your work also fun: use Python! ‚‚‚ f = open(‚poem.txt‚, ‚w‚)# open for ‚w‚riting f.write(poem) # write text to file f.close() # close the file f = open(‚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, end=‚‚) f.close() # close the file Output: $ python3 using_file.py Programming is fun When the work is done if you wanna make your work also fun: use Python! 97 How It Works: First, open a file by using the built-in open function and 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’). We can also specify whether we are reading, writing, or appending in text mode (’t’) or binary mode (’b’). There are actually many more modes available and help(open) will give you more details about them. By default, open() considers the file to be a ’t’ext file and opens it in ’r’ead mode. In our example, we first open the file in write text mode and use the write method of the file object to write to the file and then we finally close the file. Next, we open the same file again for reading. We don’t need to specify a mode because ‘read text file’ is the default mode. 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. When an empty string is returned, it means that we have reached the end of the file and we ‘break’ out of the loop. By default, the print() function prints the text as well as an automatic newline to the screen. We are suppressing the newline by specifying end=” because the line that is read from the file already ends with a newline character. Then, we finally closethe file. Now, check the contents of the poem.txt file to confirm that the program has indeed written to and read from that file. 14.3 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. This is called storing the object persistently. Example (save as pickling.py): import pickle # the name of the file where we will store the object shoplistfile = ‚shoplist.data‚ # the list of things to buy shoplist = [‚apple‚, ‚mango‚, ‚carrot‚] # Write to the file f = open(shoplistfile, ‚wb‚) pickle.dump(shoplist, f) # dump the object to a file f.close() del shoplist # destroy the shoplist variable 98 # Read back from the storage f = open(shoplistfile, ‚rb‚) storedlist = pickle.load(f) # load the object from the file print(storedlist) Output: $ python3 pickling.py [’apple’, ’mango’, ’carrot’] How It Works: To store an object in a file, we have to first open the file in ’w’rite ’b’inary mode and then call the dump function of thepickle 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. 14.4 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. 15 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 program was running? Such situations are handled using exceptions. Similarly, what if your program had some invalid statements? This is handled by Python which raises its hands and tells you there is an error. 15.1 Errors Consider a simple print function call. What if we misspelt print as Print? Note the capitalization. In this case, Python raises a syntax error. 99 >>> Print(’Hello World’) Traceback (most recent call last): File "", line 1, in Print(’Hello World’) NameError: name ’Print’ is not defined >>> print(’Hello World’) Hello World Observe that a NameError is raised and also the location where the error was detected is printed. This is what an error handler for this error does. 15.2 Exceptions We will try to read input from the user. Press ctrl-d and see what happens. >>> s = input(’Enter something --> ’) Enter something --> Traceback (most recent call last): File "", line 1, in s = input(’Enter something --> ’) EOFError: EOF when reading a line Python raises an error called EOFError which basically means it found an end of file symbol (which is represented by ctrl-d) when it did not expect to see it. 15.3 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. Example (save as try_except.py): try: text = input(‚Enter something --> ‚) except EOFError: print(‚Why did you do an EOF on me?‚) except KeyboardInterrupt: print(‚You cancelled the operation.‚) else: print(‚You entered {0}‚.format(text)) Output: 100 $ python3 try_except.py Enter something --> # Press ctrl-d Why did you do an EOF on me? $ python3 try_except.py Enter something --> # Press ctrl-c You cancelled the operation. $ python3 try_except.py Enter something --> no exceptions You entered no exceptions How It Works: We put all the statements that might raise exceptions/errors inside the try block and then put handlers for the appropriate errors/exceptions in the except clause/block. The except clause can handle a single specified error or exception, or a parenthesized list of errors/exceptions. If no names of errors or exceptions are supplied, it will handle all errors and exceptions. Note that there has to be at least one except clause associated with every try clause. Otherwise, what’s the point of having a try block? If any error or exception is not handled, then the default Python handler is called which just stops the execution of the program and prints an error message. We have already seen this in action above. You can also have an else clause associated with a try..except block. The else clause is executed if no exception occurs. In the next example, we will also see how to get the exception object so that we can retrieve additional information. 15.4 Raising Exceptions You can raise exceptions using the raise statement by providing the name of the error/exception and the exception object that is to be thrown. The error or exception that you can raise should be a class which directly or indirectly must be a derived class of the Exception class. Example (save as raising.py): class ShortInputException(Exception): ‚‚‚A user-defined exception class.‚‚‚ def __init__(self, length, atleast): Exception.__init__(self) self.length = length 101 self.atleast = atleast try: text = input(‚Enter something --> ‚) if len(text) <3: raise ShortInputException(len(text),3) # Other work can continue as usual here except EOFError: print(‚Why did you do an EOF on me?‚) except ShortInputException as ex: print(‚ShortInputException: The input was {0} long, expected at least {1}‚\ .format(ex.length, ex.atleast)) else: print(‚No exception was raised.‚) Output: $ python3 raising.py Enter something --> a ShortInputException: The input was 1 long, expected at least 3 $ python3 raising.py Enter something --> abc No exception was raised. How It Works: Here, we are creating our own exception type. This new exception type is called ShortInputException. 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 which will be stored as the variable name to hold the corresponding error/exception object. This is analogous to parameters and arguments in a function call. Within this particular except clause, we use thelength and atleast fields of the exception object to print an appropriate message to the user. 15.5 Try .. Finally Suppose you are reading a file in your program. How do you ensure that the file object is closed properly 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 finally block for the same corresponding try block. You will have to embed one within another if you want to use both. Save as finally.py: 102 import time try: f = open(‚poem.txt‚) while True:# our usual file-reading idiom line = f.readline() if len(line) ==0: break print(line, end=‚‚) time.sleep(2)# To make sure it runs for a while except KeyboardInterrupt: print(‚!! You cancelled the reading from the file.‚) finally: f.close() print(‚(Cleaning up: Closed the file)‚) Output: $ python3 finally.py Programming is fun When the work is done if you wanna make your work also fun: !! You cancelled the reading from the file. (Cleaning up: Closed the file) How It Works: We do the usual file-reading stuff, but we have arbitrarily introduced sleeping for 2 seconds after printing each line using the time.sleep function 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 the KeyboardInterrupt exception is thrown and the program quits. However, before the program exits, the finally clause is executed and the file object is always closed. 15.6 The with statement Acquiring a resource in the try block and subsequently releasing the resource in the finally block is a common pattern. Hence, there is also a with statement that enables this to be done in a clean manner: Save as using_with.py: with open("poem.txt") as f: for line in f: print(line, end=‚‚) 103 How It Works: The output should be same as the previous example. The difference here is that we are using the open function with the with statement - we leave the closing of the file to be done automatically by with open. What happens behind the scenes is that there is a protocol used by the with statement. It fetches the object returned by the open statement, let’s call it “thefile” in this case. It always calls the thefile.__enter__ function before starting the block of code under it and always calls thefile.__exit__ after finishing the block of code. So the code that we would have written in a finally block should be taken care of automatically by the __exit__method. This is what helps us to avoid having to use explicit try..finally statements repeatedly. More discussion on this topic is beyond scope of this book, so please refer PEP 343 for a comprehensive explanation. 15.7 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. 16 Standard Library The Python Standard Library contains a huge number of useful modules and is part of every standard Python installation. It is important to become familiar with the Python Standard Library since many problems can be solved quickly if you are familiar with the range of things that these libraries can do. 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 of the documentation that comes with your Python installation. Let us explore a few useful modules. Note If you find the topics in this chapter too advanced, you may skip this chapter. However, I highly recommend coming back to this chapter when you are more comfortable with programming using Python. 104 16.1 sys module The sys module contains system-specific functionality. We have already seen that the sys.argv list contains the command-line arguments. Suppose we want to check the version of the Python command being used so that, say, we want to ensure that we are using at least version 3. The sys module gives us such functionality. $ python3 >>> import sys >>> sys.version_info sys.version_info(major=3, minor=3, micro=0, releaselevel=’final’, serial=0) >>> sys.version_info.major >= 3 True How It Works: The sys module has a version_info tuple that gives us the version information. The first entry is the major version. We can check this to, for example, ensure the program runs only under Python 3.0: Save as versioncheck.py: import sys, warnings if sys.version_info.major <3: warnings.warn("Need Python 3.0 for this program to run", RuntimeWarning) else: print(‚Proceed as normal‚) Output: $ python2.7 versioncheck.py versioncheck.py:6: RuntimeWarning: Need Python 3.0 for this program to run RuntimeWarning) $ python3 versioncheck.py Proceed as normal How It Works: We use another module from the standard library called warnings that is used to display warnings to the end-user. If the Python version number is not at least 3, we display a corresponding warning. 105 16.2 logging module What if you wanted to have some debugging messages or important messages to be stored somewhere so that you can check whether your program has been running as you would expect it? How do you “store somewhere” these messages? This can be achieved using the logging module. Save as use_logging.py: import os, platform, logging if platform.platform().startswith(‚Windows‚): logging_file = os.path.join(os.getenv(‚HOMEDRIVE‚), os.getenv(‚HOMEPATH‚), ‚test.log‚) else: logging_file = os.path.join(os.getenv(‚HOME‚), ‚test.log‚) print("Logging to", logging_file) logging.basicConfig( level=logging.DEBUG, format=‚%(asctime)s: %(levelname)s: %(message)s‚, filename = logging_file, filemode = ‚w‚, ) logging.debug("Start of the program") logging.info("Doing something") logging.warning("Dying now") Output: $ python3 use_logging.py Logging to C:\Users\swaroop\test.log If we check the contents of test.log, it will look something like this: 2012-10-26 16:52:41,339 : DEBUG : Start of the program 2012-10-26 16:52:41,339 : INFO : Doing something 2012-10-26 16:52:41,339 : WARNING : Dying now How It Works: We use three modules from the standard library - the os module for interacting with the operating system, the platform module for information about the platform i.e. the operating system and the logging module to log information. 106 First, we check which operating system we are using by checking the string re- turned by platform.platform() (for more information, see import platform; help(platform)). If it is Windows, we figure out the home drive, the home folder and the filename where we want to store the information. Putting these three parts together, we get the full location of the file. For other platforms, we need to know just the home folder of the user and we get the full location of the file. We use the os.path.join() function to put these three parts of the location together. The reason to use a special function rather than just adding the strings together is because this function will ensure the full location matches the format expected by the operating system. We configure the logging module to write all the messages in a particular format to the file we have specified. Finally, we can put messages that are either meant for debugging, information, warning or even critical messages. Once the program has run, we can check this file and we will know what happened in the program, even though no information was displayed to the user running the program. 16.3 Module of the Week Series There is much more to be explored in the standard library such as debugging, handling command line options, regular expressions and so on. The best way to further explore the standard library is to read Doug Hellmann’s excellent Python Module of the Week series or reading the Python documentation. 16.4 Summary We have explored some of the functionality of many modules in the Python Standard Library. It is highly recommended to browse through the Python Standard Library documentation to get an idea of all the modules that are available. Next, we will cover various aspects of Python that will make our tour of Python more complete. 17 More So far we have covered a 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 well-rounded. 107 17.1 Passing tuples around Ever wished you could return two different values from a function? You can. All you have to do is use a tuple. >>> def get_error_details(): ... return (2, ’second error details’) ... >>> errnum, errstr = get_error_details() >>> errnum 2 >>> errstr ’second error details’ Notice that the usage of a, b = interprets the result of the expression as a tuple with two values. If you want to interpret the results as (a, ), then you just need to star it just like you would in function parameters: >>> a, *b = [1, 2, 3, 4] >>> a 1 >>> b [2, 3, 4] This also means the fastest way to swap two variables in Python is: >>> a = 5; b = 8 >>> a, b = b, a >>> a, b (8, 5) 17.2 Special Methods There are certain methods such as the __init__ and __del__ methods which have special significance in classes. Special methods are used to mimic certain behaviors of built-in types. For example, if you want to use the x[key] indexing operation for your class (just like you use it for lists and tuples), then all you have to do is 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, see the manual. 108 __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 function or when str()is used. __lt__(self, other) Called when the less than operator (<) is used. Similarly, there are special methods for all the operators (+, >, 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. 17.3 Single Statement Blocks We have seen that each block of statements is set apart from the rest by its own indentation level. Well, there is one caveat. If your block of statements contains only one single statement, then you can specify it on the same line of, say, a conditional statement or looping statement. The following example should make this clear: >>> flag = True >>> if flag: print(’Yes’) Yes Notice that the single statement is used in-place and not as a separate block. Al- though, you can use this for making your program smaller, I strongly recommend avoiding this short-cut method, except for error checking, mainly because it will be much easier to add an extra statement if you are using proper indentation. 17.4 Lambda Forms A lambda statement is used to create new function objects. Essentially, the lambda takes a parameter followed by a single expression only which becomes the body of the function and the value of this expression is returned by the new function. Example (save as lambda.py): points = [ { ‚x‚:2, ‚y‚:3},{ ‚x‚:4, ‚y‚:1}] points.sort(key=lambda i : i[‚y‚]) print(points) Output: 109 [{’x’: 4, ’y’: 1}, {’x’: 2, ’y’: 3}] How It Works: Notice that the sort method of a list can take a key parameter which deter- mines how the list is sorted (usually we know only about ascending or descending order). In our case, we want to do a custom sort, and for that we need to write a function but instead of writing a separate def block for a function that will get used in only this one place, we use a lambda expression to create a new function. 17.5 List Comprehension List comprehensions are used to derive a new list from an existing list. Suppose you have a list of numbers and you want to get a corresponding list with all the numbers multiplied by 2 only when the number itself is greater than 2. List comprehensions are ideal for such situations. Example (save as list_comprehension.py): listone = [2,3,4] listtwo = [2*i for i in listone if i >2] print(listtwo) Output: $ python3 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 satisfied (if i > 2). Note that the original list remains unmodified. The advantage of using list comprehensions is that it reduces the amount of boilerplate code required when we use loops to process each element of a list and store it in a new list. 17.6 Receiving Tuples and Dictionaries 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. 110 >>> 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 Because we have a * 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. 17.7 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 AssertionError is raised. >>> mylist = [’item’] >>> assert len(mylist) >= 1 >>> mylist.pop() ’item’ >>> mylist [] >>> assert len(mylist) >= 1 Traceback (most recent call last): File "", line 1, in AssertionError The assert statement should be used judiciously. Most of the time, it is better to catch exceptions, either handle the problem or display an error message to the user and then quit. 17.8 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 111 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 for using 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 previously 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 line\nThis 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 sentence." 17.8.1 Raw String 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". Note for Regular Expression Users Always use raw strings when dealing with regular expressions. Otherwise, a lot of backwhacking may be required. For example, backreferences can be referred to as ’\\1’ or r’\1’. 17.9 Summary We have covered some more features of Python in this chapter and yet 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. 112 18 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 using which you can browse, 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 retrieval. 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 (Don’t read without trying first) Create a class to represent the per- son’s information. Use a dictionary to store person objects with their name as the key. Use the pickle module to store the objects persistently on your hard disk. Use the dictionary built-in methods to add, delete and modify the persons. Once you are able to do this, you can claim to be a Python programmer. Now, immediately send me an email thanking me for this great book ;-). This step is optional but recommended. Also, please consider buying a printed copy to support the continued development of this book. If you found that program easy, here’s another one: Implement the replace command. This command will replace one string with another in the list of files provided. The replace command can be as simple or as sophisticated as you wish, from simple string substitution to looking for patterns (regular expressions). After that, below are some ways to continue your journey with Python: 18.1 Example Code The best way to learn a programming language is to write a lot of code and read a lot of code: 113 • 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. • Python Module of the Week is another excellent must-read guide to the Python Standard Library. 18.2 Questions and Answers • Official Python Dos and Don’ts • Official Python FAQ • Norvig’s list of Infrequently Asked Questions • Python Interview Q & A • StackOverflow questions tagged with python 18.3 Tutorials • Awaretek’s comprehensive list of Python tutorials 18.4 Videos • PyVideo 18.5 Discussion If you are stuck with a Python problem, and don’t know whom to ask, then the python-tutor list is the best place to ask your question. Make sure you do your homework and have tried solving the problem yourself first. 18.6 News If you want to learn what is the latest in the world of Python, then follow the Official Python Planet. 18.7 Installing libraries There are a huge number of open source libraries at the Python Package Index which you can use in your own programs. To install and use these libraries, you can use pip. 114 18.8 Graphical Software Suppose you want to create your own graphical programs using Python. This can be done using a GUI (Graphical User Interface) library with their Python 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: Kivy http://kivy.org PyGTK This is the Python binding for the GTK+ toolkit which is the foun- dation 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+. To get started, read the PyGTK tutorial. 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 amazing Qt documentation. PyQt is free if you want to create open source (GPL’ed) software and you need to buy it if you want to create proprietary closed source software. Starting with Qt 4.5 you can use it to create non-GPL software as well. To get started, read the PyQt tutorial or the PyQt book. 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 embedded platforms. There are many IDEs available for wxPython which include GUI designers as well such as SPE (Stani’s Python Editor) and the wxGlade GUI builder. You can create free as well as proprietary software using wxPython. To get started, read the wxPython tutorial. 18.8.1 Summary of GUI Tools For more choices, see the GuiProgramming wiki page at the official python website. 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 only on Windows or on Mac and Linux or all of them. The third factor, if Linux is a chosen platform, is whether you are a KDE or GNOME user on Linux. 115 For a more detailed and comprehensive analysis, see Page 26 of the The Python Papers, Volume 3, Issue 1. 18.9 Various Implementations There are usually two parts a programming language - the language and the software. A language is how you write something. The software is what actually runs our programs. We have been using the CPython software to run our programs. It is referred to as CPython because it is written in the C language and is the Classical Python interpreter. There are also other software that can run your Python programs: Jython A Python implementation that runs on the Java platform. This means you can use Java libraries and classes from within Python language and vice-versa. IronPython A Python implementation that runs on the .NET platform. This means you can use .NET libraries and classes from within Python language and vice-versa. PyPy A Python implementation written in Python! This is a research project to make it fast and easy to improve the interpreter since the interpreter itself is written in a dynamic language (as opposed to static languages such as C, Java or C# in the above three implementations) Stackless Python A Python implementation that is specialized for thread- based performance. There are also others such as CLPython - a Python implementation written in Common Lisp and IronMonkey which is a port of IronPython to work on top of a JavaScript interpreter which could mean that you can use Python (instead of JavaScript) to write your web-browser (“Ajax”) programs. Each of these implementations have their specialized areas where they are useful. 18.10 Functional Programming (for advanced readers) When you start writing larger programs, you should definitely learn more about a functional approach to programming as opposed to the class-based approach to programming that we learned in the object-oriented programming chapter: • Functional Programming Howto by A.M. Kuchling • Functional programming chapter in ‘Dive Into Python’ book • Functional Programming with Python presentation 116 18.11 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! 19 FLOSS Free/Libre and Open Source Software, in short, FLOSS is based on the concept of a community, which itself is based on the concept of sharing, and particularly the sharing of knowledge. FLOSS are free for usage, modification and redistribution. If you have already read this book, then you are already familiar with FLOSS since you have been using Python all along and Python is an open source software! Here are some examples of FLOSS to give an idea of the kind of things that community sharing and building can create: Linux This is a FLOSS OS kernel used in the GNU/Linux operating system. Linux, the kernel, was started by Linus Torvalds as a student. Android is based on Linux. Any website you use these days will mostly be running on Linux. Ubuntu This is a community-driven distribution, sponsored by Canonical and it is the most popular Linux distribution today. It allows you to install a plethora of FLOSS available and all this in an easy-to-use and easy-to- install manner. Best of all, you can just reboot your computer and run GNU/Linux off the CD! This allows you to completely try out the new OS before installing it on your computer. However, Ubuntu is not entirely free software; it contains proprietary drivers, firmware, and applications. LibreOffice This is an excellent community-driven and developed office suite with a 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 and is entirely free, libre and open source software. Mozilla Firefox This is the best web browser. It is blazingly fast and has gained critical acclaim for its sensible and impressive features. The extensions concept allows any kind of plugins to be used. Its companion product Thunderbird is an excellent email client that makes reading email a snap. 117 Mono This is an open source implementation of the Microsoft .NET platform. It allows .NET applications to be created and run on GNU/Linux, Windows, FreeBSD, Mac OS and many other platforms as well. 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 more than half of the websites out there. Yes, that’s right - Apache handles more websites than all the competition (including Microsoft IIS) combined. VLC Player 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? ;-) 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 database server, TORCS racing game, KDevelop IDE, Xine - the movie player, VIM editor, Quanta+ editor, Banshee audio player, GIMP image editing program, . . . This list could go on forever. To get the latest buzz in the FLOSS world, check out the following websites: • linux.com • LinuxToday • NewsForge • DistroWatch Visit the following websites for more information on FLOSS: • GitHub Explore • OMG! Ubuntu! • SourceForge • FreshMeat So, go ahead and explore the vast, free and open world of FLOSS! 20 Colophon Almost all of the software that I have used in the creation of this book are FLOSS. 118 20.1 Birth of the Book In the first draft of this book, I had used Red Hat 9.0 Linux as the foundation of my setup and in the sixth draft, I used 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). 20.2 Teenage Years 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 the sixth draft, I decided to use Quanta+ to do all the editing. The standard XSL stylesheets that came with Fedora Core 3 Linux were being used. However, I had written a CSS document to give color and style to the HTML pages. I had also written a crude lexical analyzer, in Python of course, which automatically provides syntax highlighting to all the program listings. For this seventh draft, I’m using MediaWiki as the basis of my setup. Now I edit everything online and the readers can directly read/edit/discuss within the wiki website. I used Vim for editing thanks to the ViewSourceWith extension for Firefox that integrates with Vim. 20.3 Now Using Vim, Pandoc, and Mac OS X. 20.4 About The Author http://www.swaroopch.com/about/ 21 Revision History • 2.0 – 20 Oct 2012 119 – Rewritten in Pandoc format, thanks to my wife who did most of the conversion from the Mediawiki format – Simplifying text, removing non-essential sections such as nonlocal and metaclasses • 1.90 – 04 Sep 2008 and still in progress – Revival after a gap of 3.5 years! – Rewriting for Python 3.0 – Rewrite using MediaWiki (again) • 1.20 – 13 Jan 2005 – Complete rewrite using Quanta+ on Fedora Core 3 with lot of correc- tions and updates. Many new examples. Rewrote my DocBook setup from scratch. • 1.15 – 28 Mar 2004 – Minor revisions • 1.12 – 16 Mar 2004 – Additions and corrections. • 1.10 – 09 Mar 2004 – More typo corrections, thanks to many enthusiastic and helpful read- ers. • 1.00 – 08 Mar 2004 – After tremendous feedback and suggestions from readers, I have made significant revisions to the content along with typo corrections. • 0.99 – 22 Feb 2004 – Added a new chapter on modules. Added details about variable number of arguments in functions. 120 • 0.98 – 16 Feb 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. • 0.97 – 13 Feb 2004 – Another completely rewritten draft, in DocBook XML (again). Book has improved a lot - it is more coherent and readable. • 0.93 – 25 Jan 2004 – Added IDLE talk and more Windows-specific stuff • 0.92 – 05 Jan 2004 – Changes to few examples. • 0.91 – 30 Dec 2003 – Corrected typos. Improvised many topics. • 0.90 – 18 Dec 2003 – Added 2 more chapters. OpenOffice format with revisions. • 0.60 – 21 Nov 2003 – Fully rewritten and expanded. • 0.20 – 20 Nov 2003 – Corrected some typos and errors. • 0.15 – 20 Nov 2003 – Converted to DocBook XML with XEmacs. • 0.10 – 14 Nov 2003 – Initial draft using KWord. 121 22 Translations There are many translations of the book available in different human languages, thanks to many tireless volunteers! If you want to help with these translations, please see the list of volunteers and languages below and decide if you want to start a new translation or help in existing translation projects. If you plan to start a new translation, please read the Translation Howto. 22.1 Arabic Below is the link for the Arabic version. Thanks to Ashraf Ali Khalaf for translating the book, you can read the whole book online here or you can download it from sourceforge.net for more info click here. 22.2 Brazilian Portuguese There are two translations: Samuel Dias Neto (samuel.arataca-at-gmail-dot-com) made the first Brazilian Portuguese translation of this book when Python was in 2.3.5 version. Samuel’s translation is available at aprendendopython. Rodrigo Amaral (rodrigoamaral-at-gmail-dot-com) has volunteered to translate the book to Brazilian Portuguese. Rodrigo’s translation is available at http://www.swaroopch.org/notes/Python_pt- br:Indice. 22.3 Catalan Moises Gomez (moisesgomezgiron-at-gmail-dot-com) has volunteered to translate the book to Catalan. The translation is in progress, and was present in the erstwhile wiki. Moisès Gómez - I am a developer and also a teacher of programming (normally for people without any previous experience). Some time ago I needed to learn how to program in Python, and Swaroop’s work was really helpful. Clear, concise, and complete enough. Just what I needed. After this experience, I thought some other people in my country could take benefit from it too. But English language can be a barrier. 122 So, why not try to translate it? And I did for a previous version of BoP. I my country there are two official languages. I selected the Catalan language assuming that others will translate it to the more widespread Spanish. 22.4 Chinese Here’s a Chinese version at http://www.swaroopch.org/notes/Python_cn:Table_of_Contents. Juan Shen (orion-underscore-val-at-163-dot-com) has volunteered to translate the book to Chinese. It is available at http://www.pycn.org/python%E5%9C%A8%E7%BA%BF%E6%89%8B%E5%86%8C. I am a postgraduate at Wireless Telecommunication Graduate School, Beijing University of Technology, China PR. My current research interest is on the synchronization, channel estimation and multi- user detection of multicarrier CDMA system. Python is my major programming language for daily simulation and research job, with the help of Python Numeric, actually. I learned Python just half a year before, but as you can see, it’s really easy-understanding, easy- to-use and productive. Just as what is ensured in Swaroop’s book, ‘It’s my favorite programming language now’. ‘A Byte of Python’ is my tutorial to learn Python. It’s clear and effective to lead you into a world of Python in the shortest time. It’s not too long, but efficiently covers almost all important things in Python. I think ‘A Byte of Python’ should be strongly recommendable for newbies as their first Python tutorial. Just dedicate my translation to the potential millions of Python users in China. 22.5 Chinese Traditional Fred Lin (gasolin-at-gmail-dot-com) has volunteered to translate the book to Chinese Traditional. It is available at http://code.google.com/p/zhpy/wiki/ByteOfZhpy. An exciting feature of this translation is that it also contains the executable chinese python sources side by side with the original python sources. Fred Lin - I’m working as a network firmware engineer at Delta Network, and I’m also a contributor of TurboGears web framework. As a python evangelist (:-p), I need some material to promote python language. I found ‘A Byte of Python’ hit the sweet point for both newbies and experienced programmers. ‘A Byte of Python’ elaborates the python essentials with affordable size. 123 The translation are originally based on simplified chinese version, and soon a lot of rewrite were made to fit the current wiki version and the quality of reading. The recent chinese traditional version also featured with executable chinese python sources, which are achieved by my new ‘zhpy’ (python in chinese) project (launch from Aug 07). zhpy(pronounce (Z.H.?, or zippy) build a layer upon python to translate or interact with python in chinese(Traditional or Simplified). This project is mainly aimed for education. 22.6 French Gregory (coulix-at-ozforces-dot-com-dot-au) has volunteered to translate the book to French. Gérard Labadie (Palmipede) has completed to translate the book to French, it starts with http://www.swaroopch.org/notes/Python_fr:Table_des_Mati%C3%A8res. 22.7 German Lutz Horn (lutz-dot-horn-at-gmx-dot-de), Bernd Hengelein (bernd-dot-hengelein- at-gmail-dot-com) and Christoph Zwerschke (cito-at-online-dot-de) have volun- teered to translate the book to German. Their translation is located at http://abop-german.berlios.de. Lutz Horn says: I’m 32 years old and have a degree of Mathematics from University of Heidelberg, Germany. Currently I’m working as a software engineer on a publicly funded project to build a web portal for all things related to computer science in Germany.The main language I use as a professional is Java, but I try to do as much as possible with Python behind the scenes. Especially text analysis and conversion is very easy with Python. I’m not very familiar with GUI toolkits, since most of my programming is about web applications, where the user interface is build using Java frameworks like Struts. Currently I try to make more use of the functional programming features of Python and of generators. After taking a short look into Ruby, I was very impressed with the use of blocks in this language. Generally I like the dynamic nature of languages like Python and Ruby since it allows me to do things not possible in more static languages like Java.I’ve searched for some kind of introduction to programming, suitable to teach a complete non-programmer. I’ve found the book ‘How to Think Like a Computer Scientist: Learning with Python’, 124 and ‘Dive into Python’. The first is good for beginners but to long to translate. The second is not suitable for beginners. I think ‘A Byte of Python’ falls nicely between these, since it is not too long, written to the point, and at the same time verbose enough to teach a newbie. Besides this, I like the simple DocBook structure, which makes translating the text a generation the output in various formats a charm. Bernd Hengelein says: Lutz and me are going to do the german translation together. We just started with the intro and preface but we will keep you informed about the progress we make. Ok, now some personal things about me. I am 34 years old and playing with computers since the 1980’s, when the “Commodore C64” ruled the nurseries. After studying computer science I started working as a software engineer. Currently I am working in the field of medical imaging for a major german company. Although C++ is the main language I (have to) use for my daily work, I am constantly looking for new things to learn.Last year I fell in love with Python, which is a wonderful language, both for its possibilities and its beauty. I read somewhere in the net about a guy who said that he likes python, because the code looks so beautiful. In my opinion he’s absolutly right. At the time I decided to learn python, I noticed that there is very little good documentation in german available. When I came across your book the spontaneous idea of a german translation crossed my mind. Luckily, Lutz had the same idea and we can now divide the work.I am looking forward to a good cooperation! 22.8 Greek The Greek Ubuntu Community translated the book in Greek, for use in our on-line asynchronous Python lessons that take place in our forums. Contact @savvasradevic for more information. 22.9 Indonesian Daniel (daniel-dot-mirror-at-gmail-dot-com) is translating the book to Indonesian at http://python.or.id/moin.cgi/ByteofPython. W. Priyambodo also has volunteered to translate the book to Indonesian. The translation is in progress and here is the http://www.swaroopch.org/notes/Python_id:Daftar_Isi. 125 22.10 Italian Enrico Morelli (mr-dot-mlucci-at-gmail-dot-com) and Massimo Lucci (morelli-at- cerm-dot-unifi-dot-it) have volunteered to translate the book to Italian. The Italian translation is present at www.gentoo.it/Programmazione/byteofpython. The new translation is in progress and start with http://www.swaroopch.org/notes/Python_it:Prefazione. Massimo Lucci and Enrico Morelli - we are working at the Uni- versity of Florence (Italy) - Chemistry Department. I (Massimo) as service engineer and system administrator for Nuclear Magnetic Resonance Spectrometers; Enrico as service engineer and system administrator for our CED and parallel / clustered systems. We are programming on python since about seven years, we had experience working with Linux platforms since ten years. In Italy we are respon- sible and administrator for www.gentoo.it web site for Gentoo/Linux distrubution and www.nmr.it (now under construction) for Nuclear Magnetic Resonance applications and Congress Organization and Managements.That’s all! We are impressed by the smart language used on your Book and we think this is essential for approaching the Python to new users (we are thinking about hundred of students and researcher working on our labs). 22.11 Japanese Here’s a Japanese version at http://www.swaroopch.org/notes/Python_ja:Table_of_Contents. Shunro Dozono (dozono-at-gmail-dot-com) is translating the book to Japanese. 22.12 Mongolian Ariunsanaa Tunjin (luftballons2010-at-gmail-dot-com) has volunteered to trans- late the book to Mongolian. Update on Nov 22, 2009 : Ariunsanaa is on the verge of completing the transla- tion. 22.13 Norwegian (bokmål) Eirik Vågeskar (http://www.swaroopch.org/notes/User:Vages) is a high school student at Sandvika videregående skole in Norway, a blogger and currently translating the book to Norwegian (bokmål). The translation is in progress, and you can check the http://www.swaroopch.org/notes/Python_nb- no:Innholdsfortegnelse for more details. 126 Eirik Vågeskar: I have always wanted to program, but because I speak a small language, the learning process was much harder. Most tutorials and books are written in very technical English, so most high school graduates will not even have the vocabulary to understand what the tutorial is about. When I discovered this book, all my problems were solved. “A Byte of Python” used simple non-technical language to explain a programming language that is just as simple, and these two things make learning Python fun. After reading half of the book, I decided that the book was worth translating. I hope the translation will help people who have found themself in the same situation as me (especially young people), and maybe help spread interest for the language among people with less technical knowledge. 22.14 Polish Dominik Kozaczko (dkozaczko-at-gmail-dot-com) has volunteered to translate the book to Polish. Translation is in progress and it’s main page is available here: Ukąś Pythona. Update : The translation is complete and ready as of Oct 2, 2009. Thanks to Dominik, his two students and their friend for their time and effort! Dominik Kozaczko - I’m a Computer Science and Information Tech- nology teacher. 22.15 Portuguese Fidel Viegas (fidel-dot-viegas-at-gmail-dot-com) has volunteered to translate the book to Portuguese. 22.16 Romanian Paul-Sebastian Manole (brokenthorn-at-gmail-dot-com) has volunteered to trans- late this book to Romanian. Paul-Sebastian Manole - I’m a second year Computer Science student at Spiru Haret University, here in Romania. I’m more of a self-taught programmer and decided to learn a new language, Python. The web told me there was no better way to do so but read ‘’A Byte of Python”. That’s how popular this book is (congratulations to the author for writing such an easy to read book). I started liking Python so I decided to help translate the latest version of Swaroop’s book in Romanian. Although I could be the one with the first initiative, I’m just one volunteer so if you can help, please join me. 127 The translation is being done http://www.swaroopch.org/notes/Python_ro. 22.17 Russian and Ukranian Averkiev Andrey (averkiyev-at-ukr-dot-net) has volunteered to translate the book to Russian, and perhaps Ukranian (time permitting). Vladimir Smolyar (v_2e-at-ukr-dot-net) has started a Russian translation wiki pages. You may read the development version at http://www.swaroopch.org/notes/Python_ru:Table_of_Contents. 22.18 Slovak Albertio Ward (albertioward-at-gmail-dot-com) has translated the book to Slovak at fatcow.com/edu/python-swaroopch-sl/: We are a non-profit organization called “Translation for education”. We represent a group of people, mainly students and professors, of the Slavonic University. Here are students from different departments: linguistics, chemistry, biology, etc. We try to find interesting publica- tions on the Internet that can be relevant for us and our university colleagues. Sometimes we find articles by ourselves; other times our professors help us choose the material for translation. After obtaining permission from authors we translate articles and post them in our blog which is available and accessible to our colleagues and friends. These translated publications often help students in their daily study routine. Why have I chosen your article for translation? It was made to help the Bulgarians understand this article in all possible detail. Having done some research concerning the novelty and relevance of topics, I found that it was quite urgent for those who live in my country. So,I think it can become very popular. The language barrier in this little case no longer exists, because it was eliminated by my translation. 22.19 Spanish Alfonso de la Guarda Reyes (alfonsodg-at-ictechperu-dot-net), Gustavo Echeverria (gustavo-dot-echeverria-at-gmail-dot-com), David Crespo Ar- royo (davidcrespoarroyo-at-hotmail-dot-com) and Cristian Bermudez Serna (crisbermud-at-hotmail-dot-com) have volunteered to translate the book to Spanish. The translation is in progress, you can read the spanish (argentinian) translation starting by the http://www.swaroopch.org/notes/Python_es- ar:Tabla_de_Contenidos. Gustavo Echeverria says: 128 I work as a software engineer in Argentina. I use mostly C# and .Net technologies at work but strictly Python or Ruby in my personal projects. I knew Python many years ago and I got stuck inmediately. Not so long after knowing Python I discovered this book and it helped me to learn the language. Then I volunteered to translate the book to Spanish. Now, after receiving some requests, I’ve begun to translate “A Byte of Python” with the help of Maximiliano Soler. Cristian Bermudez Serna says: I am student of Telecommunications engineering at the University of Antioquia (Colombia). Months ago, i started to learn Python and found this wonderful book, so i volunteered to get the Spanish translation. 22.20 Swedish Mikael Jacobsson (leochingkwake-at-gmail-dot-com) has volunteered to translate the book to Swedish. 22.21 Turkish Türker SEZER (tsezer-at-btturk-dot-net) and Bugra Cakir (bugracakir-at-gmail- dot-com) have volunteered to translate the book to Turkish. Where is Turkish version? Bitse de okusak. Note : Replace -at- with @,-dot- with . and -underscore- with _ in the email addresses mentioned on this page. Dashes in other places in the email address remain as-is. 23 Translation Howto The full source of the book is available from the Git repository https://github. com/swaroopch/byte_of_python. Please fork the repository. Then, fetch the repository to your computer. You need to know how to use Git to do that. Start editing the .pd files to your local language. Please read the Pandoc README to understand the formatting of the text. Then follow the instructions in the README to install the software required to be able to convert the raw source files into PDFs, etc. 129



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