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Effect of Mastery Learning Strategy on Male And Female Students' Academic Achievement In Basic Technology In Edo State, Nigeria
Unsatisfactory gender differences in science based subjects and the need to enhance their academic achievement prompted this study. It focused on the effect of mastery learning strategy on academic achievement of Male and Female students' in Basic Technology (BTE). The study has five purposes, five research questions guided the study and four null hypotheses formulated were tested at 0.05 level of significance. Quasi-Experimental design was adopted. The population was 3,170 (1,675 male & 1,495 female) JSS II students. A sample size of 78 (43 male, 35 female) JSS11 students from two selected schools participated in this study. Simple random sampling technique was used to select which of the schools will be experimental or control group. A 50-item multiple choice Basic Technology Achievement Test (BTEAT) was used. The instrument was face and content validated before administration. Test – retest method was used to establish the reliability of the instrument. Pearson product moment correlation coefficient was used to correlate the two results and a reliability index of 0.85 was obtained. Both the experimental and control groups received pre-test and posttest. Data collected were analyzed with descriptive and inferential statistics (mean, mean difference, t-test and Analysis of Covariance (ANCOVA). It was found out that female students taught BTE with MLS performed relatively higher in their post-test academic achievement than the male students. Furthermore, there was a not significant interaction effect between gender and instructional strategy (MLS), on students' academic achievement in BTE. However, the findings revealed that both male and female taught with MLS performed significantly higher in there posttest academic achievement in BTE than those taught with Direct Instruction Strategy (DIS). Based on the findings, it was concluded that MLS is an effective instructional strategy that significantly enhances gender academic achievement in BTE. Therefore, the use of MLS is recommended, for curbing gender disparity in academic achievement in science based
Little epigraphy: Texts on public and private objects
Lampas 54.1, 2021
This contribution introduces small, often informal texts scratched or stamped on rocks, metal surfaces and pottery. To this type of so-called 'little epigraphy' belong graffiti, ostraca, weights and measures and curse tablets.
Critical Perspectives on Ancient DNA: Concluding Commentary
A great deal of ink has been spilled over the prob lems exhibited by researchers attempting to incorporate ancient DNA (aDNA) data into anthropological models of prehistory. The prob lems are both ethical and interpretive. Several of the chapters in this volume have compellingly and comprehensively discussed the ethical violations abundantly seen in aDNA research. They show that since there continue to be significant professional rewards for rapid and sensational publication-a phenomenon explored in detail in Andreas Nyblom's chapter on the fuss surrounding the "the female Viking warrior"-and few professional consequences for riding roughshod over ethical standards and the concerns of descendant and stakeholder communities, researchers will continue to make their own culture-bound value judgments. The research community itself must decide whether the ethical requirements of engaging in aDNA research should have teeth, by whom those teeth should be wielded, and what kinds of wounds those teeth should inflict. I want to thank the editors of this volume for the opportunity to provide this commentary. I will use the space available to me to discuss two phenomena related to anthropological aDNA research: one relevant to the community of scholars interested in molecular approaches to the past, and one relevant to both public understandings of the kinds of research discussed in this book and to the ways in which scholars untrained in ge ne tics understand the data generated. First, however, I would like to be explicit about my positionality in this space, because the peculiarities of my academic background significantly shape my views on the current state of affairs. I am a molecular anthropologist trained in the four-field Americanist tradition, in which the subdisciplines of biological anthropology, archaeology, linguistics, and sociocultural anthropology sit together under the umbrella of anthropology. I was trained in this way first in my home country of Aotearoa New Zealand,
DOCTORAT En Ecologie végétale
2011
In semi-arid and arid areas and especially in halomorphic formations (Sebkha, Chott, coast ...), the high salt concentration of soil and water in major part due to high evaporation and low rainfall and drainage, is a constraint to the development of most plant species including glycophytes. Thus, in these areas, the plant population is made up mostly of species able to perform life cycle under extremely restrictive conditions, namely halophytes. For this purpose, the latter have a double interest; in one hand, they allow the settlement of marginal areas and secondly, they can be used for identification of salt tolerance genes and their transfer to sensitive plant species using modern genetic and biotechnology engineering. In this study, we focused in particular stands on Arthrocnemum glaucum. Growth and development of species are not equal towards the salt stress; this heterogeneity also encouraged us to study the bio-ecology of a perennial Chenopodiaceae: Arthrocnemum glaucum, very active in both, North (Rachgoun 1 and 2, Moscarda, Sebkha 1 and 2) and South (Chott El-Gharbi) of Western Algeria. A description of the physical environment of the study area, including bioclimatology, geomorphology, geology and edaphology, was made. The stands studied are located in stations belonging to the low sub-humid and semi-arid bioclimatic stage with warm winter for the North and to the low arid with cold winter for the South. Soil tests indicate a high ecological plasticity of Arthrocnemum glaucum found on very different textures, namely sander for "Rachgoun 2 and Chott El-Gharbi", sandy loam for "Rachgoun 1, Moscarda", loamy clay for "Sebkha 1" and mostly loamy for "Sebkha 2". "Pollu tolerance" of species present in "Sebkha 1" has been highlighted by the notion of "biological concentrator" of heavy metals. The dosage of the latter, in the three organs (stem, leaf, and root) showed that lead and zinc have higher rates of accumulations larger than nickel, copper and cadmium. However their presence in the organs seems natural; impressive pollution of this situation has no impact on the studied species. The organographic histology of Arthrocnemum glaucum was studied to better know the anatomy and internal structure of the species and to identify possible histological alterations of the plant to the stational conditions. Histometric study has been statistically treated. In vitro culture of Arthrocnemum glaucum stem fragments in different culture media was performed to observe the root elongation; it remains low, reaching respectively 9 and 25 mm in distilled water and in the media knop + auxin. According to Rancillac (1981), auxins are known for their role in rhizogenesis division and cells elongation. A biomorphological study followed by a statistical study made it possible to assess the influence of bioclimate and soil on the development of Arthrocnemum glaucum which is very different from one station to another. A floristic study of Arthrocnemum glaucum stands, associated with a factorial correspondence analysis were performed on the basis of identified flora (Braun-Blanquet method, 1951) to get an overview of the diversity of the latter, consisting mainly of Salicornideae and annual grasses.
Thermally and electrically conductive multifunctional sensor based on epoxy/graphene composite
Flexible electronics is expected to be one of the most active research areas in the next decade. In this study, a mechanically strong and flexible epoxy/GnP composite film was fabricated having percolation threshold of electrical conductivity at 1.08 vol% GnPs and high thermal conductivity as 1.07 W m -1 K -1 at 10 vol% GnPs. The composite film shows high mechanical performance: Young's modulus and tensile strength were improved by 1344% and 66.7%, respectively at 10 vol%. The film has demonstrated high sensitivity to various mechanical loads: (i) it has gauge factors of 2 at strain range 0-7% and 6 at range 7-10% (ii) it gives good electrical response with bending and twisting angles up to 180 o ; and (iii) it displays a good compressive load response up to 2N where the absolute value of electrical resistance change increased by 71%. Furthermore, the film has showed an excellent reliability up to 5.5×10 3 cycles with minor zero-point error. Above 20 ºC, the film solely acts as a temperature sensor; upon cyclic temperature testing, the film demonstrated a stable resistive response in the range of 30 −75 ºC with a temperature sensitivity coefficient of 0.0063℃ -1 . This flexible composite film has remarkable properties that enable it to be used as a full-fledged sensor for universal applications in aerospace, automotive and civil engineering.
A Byte of Python
v1.92 (for Python 3.0)
PDF generated using the open source mwlib toolkit
see http://code.pediapress.com/ for more information
Python
2
Python
Choose your Python version:
If you want to learn the current Python 2.x, read
[1]
[2]
here
or download the PDF
If you want to learn the new Python 3.0, read here or
[3]
download the PDF
[4]
You can also buy a printed hardcopy.
Introduction
'A Byte of Python' is a 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 updated for the new Python 3.0 language. If you are looking for a tutorial
on the current Python 2.x version, please download the previous revision of the book [5]. On
the same note, if you're wondering whether to learn Python 2.x or 3.x, then read this article
by James Bennett [6].
Who Reads 'A Byte of Python'?
Here are what people are saying about the book:
Feedback From Readers
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)
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 cluless 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
Python
3
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.
...
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
[7]
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
[8]
Academic Courses
This book is being used as instructional material in various educational institutions:
1.
2.
3.
4.
5.
6.
7.
8.
'Principles of Programming Languages' course at Vrije Universiteit, Amsterdam [9]
'Basic Concepts of Computing' course at University of California, Davis [10]
'Programming With Python' course at Harvard University [11]
'Introduction to Programming' course at University of Leeds [12]
'Introduction to Application Programming' course at Boston University [13]
'Information Technology Skills for Meteorology' course at University of Oklahoma [14]
'Geoprocessing' course at Michigan State University [15]
'Multi Agent Semantic Web Systems' course at the University of Edinburgh [16]
Python
4
Even NASA
The book is even used by NASA! It is being used in their Jet Propulsion Laboratory
their Deep Space Network project.
[17]
with
Official Recommendation
This book has been listed on the official website for Python in the Full Tutorials
next to the official documentation.
[18]
section,
License
1. This book is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported
[19]
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
• Under the following conditions:
• Attribution. You must attribute the work in the manner specified by the author or
licensor (but not in any way that suggests that they endorse you or your use of this
book).
• Share Alike. If you alter, transform, or build upon this work, you may distribute the
resulting work only under the same or similar license to this one.
• For any reuse or distribution, you must make clear to others the license terms of this
book.
• Any of the above conditions can be waived if you get permission from the copyright
holder.
• Nothing in this license impairs or restricts the author's moral rights.
2. Attribution must be shown by linking back to http:/ / www. swaroopch. com/ notes/
Python and clearly indicating that the original text can be fetched from this location.
3. All the code/scripts provided in this book is licensed under the 3-clause BSD License [20]
unless otherwise noted.
4. Volunteer contributions to this original book must be under this same license and the
copyright must be assigned to the main author of this book.
Read Now
You can read the book online at Python_en:Table of Contents.
Buy the Book
A printed hardcopy of the book can be purchased [21] for your offline reading pleasure, and
to support the continued development and improvement of this book.
Download
• PDF (631KB) [22]
• Mediawiki XML dump (276KB)
[23]
(for advanced users only)
If you wish to support the continued development of this book, please consider
making a donation [24] or buy a printed hardcopy [25].
Python
Translations
If you are interested in reading or contributing translations of this book to other human
languages, please see Translations.
Next
References
[1] http:/ / www. ibiblio. org/ swaroopch/ byteofpython/ read/
[2] http:/ / www. ibiblio. org/ swaroopch/ byteofpython/ files/ 120/ byteofpython_120. pdf
[3] http:/ / www. swaroopch. com/ files/ byteofpython/ byte_of_python_v191. pdf
[4] http:/ / www. swaroopch. com/ buybook
[5] http:/ / www. ibiblio. org/ swaroopch/ byteofpython/ files/ 120/
[6] http:/ / www. b-list. org/ weblog/ 2008/ dec/ 05/ python-3000/
[7] http:/ / www. linux. com/ feature/ 126522
[8] http:/ / paxmodept. com/ telesto/ blogitem. htm?id=627
[9] http:/ / www. few. vu. nl/ ~nsilvis/ PPL/ 2007/ index. html
[10] http:/ / www. cs. ucdavis. edu/ courses/ exp_course_desc/ 10. html
[11] http:/ / www. people. fas. harvard. edu/ ~preshman/ python_winter. html
[12] http:/ / www. comp. leeds. ac. uk/ acom1900/
[13] http:/ / www. cs. bu. edu/ courses/ cs108/ materials. html
[14] http:/ / gentry. metr. ou. edu/ byteofpython/
[15] http:/ / www. msu. edu/ ~ashton/ classes/ 825/ index. html
[16] http:/ / homepages. inf. ed. ac. uk/ ewan/ masws/
[17] http:/ / dsnra. jpl. nasa. gov/ software/ Python/ byte-of-python/ output/
byteofpython_html/
[18] http:/ / www. python. org/ doc/ intros/
[19] http:/ / creativecommons. org/ licenses/ by-sa/ 3. 0/
[20] http:/ / www. opensource. org/ licenses/ bsd-license. php
[21] http:/ / www. swaroopch. com/ buybook
[22] http:/ / www. swaroopch. com/ files/ byteofpython/ byte_of_python_v191. pdf
[23] http:/ / www. swaroopch. com/ files/ byteofpython/ byte_of_python_v191. xml
[24] https:/ / www. paypal. com/ cgi-bin/ webscr?cmd=_donations&
business=swaroop%40swaroopch%2ecom&item_name=A%20Byte%20of%20Python&
no_shipping=0&no_note=1& tax=0& currency_code=USD& lc=IN&
bn=PP%2dDonationsBF& charset=UTF%2d8
[25] http:/ / www. swaroopch. com/ buybook
Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=1391
Contributors: Swaroop, 1 anonymous edits
5
Python en:Table of Contents
Python en:Table of Contents
• → Front Page
1. → Translations
2. → Preface
3. → Introduction
4. → Installation
5. → First Steps
6. → Basics
7. → Operators and Expressions
8. → Control Flow
9. → Functions
10. → Modules
11. → Data Structures
12. → Problem Solving
13. → Object Oriented Programming
14. → Input Output
15. → Exceptions
16. → Standard Library
17. → More
18. → What Next
19. → Appendix: FLOSS
20. → Appendix: About
21. → Appendix: Revision History
→ Previous → Next
Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=1343
Contributors: Swaroop, Waterox888, 3 anonymous edits
6
Python en:Translations
Python en:Translations
There are many translations of the book available in different human languages, thanks to
many tireless volunteers!
If you want to help 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.
Chinese
Juan Shen (orion-underscore-val-at-163-dot-com) has volunteered to translate the book to
Chinese.
what - 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.
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 (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. 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.
7
Python en:Translations
8
Italian
Enrico
Morelli
(mr-dot-mlucci-at-gmail-dot-com)
and
Massimo
(morelli-at-cerm-dot-unifi-dot-it) have volunteered to translate the book to Italian.
Lucci
The Italian translation is present at www.gentoo.it/Programmazione/byteofpython (http:/ /
www. gentoo. it/ Programmazione/ byteofpython). The new translation is in progress and
start with "Prefazione".
Massimo Lucci and Enrico Morelli - we are working at the University 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
responsible 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).
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 volunteered to translate the book to German.
Their translation is located at http:/ / abop-german. berlios. de (http:/ / abop-german.
berlios. de).
Lutz Horn : 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', 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.
Python en:Translations
Bernd Hengelein : 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!
Norwegian (bokmål)
Eirik Vågeskar (or Vages) is a high school student at Sandvika videregående skole (http:/ /
no. wikipedia. org/ wiki/ Sandvika_videregående_skole) in Norway, a blogger (http:/ /
forbedre. blogspot. com/ ) and currently translating the book to Norwegian (bokmål). The
translation is in progress, and you can check the table of contents for more details.
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.
Indonesian
Daniel (daniel-dot-mirror-at-gmail-dot-com) is translating the book to Indonesian at http:/ /
python. or. id/ moin. cgi/ ByteofPython
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 (http:/ /
wiki. mercury. lo5. bielsko. pl/ index. php/ UkÄ Å_Pythona).
Dominik Kozaczko - I'm a Computer Science and Information Technology
teacher.
9
Python en:Translations
10
Catalan
Moises Gomez (moisesgomezgiron-at-gmail-dot-com) has volunteered to translate the book
to Catalan. The translation is in progress, and starts with the chapter "Taula de continguts".
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. 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.
Portuguese
Fidel Viegas (fidel-dot-viegas-at-gmail-dot-com) has volunteered to translate the book to
Portuguese.
Romanian
Paul-Sebastian Manole (brokenthorn-at-gmail-dot-com) has volunteered to translate 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.
The translation is being done here (http:/ / www. swaroopch. com/ notes/ Python_ro).
Brazilian Portuguese
Rodrigo Amaral (http:/ / rodrigoamaral. net) (rodrigoamaral-at-gmail-dot-com)
volunteered to translate the book to Brazilian Portuguese...
has
French
Gregory (coulix-at-ozforces-dot-com-dot-au) has volunteered to translate the book to
French.
Danish
Lars Petersen (lars-at-ioflux-dot-net) has volunteered to translate the book to Danish.
Spanish
Alfonso de la Guarda Reyes (alfonsodg-at-ictechperu-dot-net) and Gustavo Echeverria
(gustavo-dot-echeverria-at-gmail-dot-com) have volunteered to translate the book to
Python en:Translations
Spanish. The translation is in progress, you can read the spanish (argentinian) translation
starting by the table of contents (tabla de contenidos).
Gustavo Echeverria: 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.
Arabic
Alaa Abadi (alaanassir-at-gmail-dot-com) has volunteered to translate the book to Arabic.
ISA .
Swedish
Mikael Jacobsson (leochingkwake-at-gmail-dot-com) has volunteered to translate the book
to Swedish.
Russian and Ukranian
Averkiev Andrey (averkiyev-at-ukr-dot-net) has volunteered to translate the book to
Russian, and perhaps Ukranian (time permitting).
Turkish
Türker SEZER (tsezer-at-btturk-dot-net) and Bugra Cakir (bugracakir-at-gmail-dot-com)
have volunteered to translate the book to Turkish.
Mongolian
Ariunsanaa Tunjin (tariunsanaa-at-yahoo-dot-com) has volunteered to translate the book to
Mongolian.
Note
Replace ' - a t - ' with ' @ ' , ' - d o t - ' with ' . ' and ' - u n d e r s c o r e - ' with ' _ ' in the
email addresses mentioned on this page. Dashes in other places in the email address
remain as-is.
11
Python en:Translations
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Python en:Preface
Python is probably one of the few programming languages which is both simple and
powerful. This is good for both and beginners as well as experts, and more importantly, is
fun to program with. This book aims to help you learn this wonderful language and show
how to get things done quickly and painlessly - in effect 'The Perfect Anti-venom to your
programming problems'.
Who This Book Is For
This book serves as a guide or tutorial to the Python programming language. It is mainly
targeted at newbies. It is useful for experienced programmers as well.
The aim is that if all you know about computers is how to save text files, then you can learn
Python from this book. If you have previous programming experience, then you can also
learn Python from this book.
If you do have previous programming experience, you will be interested in the differences
between 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!
History Lesson
I first started with Python when I needed to write an installer for a 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 where Eric S. Raymond, the famous and respected hacker, talked about how Python
has 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.
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.
12
Python en:Preface
This book started out as my personal notes on Python and I still consider it in the same way,
although I've taken a lot of effort to make it more palatable to others :)
In the true spirit of open source, I have received lots of constructive suggestions, criticisms
and feedback from enthusiastic readers which has helped me improve this book a lot.
Status Of The Book
Changes since the last major revision in March 2005 is updating for the Python 3.0 release
(expected in August/September 2008). Since the Python 3.0 language itself is still not
finalized/released, this book is constantly undergoing changes. However, in the spirit of the
open source philosophy of "Release Early, Release Often", the updated book has been
released and is constantly being updated.
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 (http:/ / www. swaroopch. com/ contact/ ) or the respective translators with your
comments and suggestions.
It's a constant tussle to balance this book between a beginner's needs and the tendency
towards 'completeness' of information. It would be helpful if readers also gave feedback on
how much depth this book should go into.
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 (http:/ / www. swaroopch. com/ buybook), and also send me feedback.
License
1. This book is licensed under the Creative Commons Attribution-Noncommercial-Share
Alike 3.0 Unported (http:/ / creativecommons. org/ licenses/ by-nc-sa/ 3. 0/ ) 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
• Under the following conditions:
• Attribution. You must attribute the work in the manner specified by the author or
licensor (but not in any way that suggests that they endorse you or your use of this
book).
• Share Alike. If you alter, transform, or build upon this work, you may distribute the
resulting work only under the same or similar license to this one.
• For any reuse or distribution, you must make clear to others the license terms of this
book.
• Any of the above conditions can be waived if you get permission from the copyright
holder.
• Nothing in this license impairs or restricts the author's moral rights.
2. Attribution must be shown by linking back to http:/ / www. swaroopch. com/ notes/
Python and clearly indicating that the original text can be fetched from this location.
13
Python en:Preface
3. All the code/scripts provided in this book is licensed under the 3-clause BSD License
(http:/ / www. opensource. org/ licenses/ bsd-license. php) unless otherwise noted.
4. Volunteer contributions to this original book must be under this same license and the
copyright must be assigned to the main author of this book.
Feedback
I have put in a lot of effort to make this book as interesting and as accurate as possible.
However, if you find some material to be inconsistent or incorrect, or simply needs
improvement, then please do inform me, so that I can make suitable improvements. You can
reach me via my user page.
Buy the Book
If you wish to support the continued development of this book, please consider purchasing
a printed copy (http:/ / www. swaroopch. com/ buybook) or making a donation.
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
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14
Python en:Introduction
Python en:Introduction
Introduction
Python is one of those rare languages which can claim to be both simple and powerful.
You will find that you will be pleasantly surprised on how easy it is to concentrate on the
solution to the problem rather than the syntax and structure of the language you are
programming in.
The official introduction to Python is:
Python is an easy to learn, powerful programming language. It has efficient
high-level data structures and a simple but effective approach to object-oriented
programming. Python's elegant syntax and dynamic typing, together with its
interpreted nature, make it an ideal language for scripting and rapid application
development in many areas on most platforms.
I will discuss most of these features in more detail in the next section.
Note
Guido van Rossum, the creator of the Python language, named the language after the
BBC show "Monty Python's Flying Circus". He doesn't particularly like snakes that kill
animals for food by winding their long bodies around them and crushing them.
Features of Python
Simple
Python is a simple and minimalistic language. Reading a good Python program feels
almost like reading English, although very strict English! This pseudo-code nature of
Python is one of its greatest strengths. It allows you to concentrate on the solution to
the problem rather than the language itself.
Easy to Learn
As you will see, Python is extremely easy to get started with. Python has an
extraordinarily simple syntax, as already mentioned.
Free and Open Source
Python is an example of a FLOSS (Free/Libré and Open Source 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.
High-level Language
When you write programs in Python, you never need to bother about the low-level
details such as managing the memory used by your program, etc.
Portable
Due to its open-source nature, Python has been ported 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
15
Python en:Introduction
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 !
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, 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!
Object Oriented
Python supports procedure-oriented programming as well as object-oriented
programming. In procedure-oriented languages, the program is built around
procedures or functions which are nothing but reusable pieces of programs. In
object-oriented languages, the program is built around objects which combine data
and functionality. Python has a very powerful but simplistic way of doing OOP,
especially when compared to big languages like C++ or Java.
Extensible
If you need a critical piece of code to run very fast or want to have some piece of
algorithm not to be open, you can code that part of your program in C or C++ and
then use it from your Python program.
Embeddable
You can embed Python within your C/C++ programs to give 'scripting' capabilities for
your program's users.
Extensive Libraries
The Python Standard Library is huge indeed. It can help you do various things
involving regular expressions, documentation generation, unit testing, threading,
databases, web browsers, CGI, FTP, email, XML, XML-RPC, HTML, WAV files,
cryptography, GUI (graphical user interfaces), Tk, 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 such as
wxPython (http:/ / www. wxpython. org) , Twisted (http:/ / www. twistedmatrix. com/
products/ twisted), Python Imaging Library (http:/ / www. pythonware. com/ products/
pil/ index. htm) and many more.
16
Python en:Introduction
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.
Why not Perl?
If you didn't know already, Perl is another extremely popular open source interpreted
programming language.
If you have ever tried writing a large program in Perl, you would have answered this
question yourself! In other words, Perl programs are easy when they are small and it excels
at small hacks and scripts to 'get work done'. However, they quickly become unwieldy once
you start writing bigger programs and I am speaking this out of my experience writing
large Perl programs at Yahoo!
When compared to Perl, Python programs are definitely simpler, clearer, easier to write
and hence more understandable and maintainable. I do admire Perl and I do use it on a
daily basis for various things but whenever I write a program, I always start thinking in
terms of Python because it has become so natural for me. Perl has undergone so many
hacks and changes, that it feels like it is one big (but one hell of a) hack. Sadly, the
upcoming Perl 6 does not seem to be making any improvements regarding this.
The only and very significant advantage that I feel Perl has, is its huge CPAN (http:/ / cpan.
perl. org) library - the Comprehensive Perl Archive Network. As the name suggests, this is a
humongous collection of Perl modules and it is simply mind-boggling because of its sheer
size and depth - you can do virtually anything you can do with a computer using these
modules. One of the reasons that Perl has more libraries than Python is that it has been
around for a much longer time than Python. However this seems to be changing with the
growing Python Package Index (http:/ / pypi. python. org/ pypi).
Why not Ruby?
If you didn't know already, Ruby is another popular open source interpreted programming
language.
If you already like and use Ruby, then I would definitely recommend you to continue using
it.
For other people who have not used it and are trying to judge whether to learn Python or to
learn Ruby, then I would recommend Python, purely from an ease-of-learning perspective. I
personally found it hard to grok the Ruby language, but for people who understand Ruby,
they all praise the beauty of the language. Unfortunately, I am not as lucky.
What Programmers Say
You may find it interesting to read what great hackers like ESR have to say about Python:
• Eric S. Raymond is the author of "The Cathedral and the Bazaar" and is also the person
who coined the term Open Source. He says that Python has become his favorite
programming language (http:/ / www. linuxjournal.com/ article. php?sid=3882). This
article was the real inspiration for my first brush with Python.
• Bruce Eckel is the author of the famous Thinking in Java and Thinking in C++ books.
He says that no language has made him more productive than Python. He says that
Python is perhaps the only language that focuses on making things easier for the
17
Python en:Introduction
programmer. Read the complete interview (http:/ / www. artima. com/ intv/ aboutme.
html) for more details.
• Peter Norvig is a well-known Lisp author and Director of Search Quality at Google
(thanks to Guido van Rossum for pointing that out). He says that Python has always been
an integral part of Google. You can actually verify this statement by looking at the Google
Jobs (http:/ / www. google. com/ jobs/ index. html) page which lists Python knowledge as a
requirement for software engineers.
About Python 3.0
Python 3.0 is the new version of the language. It is sometimes referred to as Python 3000 or
Py3K.
The main reason for a major new version of Python is to remove all the small problems and
nitpicks that have accumulated over the years and to make the language even more clean.
If you already have a lot of Python 2.x code, then there is a utility to assist you to convert
2.x to 3.x source (http:/ / docs. python. org/ dev/ 3. 0/ library/ 2to3. html).
More details are at:
• Guido van Rossum's introduction (http:/ / www. artima. com/ weblogs/ viewpost.
jsp?thread=208549)
• What's New in Python 2.6 (http:/ / docs. python. org/ dev/ whatsnew/ 2. 6. html) (features
significantly different from previous Python 2.x versions and most likely will be included
in Python 3.0)
• What's New in Python 3.0 (http:/ / docs. python. org/ dev/ 3. 0/ whatsnew/ 3. 0. html)
• Python 2.6 and 3.0 Release Schedule (http:/ / www. python. org/ dev/ peps/ pep-0361/ )
• Python 3000 (the official authoritative list of proposed changes) (http:/ / www. python.
org/ dev/ peps/ pep-3000/ )
• Miscellaneous Python 3.0 Plans (http:/ / www. python. org/ dev/ peps/ pep-3100/ )
• Python News (detailed list of changes) (http:/ / www. python. org/ download/ releases/ 3.
0/ NEWS. txt)
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18
Python en:Installation
Python en:Installation
If you have Python 2.x installed already, you do not have to remove it to install Python 3.0.
You can have both installed at the same time.
For Linux and BSD users
If you are using a Linux distribution such as Ubuntu, Fedora, OpenSUSE or {put your
choice here}, or a BSD system such as FreeBSD, then it is most likely you already have
Python installed on your system.
To test if you have Python already installed on your Linux box, open a shell program (like
k o n s o l e or g n o m e - t e r m i n a l ) and enter the command p y t h o n - V as shown below.
$ python -V
Python 3.0b1
Note
$ is the prompt of the shell. It will be different for you depending on the settings of
your OS, hence I will indicate the prompt by just the $ symbol.
If you see some version information like the one shown above, then you have Python
installed already.
However, if you get a message like this one:
$ python -V
bash: Python: command not found
Then you don't have Python installed. This is highly unlikely but possible.
Note
If you have Python 2.x already installed, then try p y t h o n 3 - V .
In this case, you have two ways of installing Python on your system.
• You can compile Python from the source code (http:/ / www. python. org/ download/
releases/ 3. 0/ ) and install it. The compilation instructions are provided at the website.
• [This option will be available after the final release of Python 3.0] Install the binary
packages using the package management software that comes with your OS, such as
a p t - g e t in Ubuntu/Debian and other Debian-based Linux, y u m in Fedora Linux, p k g _ a d d
in FreeBSD, etc. Note that you will need an internet connection to use this method.
Alternatively, you can download the binaries from somewhere else and then copy to your
PC and install it.
19
Python en:Installation
For Windows Users
Visit http:/ / www. python. org/ download/ releases/ 3. 0/ and download the latest version
from this website, which was 3.0 beta 1 (http:/ / www. python. org/ ftp/ python/ 3. 0/
python-3. 0b1. msi) as of this writing. This is just 12.8 MB which is very compact compared
to most other languages or software. The installation is just like any other Windows-based
software.
Caution
When you are given the option of unchecking any "optional" components, don't
uncheck any! Some of these components can be useful for you, especially IDLE.
An interesting fact is that majority of Python downloads are by Windows users. Of course,
this doesn't give the complete picture since almost all Linux users will have Python installed
already on their systems by default.
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.
For Windows 2000, XP, 2003 , click on C o n t r o l P a n e l -> S y s t e m -> A d v a n c e d ->
E n v i r o n m e n t V a r i a b l e s . Click on the variable named PATH in the 'System Variables'
section, then select E d i t and add ; C : \ P y t h o n 3 0 to the end of what is already there. Of
course, use the appropriate directory name.
For older versions of Windows, add the following line to the file C : \ A U T O E X E C . B A T :
'P A T H = % P A T H % ; C : \ P y t h o n 3 0 ' (without the quotes) and restart the system. For Windows NT,
use the A U T O E X E C . N T file.
For Mac OS X Users
Mac OS X Users will find Python already installed on their system. Open the T e r m i n a l . a p p
and run p y t h o n - V and follow the advice in the above Linux section.
Summary
For a Linux system, you most probably already have Python installed on your system.
Otherwise, you can install it using the package management software that comes with your
distribution. For a Windows system, installing Python is as easy as downloading the
installer and double-clicking on it. From now on, we will assume that you have Python
installed on your system.
Next, we will write our first Python program.
20
Python en:Installation
21
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Python en:First Steps
Introduction
We will now see how to run a traditional 'Hello World' program in Python. This will teach
you how to write, save and run Python programs.
There are two ways of using Python to run your program - using the interactive interpreter
prompt or using a source file. We will now see how to use both of these methods
Using The Interpreter Prompt
Start the interpreter on the command line by entering p y t h o n at the shell prompt.
For Windows users, you can run the interpreter in the command line if you have set the
P A T H variable appropriately.
If you are using IDLE, click on S t a r t → P r o g r a m s → P y t h o n 3 . 0 → I D L E ( P y t h o n G U I ) .
Now enter p r i n t ( ' H e l l o
H e l l o W o r l d as output.
$
P
bit (
T
infor
>
H
>
y
I
y
m
>
e
>
p
t
n
p
a
>
l
>
y
h
t
e
t
thon
on 3.0
el)] o
"help
ion.
print(
lo Worl
W o r l d ' ) followed by the E n t e r key. You should see the words
b2 (r30b2:65106, Jul 18 2008, 18:44:17) [MSC v.1500 32
n win32
", "copyright", "credits" or "license" for more
'Hello World')
d
Notice that Python gives you the output of the line immediately! What you just entered is a
single Python statement. We use p r i n t to (unsurprisingly) print any value that you supply
to it. Here, we are supplying the text H e l l o W o r l d and this is promptly printed to the
screen.
How to Quit the Interpreter Prompt
To exit the prompt, press c t r l - d if you are using IDLE or are using a Linux/BSD shell.
In case of the Windows command prompt, press c t r l - z followed by e n t e r key.
Choosing An Editor
Before we move on to writing Python programs in source files, we need an editor to write
the source files. The choice of an editor is crucial indeed. You have to choose an editor as
you would choose a car you would buy. A good editor will help you write Python programs
easily, making your journey more comfortable and helps you reach your destination
(achieve your goal) in a much faster and safer way.
Python en:First Steps
One of the very basic requirements is syntax highlighting where all the different parts of
your Python program are colorized so that you can see your program and visualize its
running.
If you are using Windows, then I suggest that you use IDLE. IDLE does syntax highlighting
and a lot more such as allowing you to run your programs within IDLE among other things.
A special note: 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 IDLE (and also VIM) will
automatically help you do this.
If you are using Linux/FreeBSD, then you have a lot of choices for an editor. If you are just
beginning to program, you might want to use geany. It has a graphical user interface and
has buttons to compile and run your python program without a fuss.
If you are an experienced programmer, then you must be already using V i m or E m a c s .
Needless to say, these are two of the most powerful editors and you will be benefitted by
using them to write your Python programs. I personally use V i m for most of my programs.
If you are a beginner programmer, then you can use K a t e which is one of my favorites. 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.
In this book, we will use IDLE, our IDE and editor of choice. IDLE is installed by default
with the Windows and Mac OS X Python installers. It is also available for installation for
Linux (http:/ / love-python. blogspot. com/ 2008/ 03/ install-idle-in-linux. html) and BSDs in
their respective repositories.
We will explore how to use IDLE in the next section. For further details, please refer the
IDLE documentation (http:/ / www. python. org/ idle/ doc/ idlemain. html).
If you still want to explore other choices of an editor, see the comprehensive list of Python
editors (http:/ / www. python. org/ cgi-bin/ moinmoin/ PythonEditors) and make your choice.
You can also choose an IDE (Integrated Development Environment) for Python. See the
comprehensive list of IDEs that support Python (http:/ / www. python. org/ cgi-bin/
moinmoin/ IntegratedDevelopmentEnvironments) for more details. Once you start writing
large Python programs, IDEs can be very useful indeed.
I repeat once again, please choose a proper editor - it can make writing Python programs
more fun and easy.
For Vim users
There is a good introduction on how to make Vim a powerful Python IDE by John M
Anderson (http:/ / blog. sontek. net/ 2008/ 05/ 11/ python-with-a-modular-ide-vim/).
For Emacs users
There is a good introduction on how to make Emacs a powerful Python IDE by Ryan
McGuire
(http:/
/
www.
enigmacurry.
com/
2008/
05/
09/
emacs-as-a-powerful-python-ide/).
22
Python en:First Steps
Using A Source File
Now let's get back to programming. There is a tradition that whenever you learn a new
programming language, the first program that you write and run is the 'Hello World'
program - all it does is just say 'Hello World' when you run it. As Simon Cozens [1] puts it, it
is the 'traditional incantation to the programming gods to help you learn the language
better' :) .
Start your choice of editor, enter the following program and save it as h e l l o w o r l d . p y
If you are using IDLE, click on F i l e → N e w W i n d o w and enter the following program. Then
click on F i l e → S a v e .
#!/usr/bin/python
#Filename: helloworld.py
print('Hello World')
Run this program by opening a shell (Linux terminal or DOS prompt) and entering the
command p y t h o n h e l l o w o r l d . p y .
If you are using IDLE, use the menu R u n → R u n M o d u l e or the keyboard shortcut F 5 .
The output is as shown below.
$ python helloworld.py
Hello World
If you got the output as shown above, congratulations! - you have successfully run your first
Python program.
In case you got an error, please type the above program exactly as shown and above and
run the program again. Note that Python is case-sensitive i.e. p r i n t is not the same as
P r i n t - 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
Let us consider the first two lines of the program. These are called comments - anything to
the right of the # symbol is a comment and is mainly useful as notes for the reader of the
program.
Python does not use comments except for the special case of the first line here. It is called
the shebang line - whenever the first two characters of the source file are # ! followed by
the location of a program, this tells your Linux/Unix system that this program should be run
with this interpreter when you execute the program. This is explained in detail in the next
section. Note that you can always run the program on any platform by specifying the
interpreter directly on the command line such as the command p y t h o n h e l l o w o r l d . p y .
Important
Use comments sensibly in your program to explain some important details of your
program - this is useful for readers of your program so that they can easily understand
what the program is doing. Remember, that person can be yourself after six months!
The comments are followed by a Python statement. Here we call the p r i n t function this
just prints the text ' H e l l o W o r l d ' . We will learn about functions in a → later chapter, what
23
Python en:First Steps
24
you should understand now is that whatever you supply in the parentheses will be printed
back to the screen. In this case, we supply ' H e l l o W o r l d ' which is referred to as a string don't worry, we will explore these terminologies in detail later.
Executable Python Programs
This applies only to Linux/Unix users but Windows users might be curious as well about the
first line of the program. First, we have to give the program executable permission using
the c h m o d command then run the source program.
$ chmod a+x helloworld.py
$ ./helloworld.py
Hello World
The chmod command is used here to change the mode of the file by giving execute
permission to all users of the system. Then, we execute the program directly by specifying
the location of the source file. We use the . / to indicate that the program is located in the
current directory.
To make things more fun, you can rename the file to just h e l l o w o r l d and run it as
. / h e l l o w o r l d 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.
What if you don't know where Python is located? Then, you can use the special e n v
program on Linux/Unix systems. Just change the first line of the program to the following:
#!/usr/bin/env python
The e n v program will in turn look for the Python interpreter which will run the program.
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 anywhere? You can do this by storing the
program in one of the directories listed in the P A T H environment variable. Whenever you
run any program, the system looks for that program in each of the directories listed in the
P A T H 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.
$
/
$
$
H
e
us
c
h
el
c
r
p
e
l
ho
/lo
he
llo
o W
$
c
l
w
o
P
a
l
o
r
A
l
o
r
l
T
/
w
l
d
H
bin:/usr/bin:/bin:/usr/X11R6/bin:/home/swaroop/bin
orld.py /home/swaroop/bin/helloworld
d
We can display the P A T H variable using the e c h o command and prefixing the variable name
by $ to indicate to the shell that we need the value of this variable. We see that
/ h o m e / s w a r o o p / b i n is one of the directories in the PATH variable where swaroop is the
username I am using in my system. There will usually be a similar directory for your
username on your system. Alternatively, you can add a directory of your choice to the P A T H
variable - this can be done by running P A T H = $ P A T H : / h o m e / s w a r o o p / m y d i r where
' / h o m e / s w a r o o p / m y d i r ' is the directory I want to add to the P A T H variable.
This method is very useful if you want to write useful scripts that you want to run the
program anytime, anywhere. It is like creating your own commands just like c d or any
Python en:First Steps
other commands that you use in the Linux terminal or DOS prompt.
Caution
W.r.t. Python, a program or a script or software all mean the same thing.
Getting Help
If you need quick information about any function or statement in Python, then you can use
the built-in h e l p functionality. This is very useful especially when using the interpreter
prompt. For example, run h e l p ( p r i n t ) - 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 h e l p ( ) to learn
more about using h e l p itself!
In case you need to get help for operators like r e t u r n , then you need to put those inside
quotes such as h e l p ( ' r e t u r n ' ) so that Python doesn't get confused on what we're trying
to do.
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.
References:
[1] The author of the amazing 'Beginning Perl' book
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25
Python en:Basics
Python en: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.
Literal Constants
An example of a literal constant is a number like 5 , 1 . 2 3 , 9 . 2 5 e - 3 or a string like ' T h i s i s
a s t r i n g ' or " I t ' s a s t r i n g ! " . 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.
Numbers
Numbers in Python are of three types - integers, floating point and complex numbers.
• An examples of an integer is 2 which is just a whole number.
• Examples of floating point numbers (or floats for short) are 3 . 2 3 and 5 2 . 3 E - 4 . The E
notation indicates powers of 10. In this case, 5 2 . 3 E - 4 means 5 2 . 3 * 1 0 - 4 .
• Examples of complex numbers are ( - 5 + 4 j ) and ( 2 . 3 - 4 . 6 j )
Note for Experienced Programmers
There is no separate 'long int' type. The default integer type can be any large value.
Strings
A string is a sequence of characters. Strings are basically just a bunch of words. The words
can be in English or any other language that is supported in the Unicode standard, which
means almost any language in the world (http:/ / www. unicode. org/ faq/ basic_q. html#16).
Note for Experienced Programmers
There are no "ASCII-only" strings because Unicode is a superset of ASCII. If a strictly
ASCII-encoded byte-stream is needed, then use s t r . e n c o d e ( " a s c i i " ) . For more
details, please see the related discussion at StackOverflow (http:/ / stackoverflow. com/
questions/
175240/
how-do-i-convert-a-files-format-from-unicode-to-ascii-using-python#175270).
By default, all strings are in Unicode.
I can almost guarantee that you will be using strings in almost every Python program that
you write, so pay attention to the following part on how to use strings in Python.
26
Python en:Basics
27
Single Quotes
You can specify strings using single quotes such as ' Q u o t e
i.e. spaces and tabs are preserved as-is.
me
on
t h i s ' . All white space
Double Quotes
Strings in double quotes work exactly the same way as strings in single quotes. An example
is " W h a t ' s y o u r n a m e ? "
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:
'
T
"
H
'
'
h
W
e
'
'This
is is
hat's
said
'
i
t
y
"
s
h
o
B
a m
e se
ur n
ond,
ulti
cond
ame?
Jam
-l
l
,"
es
ine
ine
I
Bo
string. This is the first line.
.
asked.
nd."
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 W h a t ' s y o u r n a m e ? . You cannot specify ' W h a t ' s
y o u r n a m e ? ' 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 ' W h a t \ ' s y o u r
name?'.
Another way of specifying this specific string would be " W h a t ' s y o u r n a m e ? " 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 T h i s i s t h e f i r s t l i n e \ n T h i s i s t h e
s e c o n d l i n e . 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 " T h i s i s t h e f i r s t s e n t e n c e . T h i s i s t h e s e c o n d s e n t e n c e . " .
Python en:Basics
Raw Strings
If you need to specify some strings where no special processing such as escape sequences
are handled, then what you need is to specify a raw string by prefixing r or R to the string.
An example is r " N e w l i n e s a r e i n d i c a t e d b y \ n " .
Strings Are Immutable
This means that once you have created a string, you cannot change it. Although this might
seem like a bad thing, it really isn't. We will see why this is not a limitation in the various
programs that we see later on.
String Literal Concatenation
If you place two string literals side by side, they are automatically concatenated by Python.
For example, ' W h a t \ ' s ' ' y o u r n a m e ? ' is automatically converted in to " W h a t ' s y o u r
name?".
Note for C/C++ Programmers
There is no separate c h a r 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.
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 ' .
The format Method
Sometimes we may want to construct strings from other information. This is where the
f o r m a t ( ) method is useful.
#!/usr/bin/python
# Filename: str_format.py
age = 25
name = 'Swaroop'
print('{0} is {1} years old'.format(name, age))
print('Why is {0} playing with that python?'.format(name))
Output:
$ python str_format.py
Swaroop is 25 years old
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 f o r m a t method.
28
Python en:Basics
29
Observe the first usage where we use { 0 } and this corresponds to the variable n a m e which
is the first argument to the format method. Similarly, the second specification is { 1 }
corresponding to a g e which is the second argument to the format method.
Notice that we could achieved the same using string concatenation: n a m e + ' i s ' +
s t r ( a g e ) + ' y e a r s o l d ' but notice how much uglier and error-prone this is. Second, the
conversion to string would be done automatically by the f o r m a t method instead of the
explicit conversion here. Third, when using the f o r m a t method, we can change the
message without having to deal with the variables used and vice-versa.
What Python does in the f o r m a t method is that it substitutes each argument value into the
place of the specification. There can be more detailed specifications such as:
>
'
>
c
'
>
#
>
0
>
e
_
>
>
.
>
n
_
>
k
'
33
'
te
_h
'
ey
{
3
{
r
e
{
w
0
'
0
e
l
n
o
:.3}'.format(1/3) # decimal (.) precision of 3 for float
:
d
l
a
r
_^
(
o_
me
d-
1
^
_
}
b
1}'
) t
_'
wr
ase
.format('hello') # fill with underscores (_) with the text
o 11 width
ote {book}'.format(name='Swaroop', book='A Byte of Python')
d
'Swaroop wrote A Byte of Python'
Details of this formatting specification is explained in the Python Enhancement Proposal
No. 3101 (http:/ / www. python. org/ dev/ peps/ pep-3101/ ).
Variables
Using just literal constants can soon become boring - we need some way of storing any
information and manipulate them as well. This is where variables come into the picture.
Variables are exactly what 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.
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 (uppercase 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, m y n a m e and m y N a m e 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 , _ _ m y _ n a m e , n a m e _ 2 3 , a 1 b 2 _ c 3 and
resumé_count.
• Examples of invalid identifier names are 2 t h i n g s , t h i s i s s p a c e d o u t , m y - n a m e , and
"this_is_in_quotes".
Python en:Basics
Data Types
Variables can hold values of different types called data types. The basic types are numbers
and strings, which we have already discussed. In later chapters, we will see how to create
our own types using classes.
Objects
Remember, Python refers to anything used in a program as an object. This is meant in the
generic sense. Instead of saying 'the something', we say 'the object'.
Note for Object Oriented Programming users
Python is strongly object-oriented in the sense that everything is an object including
numbers, strings and functions.
We will now see how to use variables along with literal constants. Save the following
example and run the program.
How to write Python programs
Henceforth, the standard procedure to save and run a Python program is as follows:
1. Open your favorite editor.
1. Enter the program code given in the example.
1. Save it as a file with the filename mentioned in the comment. I follow the convention
of having all Python programs saved with the extension . p y .
1. Run the interpreter with the command p y t h o n p r o g r a m . p y or use IDLE to run the
programs. You can also use the executable method as explained earlier.
Example: Using Variables And Literal Constants
# Filename : var.py
i
p
i
p
=
ri
=
ri
5
nt(i)
i + 1
nt(i)
s = '''This is a multi-line string.
This is the second line.'''
print(s)
Output:
$ python var.py
5
6
This is a multi-line string.
This is the second line.
How It Works:
Here's how this program works. First, we assign the literal constant value 5 to the variable
i using the assignment operator (= ). This line is called a statement because it states that
30
Python en:Basics
31
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 p r i n t statement 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.
Logical And Physical Lines
A physical line is what you see when you write the program. A logical line is what Python
sees as a single statement. Python implicitly assumes that each physical line corresponds to
a logical line.
An example of a logical line is a statement like p r i n t ( ' H e l l o W o r l d ' ) - 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
i = 5;
print(i);
and the same can be written as
i = 5; print(i);
or even
i = 5; print(i)
However, I strongly recommend that you stick to writing a single logical line in
single physical line only. Use more than one physical line for a single logical line only
the logical line is really long. The idea is to avoid the semicolon as much as possible since
leads to more readable code. In fact, I have never used or even seen a semicolon in
Python program.
a
if
it
a
An example of writing a logical line spanning many physical lines follows. This is referred to
as explicit line joining.
s = 'This is a string. \
This continues the string.'
print(s)
Python en:Basics
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 uses parentheses, square brackets or curly braces. This is is
called implicit line joining. You can see this in action when we write programs using lists
in later chapters.
Indentation
Whitespace is important in Python. Actually, whitespace at the beginning of the line is
important. This is called indentation. Leading whitespace (spaces and tabs) at the
beginning of the logical line is used to determine the indentation level of the logical line,
which in turn is used to determine the 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 =
pr
the
pri
5
int('Value is ', i) # Error! Notice a single space at the start of
line
nt('I repeat, the value is ', i)
When you run this, you get the following error:
Fil
p
start of
^
Inden
e "whitespace.py", line 4
rint('Value is ', i) # Error! Notice a single space at the
the line
tationError: 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 chapter.
How to indent
Do not use a mixture of tabs and spaces for the indentation as it does not work across
different platforms properly. I strongly recommend that you use a single tab or four
32
Python en:Basics
33
spaces for each indentation level.
Choose either of these two indentation styles. More importantly, choose one and use it
consistently i.e. use that indentation style only.
Note to static language programmers
Python will always use indentation for blocks and will never use braces. Run f r o m
_ _ f u t u r e _ _ i m p o r t b r a c e s to learn more.
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.
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Python en:Operators and Expressions
Introduction
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.
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:
>
5
>
1
>
>> 2 + 3
>> 3 * 5
5
>>
Operator
Name
Explanation
Examples
+
Plus
Adds the two objects
3 + 5 gives 8 . ' a ' + ' b ' gives ' a b ' .
-
Minus
Either gives a negative
number or gives the
subtraction of one number
from the other
- 5 . 2 gives a negative number. 5 0 - 2 4 gives 2 6 .
Python en:Operators and Expressions
34
*
Multiply
Gives the multiplication of the
two numbers or returns the
string repeated that many
times.
2 * 3 gives 6 . ' l a ' * 3 gives ' l a l a l a ' .
**
Power
Returns x to the power of y
3 * * 4 gives 8 1 (i.e. 3 * 3 * 3 * 3 )
/
Divide
Divide x by y
4 / 3 gives 1 . 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 .
//
Floor Division Returns the floor of the
quotient
4 / / 3 gives 1 .
%
Modulo
Returns the remainder of the
division
8 % 3 gives 2 . - 2 5 . 5 % 2 . 2 5 gives 1 . 5 .
<<
Left Shift
Shifts the bits of the number
2 < < 2 gives 8 . 2 is represented by 1 0 in bits. Left
to the left by the number of
shifting by 2 bits gives 1 0 0 0 which represents the
bits specified. (Each number is decimal 8 .
represented in memory by bits
or binary digits i.e. 0 and 1)
>>
Right Shift
Shifts the bits of the number
to the right by the number of
bits specified.
1 1 > > 1 gives 5 . 1 1 is represented in bits by 1 0 1 1
which when right shifted by 1 bit gives 1 0 1 which is
the decimal 5 .
&
Bitwise AND
Bitwise AND of the numbers
5 & 3 gives 1 .
|
Bit-wise OR
Bitwise OR of the numbers
5 | 3 gives 7
^
Bit-wise XOR
Bitwise XOR of the numbers
5 ^ 3 gives 6
~
Bit-wise
invert
The bit-wise inversion of x is
-(x+1)
~ 5 gives - 6 .
<
Less Than
Returns whether x is less than
y. All comparison operators
return T r u e or F a l s e . Note
the capitalization of these
names.
5 < 3 gives F a l s e and 3 < 5 gives T r u e .
Comparisons can be chained arbitrarily: 3 < 5 < 7
gives T r u e .
>
Greater Than
Returns whether x is greater
than y
5 > 3 returns T r u e . If both operands are numbers,
they are first converted to a common type.
Otherwise, it always returns F a l s e .
<=
Less Than or
Equal To
Returns whether x is less than
or equal to y
x = 3 ; y = 6 ; x < = y returns T r u e .
>=
Greater Than
or Equal To
Returns whether x is greater
than or equal to y
x = 4 ; y = 3 ; x > = 3 returns T r u e .
==
Equal To
Compares if the objects are
equal
x = 2 ; y = 2 ; x = = y returns T r u e .
x = ' s t r ' ; y = ' s t R ' ; x = = y returns F a l s e .
x = ' s t r ' ; y = ' s t r ' ; x = = y returns T r u e .
x = 2 ; y = 3 ; x ! = y returns T r u e .
!=
Not Equal To
Compares if the objects are
not equal
not
Boolean NOT
If x is T r u e , it returns F a l s e . If x = T r u e ; n o t x returns F a l s e .
x is F a l s e , it returns T r u e .
and
Boolean AND
x a n d y returns F a l s e if x is
F a l s e , else it returns
evaluation of y
x = F a l s e ; y = T r u e ; x a n d y returns F a l s e
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 F a l s e which implies that the whole
expression will be F a l s e irrespective of the other
values. This is called short-circuit evaluation.
Python en:Operators and Expressions
or
Boolean OR
35
If x is T r u e , it returns True,
else it returns evaluation of y
x = T r u e ; y = F a l s e ; x o r y returns T r u e .
Short-circuit evaluation applies here as well.
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 v a r = v a r o p e r a t i o n e x p r e s s i o n becomes v a r o p e r a t i o n = e x p r e s s i o n .
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 (http:/ / docs. python. org/
dev/ 3. 0/ reference/ expressions. html#evaluation-order), 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.
Operator
Description
lambda
Lambda Expression
or
Boolean OR
and
Boolean AND
not x
Boolean NOT
in, not in
Membership tests
is, is not
Identity tests
<, <=, >, >=, !=, ==
Comparisons
|
Bitwise OR
^
Bitwise XOR
&
Bitwise AND
<<, >>
Shifts
+, -
Addition and subtraction
*, /, //, %
Multiplication, Division, Floor Division and Remainder
+x, -x
Positive, Negative
Python en:Operators and Expressions
36
~x
Bitwise NOT
**
Exponentiation
x.attribute
Attribute reference
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.
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 .
Associativity
Operators are usually associated from left to right i.e. operators with same precedence are
evaluated in a left to right manner. For example, 2 + 3 + 4 is evaluated as ( 2 + 3 ) + 4 .
Some operators like assignment operators have right to left associativity i.e. a = b = c is
treated as a = ( b = c ) .
Expressions
Example:
#!/usr/bin/python
# Filename: expression.py
length = 5
breadth = 2
area = length * breadth
print('Area is', area)
print('Perimeter is', 2 * (length + breadth))
Output:
Python en:Operators and Expressions
$ python expression.py
Area is 10
Perimeter is 14
How It Works:
The length and breadth of the rectangle are stored in variables by the same name. We use
these to calculate the area and perimeter of the rectangle with the help of expressions. We
store the result of the expression l e n g t h * b r e a d t h in the variable a r e a and then print it
using the p r i n t function. In the second case, we directly use the value of the expression 2
* ( l e n g t h + b r e a d t h ) in the print function.
Also, notice how Python 'pretty-prints' the output. Even though we have not specified a
space between ' A r e a i s ' and the variable a r e a , 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.
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.
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Contributors: Swaroop, 4 anonymous edits
37
Python en:Control Flow
38
Python en:Control Flow
Introduction
In the programs we have seen till now, there has always been a series of statements and
Python faithfully executes them in the same 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 - i f , f o r and w h i l e .
The if statement
The i f statement is used to check a condition and if the condition is true, we run a block of
statements (called the if-block), else we process another block of statements (called the
else-block). The else clause is optional.
Example:
#!/usr/bin/python
# Filename: if.py
number = 23
guess = int(input('Enter an integer : '))
if gu
p
p
elif
p
#
else:
p
#
e
r
r
g
r
s
i
i
u
i
Y
s
n
n
e
n
o
=
(
(
s
(
= num
t 'Cong
t '(but
s
< nu
t 'No,
u can d
ber
rat
yo
mbe
it
o w
:
u
u
r
i
h
la
d
:
s
at
tions, you guessed it.') # New block starts here
o not win any prizes!)') # New block ends here
a little higher than that') # Another block
ever you want in a block ...
rint('No, it is a little lower than that')
you must have guess > number to reach here
print('Done')
# This last statement is always executed, after the if statement is
executed
Output:
$
E
N
D
p
nt
o,
on
ython if.py
er an integer : 50
it is a little lower than that
e
$ python if.py
Enter an integer : 22
Python en:Control Flow
No, it is a little higher than that
Done
$
E
C
(
D
n
o
b
o
p
t
n
u
n
y
e
g
t
e
thon
r an
ratu
you
i
i
la
d
f
n
t
o
.py
teger : 23
ions, you guessed it.
not win any prizes!)
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 n u m b e r to any integer we want, say 2 3 . Then, we take the user's guess
using the i n p u t ( ) 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 i n p u t function which prints it to the screen and waits for
input from the user. Once we enter something and press e n t e r key, the i n p u t ( ) function
returns what we entered, as a string. We then convert this string to an integer using i n t
and then store it in the variable g u e s s . Actually, the i n t is a class but all you need to know
right now is that you can use it to convert a string to an integer (assuming the string
contains a valid integer in the text).
Next, we compare the guess of the user with the number we have chosen. If they are equal,
we print a success message. Notice that we use indentation levels to tell Python which
statements belong to which block. This is why indentation is so important in Python. I hope
you are sticking to the "consistent indentation" rule. Are you?
Notice how the i f statement contains a colon at the end - we are indicating to Python that
a block of statements follows.
Then, we check if the guess is less than the number, and if so, we inform the user to guess
a little higher than that. What we have used here is the e l i f clause which actually
combines two related i f e l s e - i f e l s e statements into one combined i f - e l i f - e l s e
statement. This makes the program easier and reduces the amount of indentation required.
The e l i f and e l s e 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 i f statement inside the if-block of an i f statement and so on - this is
called a nested i f statement.
Remember that the e l i f and e l s e parts are optional. A minimal valid i f statement is:
if True:
print('Yes, it is true')
After Python has finished executing the complete i f statement along with the associated
e l i f and e l s e clauses, it moves on to the next statement in the block containing the i f
statement. In this case, it is the main block where execution of the program starts and the
next statement is the p r i n t ( ' D o n e ' ) statement. After this, Python sees the ends of the
program and simply finishes up.
Although this is a very simple program, I have been pointing out a lot of things that you
should notice even in this simple program. All these are pretty straightforward (and
surprisingly simple for those of you from C/C++ backgrounds) and requires you to become
39
Python en:Control Flow
40
aware of all these initially, but after that, you will become comfortable with it and it'll feel
'natural' to you.
Note for C/C++ Programmers
There is no s w i t c h statement in Python. You can use an i f . . e l i f . . e l s e statement to
do the same thing (and in some cases, use a dictionary to do it quickly)
The while Statement
The w h i l e statement allows you to repeatedly execute a block of statements as long as a
condition is true. A w h i l e statement is an example of what is called a looping statement. A
w h i l e statement can have an optional e l s e clause.
Example:
#!/usr/bin/python
# Filename: while.py
number = 23
running = True
while running:
guess = int(input('Enter an integer : '))
if gu
p
r
elif
p
else:
p
else:
print
# Do
e
r
u
g
r
s
i
n
u
i
s
n
n
e
n
=
(
n
s
(
= num
t 'Cong
i g = F
s
< nu
t 'No,
b
r
a
m
i
e
a
l
b
t
r
t
s
e
:
u
e
r
i
lations, you guessed it.')
# this causes the while loop to stop
:
s a little higher than that.')
rint('No, it is a little lower than that.')
('The while loop is over.')
anything else you want to do here
print('Done')
Output:
$
E
N
E
N
E
C
T
D
p
t
,
t
,
t
n
e
n
ytho
n er a
o
it
n er a
o
it
n er a
o grat
h
whi
o e
n
n
i
n
i
n
u
l
s
s
l
e
How It Works:
whi
int
a
int
a
int
ati
lo
l
e
l
e
l
e
o
o
e
g
i
g
i
g
n
p
.
e
t
e
t
e
s
p
r
t
r
t
r
,
i
y
:
le
:
le
:
y
s
5
l
2
h
2
ou
ov
0
ower than that.
2
igher than that.
3
guessed it.
er.
Python en:Control Flow
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 w h i l e statement.
We move the i n p u t and i f statements to inside the w h i l e loop and set the variable
r u n n i n g to T r u e before the while loop. First, we check if the variable r u n n i n g is T r u e 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 r u n n i n g 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 e l s e block is executed when the w h i l e loop condition becomes F a l s e - this may even
be the first time that the condition is checked. If there is an e l s e clause for a w h i l e loop,
it is always executed unless you break out of the loop with a b r e a k statement.
The T r u e and F a l s e are called Boolean types and you can consider them to be equivalent
to the value 1 and 0 respectively.
Note for C/C++ Programmers
Remember that you can have an e l s e clause for the w h i l e loop.
The for loop
The f o r . . i n 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:
#!/usr/bin/python
# Filename: for.py
for i in range(1, 5):
print(i)
else:
print('The for loop is over')
Output:
$ python for.py
1
2
3
4
The for loop is over
How It Works:
In this program, we are printing a sequence of numbers. We generate this sequence of
numbers using the built-in r a n g e function.
What we do here is supply it two numbers and r a n g e returns a sequence of numbers
starting from the first number and up to the second number. For example, r a n g e ( 1 , 5 )
41
Python en:Control Flow
42
gives the sequence [ 1 , 2 , 3 , 4 ] . By default, r a n g e takes a step count of 1. If we supply a
third number to r a n g e , then that becomes the step count. For example, r a n g e ( 1 , 5 , 2 )
gives [ 1 , 3 ] . Remember that the range extends up to the second number i.e. it does not
include the second number.
The f o r loop then iterates over this range - f o r i i n r a n g e ( 1 , 5 ) is equivalent to f o r i
i n [ 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 e l s e part is optional. When included, it is always executed once after
the f o r loop is over unless a break statement is encountered.
Remember that the f o r . . i n loop works for any sequence. Here, we have a list of numbers
generated by the built-in r a n g e 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 f o r loop is radically different from the C/C++ f o r loop. C# programmers
will note that the f o r loop in Python is similar to the f o r e a c h loop in C#. Java
programmers will note that the same is similar to f o r ( i n t i : I n t A r r a y ) in Java
1.5 .
In C/C++, if you want to write f o r ( i n t i = 0 ; i < 5 ; i + + ) , then in Python you
write just f o r i i n r a n g e ( 0 , 5 ) . As you can see, the f o r loop is simpler, more
expressive and less error prone in Python.
The break Statement
The b r e a k 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 F a l s e or the sequence of
items has been completely iterated over.
An important note is that if you break out of a f o r or w h i l e loop, any corresponding loop
e l s e block is not executed.
Example:
#!/usr/bin/python
# Filename: break.py
while True
s = (i
if s =
br
print(
print('Don
:
n
=
e
'
e
put('Enter something : '))
'quit':
ak
Length of the string is', len(s))
')
Output:
$
E
L
E
L
n
e
n
e
p
t
n
t
n
y
e
g
e
g
t
r
t
r
t
ho
s
h
s
h
n
o
o
o
o
m
f
m
f
bre
eth
th
eth
th
a
i
e
i
e
k.py
ng :
str
ng :
str
P
in
W
in
r
g
h
g
og
i
en
i
ram
s 1
th
s 2
ming is fun
8
e work is done
1
Python en:Control Flow
E
L
E
L
E
D
n
e
n
e
n
o
t
n
t
n
t
n
e
g
e
g
e
e
r
t
r
t
r
so
h o
so
h o
so
m
f
m
f
m
et
t
et
t
et
h
h
h
h
h
i
e
i
e
i
43
ng
s
ng
s
ng
:
tr
:
tr
:
if you
ing is 3
u
ing is 1
quit
wanna make your work also fun:
7
se Python!
2
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 ' q u i t ' . 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 l e n function.
Remember that the b r e a k statement can be used with the f o r loop as well.
Swaroop's Poetic Python
The input I have used here is a mini poem I have written called Swaroop's Poetic Python:
Programm
When the
if you w
use
in
w
an
Py
g
o
n
t
is fun
rk is done
a make your work also fun:
hon!
The continue Statement
The c o n t i n u e 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:
#!/usr/bin/python
# Filename: continue.py
while True
s = in
if s =
br
if len
pr
co
print(
# Do o
:
p
=
e
(
i
n
'
t
ut
'
ak
s)
nt
ti
In
he
('Enter something : ')
quit':
<
('
nu
pu
r
3:
Too small')
e
t is of sufficient length')
kinds of processing here...
Output:
$
E
T
E
T
n
o
n
o
p
t
o
t
o
ytho
er s
sma
er s
sma
n
o
l
o
l
test.py
mething : a
l
mething : 12
l
Python en:Control Flow
Enter something : abc
Input is of sufficient length
Enter something : quit
How It Works:
In this program, we accept input from the user, but we process them only if they are at
least 3 characters long. So, we use the built-in l e n 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 c o n t i n u e
statement. Otherwise, the rest of the statements in the loop are executed and we can do
any kind of processing we want to do here.
Note that the c o n t i n u e statement works with the f o r loop as well.
Summary
We have seen how to use the three control flow statements - i f , w h i l e and f o r along with
their associated b r e a k and c o n t i n u e statements. These are some of the most often used
parts of Python and hence, becoming comfortable with them is essential.
Next, we will see how to create and use functions.
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Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=1664
Contributors: Swaroop, 8 anonymous edits
Python en:Functions
Introduction
Functions are reusable pieces of programs. They allow you to give a name to a block of
statements and you can run that block using that name anywhere in your program and any
number of times. This is known as calling the function. We have already used many built-in
functions such as the l e n and r a n g e .
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 d e f keyword. This is followed by an identifier name for the
function followed by a pair of parentheses which may enclose some names of variables and
the line ends with a colon. Next follows the block of statements that are part of this
function. An example will show that this is actually very simple:
Example:
#!/usr/bin/python
# Filename: function1.py
def sayHello():
print('Hello World!') # block belonging to the function
# End of function
44
Python en:Functions
sayHello() # call the function
sayHello() # call the function again
Output:
$ python function1.py
Hello World!
Hello World!
How It Works:
We define a function called s a y H e l l o 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.
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.
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:
#!/usr/bin/python
# Filename: func_param.py
def printM
if a >
pr
elif a
pr
else:
pr
ax
b
in
=
in
(
:
t
=
t
a, b):
(a, 'is maximum')
b:
(a, 'is equal to', b)
int(b, 'is maximum')
printMax(3, 4) # directly give literal values
x = 5
y = 7
printMax(x, y) # give variables as arguments
Output:
45
Python en:Functions
$ python func_param.py
4 is maximum
7 is maximum
How It Works:
Here, we define a function called p r i n t M a x where we take two parameters called a and b .
We find out the greater number using a simple i f . . e l s e statement and then print the
bigger number.
In the first usage of p r i n t M a x , we directly supply the numbers i.e. arguments. In the second
usage, we call the function using variables. p r i n t M a x ( x , y ) causes value of argument x to
be assigned to parameter a and the value of argument y assigned to parameter b . The
printMax function works the same in both the cases.
Local Variables
When you declare variables inside a function definition, they are not related in any way to
other variables with the same names used outside the function i.e. variable names are local
to the function. This is called the scope of the variable. All variables have the scope of the
block they are declared in starting from the point of definition of the name.
Example:
#!/usr/bin/python
# Filename: func_local.py
x = 50
def f
p
x
p
unc
rin
=
rin
(x):
t('x is', x)
2
t('Changed local x to', x)
func(x)
print('x is still', x)
Output:
$
x
C
x
p
i
ha
i
y
s
n
s
th
5
ge
s
on func_local.py
0
d local x to 2
till 50
How It Works:
In the function, the first time that we use the value of the name x , Python uses the value of
the parameter declared in the function.
Next, we assign the value 2 to x . The name x is local to our function. So, when we change
the value of x in the function, the x defined in the main block remains unaffected.
In the last p r i n t function call, we display the value of x in the main block and confirm that
it is actually unaffected.
46
Python en:Functions
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 g l o b a l statement. It is impossible to
assign a value to a variable defined outside a function without the g l o b a l statement.
You can use the values of such variables defined outside the function (assuming there is no
variable with the same name within the function). However, this is not encouraged and
should be avoided since it becomes unclear to the reader of the program as to where that
variable's definition is. Using the g l o b a l statement makes it amply clear that the variable
is defined in an outermost block.
Example:
#!/usr/bin/python
# Filename: 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:
$
x
C
V
p
i
ha
al
y
s
n
u
th
5
ge
e
on func_global.py
0
d global x to 2
of x is 2
How It Works:
The g l o b a l 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 g l o b a l statement. For
example, g l o b a l x , y , z .
47
Python en:Functions
Using nonlocal statement
We have seen how to access variables in the local and global scope above. There is another
kind of scope called "nonlocal" scope which is in-between these two types of scopes.
Nonlocal scopes are observed when you define functions inside functions.
Since everything in Python is just executable code, you can define functions anywhere.
Let's take an example:
#!/usr/bin/python
# Filename: func_nonlocal.py
def func_outer():
x = 2
print('x is', x)
def func_inner():
nonlocal x
x = 5
func_inner()
print('Changed local x to', x)
func_outer()
Output:
$ python func_nonlocal.py
x is 2
Changed local x to 5
How It Works:
When we are inside f u n c _ i n n e r , the 'x' defined in the first line of f u n c _ o u t e r is relatively
neither in local scope nor in global scope. We declare that we are using this x by n o n l o c a l
x and hence we get access to that variable.
Try changing the n o n l o c a l x to g l o b a l x and also by removing the statement itself and
observe the difference in behavior in these two cases.
Default Argument Values
For some functions, you may want to make some of its parameters as optional and use
default values if the user does not want to provide values for such parameters. This is done
with the help of default argument values. You can specify default argument values for
parameters by following the parameter name in the function definition with the assignment
operator (= ) followed by the default value.
Note that the default argument value should be a constant. More precisely, the default
argument value should be immutable - this is explained in detail in later chapters. For now,
just remember this.
Example:
48
Python en:Functions
#!/usr/bin/python
# Filename: func_default.py
def say(message, times = 1):
print(message * times)
say('Hello')
say('World', 5)
Output:
$ python func_default.py
Hello
WorldWorldWorldWorldWorld
How It Works:
The function named s a y 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 t i m e s .
In the first usage of s a y , we supply only the string and it prints the string once. In the
second usage of s a y , we supply both the string and an argument 5 stating that we want to
say the string message 5 times.
Important
Only those parameters which are at the end of the parameter list can be given default
argument values i.e. you cannot have a parameter with a default argument value
before a parameter without a default argument value in the order of parameters
declared in the function parameter list.
This is because the values are assigned to the parameters by position. For example,
d e f f u n c ( a , b = 5 ) is valid, but d e f f u n c ( a = 5 , b ) is not valid.
Keyword Arguments
If you have some functions with many parameters and you want to specify only some of
them, then you can give values for such parameters by naming them - this is called keyword
arguments - we use the name (keyword) instead of the position (which we have been using
all along) to specify the arguments to the function.
There are two advantages - one, using the function is easier since we do not need to worry
about the order of the arguments. Two, we can give values to only those parameters which
we want, provided that the other parameters have default argument values.
Example:
#!/usr/bin/python
# Filename: func_key.py
def func(a, b=5, c=10):
print('a is', a, 'and b is', b, 'and c is', c)
func(3, 7)
49
Python en:Functions
50
func(25, c=24)
func(c=50, a=100)
Output:
$
a
a
a
p
i
i
i
y
s
s
s
th
3
2
1
on
a
5
00
f
nd
an
a
un
b
d
nd
c_
i
b
b
key.
s 7
is 5
is
py
and c is 10
and c is 24
5 and c is 50
How It Works:
The function named f u n c has one parameter without default argument values, followed by
two parameters with default argument values.
In the first usage, f u n c ( 3 , 7 ) , the parameter a gets the value 3 , the parameter b gets the
value 7 and c gets the default value of 1 0 .
In the second usage f u n c ( 2 5 , c = 2 4 ) , the variable a gets the value of 25 due to the position
of the argument. Then, the parameter c gets the value of 2 4 due to naming i.e. keyword
arguments. The variable b gets the default value of 5 .
In the third usage f u n c ( c = 5 0 , a = 1 0 0 ) , we use keyword arguments completely to specify
the values. Notice, that we are specifying value for parameter c before that for a even
though a is defined before c in the function definition.
VarArgs parameters
TODO
Should I write about this in a later chapter since we haven't talked about lists and
dictionaries yet?
Sometimes you might want to define a function that can take any number of parameters,
this can be achieved by using the stars:
#!/usr/bin/python
# Filename: total.py
def total
count
for n
c
for k
c
retur
(i
=
um
ou
ey
ou
n
ni
i
be
nt
i
nt
co
tial
niti
r in
+=
n ke
+=
unt
=5
al
n
nu
yw
ke
, *numbers, **keywords):
u
m
o
y
m
b
r
w
b
e
d
o
ers:
r
s:
rds[key]
print(total(10, 1, 2, 3, vegetables=50, fruits=100))
Output:
$ python total.py
166
How It Works:
Python en:Functions
51
When we declare a starred parameter such as * p a r a m , then all the positional arguments
from that point till the end are collected as a list called 'param'.
Similarly, when we declare a double-starred parameter such as * * p a r a m , then all the
keyword arguments from that point till the end are collected as a dictionary called 'param'.
We will explore lists and dictionaries in a later chapter.
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:
#!/usr/bin/python
# Filename: keyword_only.py
def total
count
for n
c
count
(i
=
um
ou
ni
i
be
nt
tial
niti
r in
+=
=5, *numbers, vegetables):
al
numbers:
number
+= vegetables
return count
p
p
#
f
rin
rin
Ra
or
t
t
i
'
(
(
s
v
t
t
e
e
o
o
s
g
tal
tal
er
eta
(
(
r
b
1
1
o
l
0
0
r
e
, 1, 2, 3, vegetables=50))
, 1, 2, 3))
because we have not supplied a default argument value
s'
Output:
$ py
66
Trac
Fi
prin
Type
thon keyword_only.py
e
l
t
E
b
e
(
r
ac
"
to
ro
k
t
t
r
(mos
est.p
al(10
: tot
t
y
,
a
r
",
1
l(
ec
l
,
)
e
i
2
n
n
n
,
e
t call last):
e 12, in <module>
3))
eds keyword-only argument vegetables
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.
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 d e f t o t a l ( i n i t i a l = 5 , * ,
vegetables).
Python en:Functions
The return Statement
The r e t u r n 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:
#!/usr/bin/python
# Filename: func_return.py
def maximu
if x >
re
else:
re
m(x, y):
y:
turn x
turn y
print(maximum(2, 3))
Output:
$ python func_return.py
3
How It Works:
The m a x i m u m function returns the maximum of the parameters, in this case the numbers
supplied to the function. It uses a simple i f . . e l s e statement to find the greater value and
then returns that value.
Note that a r e t u r n statement without a value is equivalent to r e t u r n N o n e . N o n e 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 N o n e .
Every function implicitly contains a r e t u r n N o n e statement at the end unless you have
written your own r e t u r n statement. You can see this by running p r i n t ( s o m e F u n c t i o n ( ) )
where the function s o m e F u n c t i o n does not use the r e t u r n statement such as:
def someFunction():
pass
The p a s s statement is used in Python to indicate an empty block of statements.
Note
There is a built-in function called m a x that already implements the 'find maximum'
functionality, so use this built-in function whenever possible.
52
Python en:Functions
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:
#!/usr/bin/python
# Filename: func_doc.py
def printMax(x, y):
'''Prints the maximum of two numbers.
The two values must be integers.'''
x = int(x) # convert to integers, if possible
y = int(y)
if x > y:
print(x, 'is maximum')
else:
print(y, 'is maximum')
printMax(3, 5)
print(printMax.__doc__)
Output:
$ python func_doc.py
5 is maximum
Prints the maximum of two numbers.
The two values must be integers.
How It Works:
A string on the first logical line of a function is the docstring for that function. Note that
DocStrings also apply to modules and classes which we will learn about in the respective
chapters.
The convention followed for a docstring is a multi-line string where the first line starts with
a capital letter and ends with a dot. Then the second line is blank followed by any detailed
explanation starting from the third line. You are strongly advised to follow this convention
for all your docstrings for all your non-trivial functions.
We can access the docstring of the p r i n t M a x function using the _ _ d o c _ _ (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 h e l p ( ) in Python, then you have already seen the usage of docstrings!
What it does is just fetch the _ _ d o c _ _ attribute of that function and displays it in a neat
manner for you. You can try it out on the function above - just include h e l p ( p r i n t M a x ) in
53
Python en:Functions
your program. Remember to press the q key to exit h e l p .
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 p y d o c command that comes with your Python distribution works similarly to
h e l p ( ) using docstrings.
Annotations
Functions have another advanced feature called annotations which are a nifty way of
attaching additional information for each of the parameters as well as the return value.
Since the Python language itself does not interpret these annotations in any way (that
functionality is left to third-party libraries to interpret in any way they want), we will skip
this feature in our discussion. If you are interested to read about annotations, please see
the Python Enhancement Proposal No. 3107 (http:/ / www. python. org/ dev/ peps/
pep-3107/ ).
Summary
We have seen so many aspects of functions but note that we still haven't covered all aspects
of it. However, we have already covered most of what you'll use regarding Python functions
on an everyday basis.
Next, we will see how to use as well as create Python modules.
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54
Python en:Modules
55
Python en:Modules
Introduction
You have seen how you can reuse code in your program by defining functions once. What if
you wanted to reuse a number of functions in other programs that you write? As you might
have guessed, the answer is modules.
There are various methods of writing modules, but the simplest way is to create a file with a
. p y 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 (http:/ / docs. python. org/ extending/ ) 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:
#!/usr/bin/python
# Filename: using_sys.py
import sys
print('The command line arguments are:')
for i in sys.argv:
print(i)
print('\n\nThe PYTHONPATH is', sys.path, '\n')
Output:
$
T
u
w
a
a
pyth
he co
sing_
e
re
rgume
on using_sys.py we are arguments
mmand line arguments are:
sys.py
T
'
'
'
h
C
C
C
T
y
y
y
e
:
:
:
P
\\
\\
\\
Y
P
P
P
nts
H
t
t
t
O
h
h
h
N
o
o
o
P
n
n
n
A
3
3
3
T
0
0
0
H
\
\
\
i
\D
\l
\l
s
L
i
i
[
Ls
b\
b\
'
'
\
\
'
,
p
s
, '
'C
lat
ite
C
:
-
:
\
w
p
\
\
i
a
\
P
n
c
W
y
'
k
i
t
,
a
ndo
hon
'C
ges
w
3
:
'
s\\system32\\python30.zip',
0\\lib',
\\Python30',
]
How It Works:
First, we import the s y s module using the i m p o r t statement. Basically, this translates to
us telling Python that we want to use this module. The s y s module contains functionality
related to the Python interpreter and its environment i.e. the system.
Python en:Modules
When Python executes the i m p o r t s y s statement, it looks for the s y s 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 s y s . p a t h variable. If the module is found,
then the statements in the body of that module is run and then the module is made
available for you to use. Note that the initialization is done only the first time that we
import a module.
The a r g v variable in the s y s module is accessed using the dotted notation i.e. s y s . a r g v . It
clearly indicates that this name is part of the s y s module. Another advantage of this
approach is that the name does not clash with any a r g v variable used in your program.
The s y s . a r g v variable is a list of strings (lists are explained in detail in a later chapter.
Specifically, the s y s . a r g v contains the list of command line arguments i.e. the arguments
passed to your program using the command line.
If you are using an IDE to write and run these programs, look for a way to specify command
line arguments to the program in the menus.
Here, when we execute p y t h o n u s i n g _ s y s . p y w e a r e a r g u m e n t s , we run the module
u s i n g _ s y s . p y with the p y t h o n command and the other things that follow are arguments
passed to the program. Python stores the command line arguments in the s y s . a r g v
variable for us to use.
Remember, the name of the script running is always the first argument in the s y s . a r g v
list. So, in this case we will have ' u s i n g _ s y s . p y ' as s y s . a r g v [ 0 ] , ' w e ' as s y s . a r g v [ 1 ] ,
' a r e ' as s y s . a r g v [ 2 ] and ' a r g u m e n t s ' as s y s . a r g v [ 3 ] . Notice that Python starts
counting from 0 and not 1.
The s y s . p a t h contains the list of directory names where modules are imported from.
Observe that the first string in s y s . p a t h is empty - this empty string indicates that the
current directory is also part of the s y s . p a t h which is same as the P Y T H O N P A T H
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 s y s . p a t h .
Note that the current directory is the directory from which the program is launched. Run
i m p o r t o s ; p r i n t ( o s . g e t c w d ( ) ) to find out the current directory of your program.
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 . p y c which is an intermediate
form that Python transforms the program into (remember the introduction section on how
Python works?). This . p y c 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 . p y c files are usually created in the same directory as the corresponding . p y
files. If Python does not have permission to write to files in that directory, then the
. p y c files will not be created.
56
Python en:Modules
The from ...import ...statement
If you want to directly import the a r g v variable into your program (to avoid typing the
s y s . everytime for it), then you can use the f r o m s y s i m p o r t a r g v statement. If you want
to import all the names used in the s y s module, then you can use the f r o m s y s i m p o r t *
statement. This works for any module.
In general, you should avoid using this statement and use the i m p o r t statement instead
since your program will avoid name clashes and will be more readable.
A module's __name__
Every module has a name and statements in a module can find out the name of its module.
This is handy in the particular situation of figuring out if the module is being run standalone
or being imported. As mentioned previously, when a module is imported for the first time,
the code in that module is executed. We can use this concept to alter the behavior of the
module if the program was used by itself and not when it was imported from another
module. This can be achieved using the _ _ n a m e _ _ attribute of the module.
Example:
#!/usr/bin/python
# Filename: using_name.py
if __name__ == '__main__':
print('This program is being run by itself')
else:
print('I am being imported from another module')
Output:
$ python using_name.py
This program is being run by itself
$
>
I
>
python
>> import using_name
am being imported from another module
>>
How It Works:
Every Python module has it's _ _ n a m e _ _ defined and if this is ' _ _ m a i n _ _ ' , it implies that the
module is being run standalone by the user and we can take appropriate actions.
57
Python en:Modules
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 . p y extension. The
following example should make it clear.
Example:
#!/usr/bin/python
# Filename: mymodule.py
def sayhi():
print('Hi, this is mymodule speaking.')
__version__ = '0.1'
# End of mymodule.py
The above was a sample module. As you can see, there is nothing particularly special about
compared to our usual Python program. We will next see how to use this module in our
other Python programs.
Remember that the module should be placed in the same directory as the program that we
import it in, or the module should be in one of the directories listed in s y s . p a t h .
#!/usr/bin/python
# Filename: mymodule_demo.py
import mymodule
mymodule.sayhi()
print ('Version', mymodule.__version__)
Output:
$ python mymodule_demo.py
Hi, this is mymodule speaking.
Version 0.1
How It Works:
Notice that we use the same dotted notation to access members of the module. Python
makes good reuse of the same notation to give the distinctive 'Pythonic' feel to it so that we
don't have to keep learning new ways to do things.
Here is a version utilising the f r o m . . i m p o r t syntax:
#!/usr/bin/python
# Filename: mymodule_demo2.py
from mymodule import sayhi, __version__
sayhi()
print('Version', __version__)
58
Python en:Modules
59
The output of m y m o d u l e _ d e m o 2 . p y is same as the output of m y m o d u l e _ d e m o . p y .
Notice that if there was already a _ _ v e r s i o n _ _ 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 i m p o r t statement even though it might make your program a little longer.
You could also use:
from mymodule import *
This will import all public names such as s a y h i but would not import _ _ v e r s i o n _ _
because it starts with double underscores.
Zen of Python
One of Python's guiding principles is that "Explicit is better than Implicit". Run i m p o r t
t h i s to learn more and see this discussion (http:/ / stackoverflow. com/ questions/
228181/ zen-of-python) which lists examples for each of the principles.
The dir function
You can use the built-in d i r 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 the d i r ( ) 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:
$ python
>>> import sys # get list of attributes, in this case, for the sys module
>
[
'
t
'
'
'
b
'
,
'
'
'
e
'
>
'
_
d
_
_
b
y
d
e
e
g
s
g
'
'm
',
>
_
_
e
c
c
u
t
l
'
x
x
e
y
e
g
a
_
p
r
o
u
i
e
l
d
e
i
t
s
t
e
x
'
d
d
a
r
m
r
l
o
h
o
c
t
d
t
s
t
u
m
i
i
c
_
p
r
t
r
a
n
u
'
e
e
i
t
n
e
r
s
k
_
a
e
i
d
n
t
t
,
f
m
z
r
i
t
(
p
a
'
c
n
n
e
d
_
a
a
e
e
a
c
a
s
l
g
,
t
t
_
r
l
w
b
'
u
n
o
c
o
_
ys)
ayho
e__'
'__
_fre
_fra
modu
', '
e'
rite
le',
flag
lten
codi
f',
e',
de
path
o
,
s
e
m
l
c
k_
'
td
li
es
e_
al
_
_
i
s
'
n
l
'
_
n
t
,
a
_
, '_
s
__',
s',
'_g
mes'
trac
_doc__', '__excepthook__', '__name__',
'__stdout__', '_clear_type_cache',
etframe', 'api_version', 'argv',
, '
ing', 'callstats', 'copyright', 'displayhook',
_bytecode', 'exc_info', 'excepthook', 'exec_prefix',
s', 'float_info', 'getcheckinterval',
coding', 'getfil
ng', 'getprofile', 'getrecursionlimit', 'getrefcount',
'getwindowsversion', 'hexversion', 'intern', 'maxsize',
', 'modules', 'path', 'path_hooks', 'path_importer_cache',
Python en:Modules
'
'
s
,
v
o
plat
m , 'p
' etre
'
'se
' ersi
f ', '
f
r
c
t
o
w
o
e
u
t
n
a
r
f
r
r
_
r
i
s
a
i
n
x
i
c
n
o
', 'ps1', 'ps2', 'setcheckinterval', 'setprofile',
onlimit
e', 'stderr', 'stdin', 'stdout', 'subversion', 'version',
ptions', 'winver']
>>> dir() # get list of attributes for current module
['__builtins__', '__doc__', '__name__', '__package__', 'sys']
>>> a = 5 # create a new variable 'a'
>>> dir()
['__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 d i r on the imported s y s module. We can see the huge list of
attributes that it contains.
Next, we use the d i r 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 d i r in action, we define a new variable a and assign it a value and
then check d i r and 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 d e l statement and
the change is reflected again in the output of the d i r function.
A note on d e l - this statement is used to delete a variable/name and after the statement
has run, in this case d e l a , you can no longer access the variable a - it is as if it never
existed before at all.
Note that the d i r ( ) function works on any object. For example, run d i r ( p r i n t ) to learn
about the attributes of the print function, or d i r ( s t r ) for the attributes of the str class.
60
Python en:Modules
61
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 _ _ i n i t _ _ . p y 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', 'madagascar', etc.
This is how you would structure the folders:
- <some fo
- worl
-
l
d
_
a
der
/
_ini
sia/
- _
- i
present in the sys.path>/
t__.py
_in
ndi
- africa/
- __in
- mada
-
i
a
_
f
t__.py
/
_init__.py
oo.py
i
g
_
b
t
a
_
a
_
s
i
r
_
c
n
.
.
a
i
p
py
r/
t__.py
y
Packages are just a convenience to hierarchically organize modules. You will see many
instances of this in the standard library.
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.
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Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=2371
Contributors: Swaroop, 7 anonymous edits
Python en:Data Structures
Python en:Data Structures
Introduction
Data structures are basically just that - they are structures which can hold some data
together. In other words, they are used to store a collection of related data.
There are 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.
List
A l i s t 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 or search for items
in the list. Since we can add and remove items, we say that a list is a mutable data type i.e.
this type can be altered.
Quick Introduction To Objects And Classes
Although I've been generally delaying the discussion of objects and classes till now, a little
explanation is needed right now so that you can understand lists better. We will explore this
topic in detail later in its own 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) i n t . In fact, you can read h e l p ( i n t ) 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 a p p e n d method for the l i s t class which allows you to add an
item to the end of the list. For example, m y l i s t . a p p e n d ( ' a n i t e m ' ) will add that string to
the list m y l i s t . 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, m y l i s t . f i e l d .
Example:
#!/usr/bin/python
# Filename: 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=' ')
62
Python en:Data Structures
63
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)
p
o
d
p
p
r
l
e
r
r
i
d
l
i
i
nt(
ite
sh
nt(
nt(
'
m
o
'
'
Th
=
pl
I
My
e f
sh
ist
bou
sh
i
o
[
g
o
r
p
0
h
p
s
l
]
t
p
t item I will buy is', shoplist[0])
ist[0]
y
a
s
l
s
hon
e 4
it
o h
opp
u
i
em
av
in
s
t
s
e
g
ing
ems
ar
to
li
the', olditem)
ing list is now', shoplist)
Output:
$
I
T
I
M
'rice
I
S
'rice
T
I
M
p
h
he
a
y
']
w
or
']
he
b
y
t
v
e
s
h
_l
t
e:
b
st
ist
o p
ap
uy
is
.
u
p
r
p
r
l
i
n
y
c
e
c
o
hase.
mango carrot banana
e.
w ['apple', 'mango', 'carrot', 'banana',
ill sort my list now
ted shopping list is ['apple', 'banana', 'carrot', 'mango',
first item I will buy is apple
ought the apple
shopping list is now ['banana', 'carrot', 'mango', 'rice']
How It Works:
The variable s h o p l i s t is a shopping list for someone who is going to the market. In
s h o p l i s t , 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 f o r . . i n 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 e n d keyword argument to the p r i n t 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 a p p e n d 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 p r i n t statement which
prints it neatly.
Then, we sort the list by using the s o r t 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
Python en:Data Structures
64
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 d e l statement. Here, we mention which item of the list we want
to remove and the d e l 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 d e l s h o p l i s t [ 0 ] (remember that
Python starts counting from 0).
If you want to know all the methods defined by the list object, see h e l p ( l i s t ) for details.
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:
#!/usr/bin/python
# Filename: using_tuple.py
zoo = ('python', 'elephant', 'penguin') # remember the parentheses are
optional
print('Number of animals in the zoo is', len(zoo))
n
p
p
p
p
p
l
e
r
r
r
r
r
e
w
i
i
i
i
i
n
_
n
n
n
n
n
(
z
t
t
t
t
t
n
o
(
(
(
(
(
e
o
'
'
'
'
'
w
N
A
A
L
N
_
=
u
l
n
a
u
z
('m
mber
l an
imal
st a
mber
oo)-
on
o
im
s
ni
o
1+
k
f
a
b
m
f
l
ey
c
ls
ro
al
a
en
',
age
in
ugh
br
nim
(ne
us
a
c
ls
pe
ro
al
a
ing_
nima
ages
in
ngui
ught
bro
nima
'ca
s i
ne
t f
oug
als
w_z
m
n
w
r
h
el
t
z
om
t
in
oo[
', zo
he ne
oo ar
old
from
the
2]))
o
w
e
z
o
n
)
'
o
l
e
z
,
o
d
w
oo
n
a
z
z
i
w
e
o
o
s',
e _zoo
r ', n
o
is'
o
is'
len(new_zoo))
)
ew_zoo[2])
, new_zoo[2][2])
,
Output:
$
N
N
A
'elep
A
L
N
p
m
m
l
a
i
s
m
ython
u ber o
u ber o
l
anim
h nt',
n mals
a t ani
u ber o
f
f
a
'
b
m
f
tupl
ls i
in
new
n'))
fro
ught
ls i
e
n
t
z
.p
t
he
oo
y
he zoo is 3
new zoo is 3
are ('monkey', 'camel', ('python',
m old zoo are ('python', 'elephant', 'penguin')
from old zoo is penguin
n the new zoo is 5
How It Works:
The variable z o o refers to a tuple of items. We see that the l e n function can be used to get
the length of the tuple. This also indicates that a tuple is a sequence as well.
Python en:Data Structures
We are now shifting these animals to a new zoo since the old zoo is being closed. Therefore,
the n e w _ z o o tuple contains some animals which are already there along with the animals
brought over from the old zoo. Back to reality, note that a tuple within a tuple does not lose
its identity.
We can access the items in the tuple by specifying the item's position within a pair of
square brackets just like we did for lists. This is called the indexing operator. We access the
third item in n e w _ z o o by specifying n e w _ z o o [ 2 ] and we access the third item within the
third item in the n e w _ z o o tuple by specifying n e w _ z o o [ 2 ] [ 2 ] . This is pretty simple once
you've understood the idiom.
Parentheses
Although the parentheses is optional, I prefer always having them to make it obvious
that it is a tuple, especially because it avoids ambiguity. For example, p r i n t ( 1 , 2 , 3 )
and p r i n t ( ( 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 m y e m p t y = ( ) .
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 s i n g l e t o n = ( 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.
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 = { k e y 1 :
v a l u e 1 , k e y 2 : v a l u e 2 } . 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.
The dictionaries that you will be using are instances/objects of the d i c t class.
Example:
#!/usr/bin/python
# Filename: using_dict.py
65
Python en:Data Structures
66
# 'ab' is short for 'a'ddress'b'ook
ab = {
'
'
'
'
S
L
M
S
w
a
a
p
a
r
t
a
r
r
s
m
o
y
u
m
op'
:
'
:
moto' :
er'
:
'
'
'
'
s
l
m
s
w
a
a
p
a
r
t
a
r
r
z
m
o
y
@
m
o
@
r
e
p
w
u
r
@
a
b
@
s
l
y
h
w
l
o
a
.
l
t
r
o
a
m
o
r
n
a
o
g
g
i
p
'
.
l
ch.com',
,
org',
.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'] = '[email protected]'
if 'Guido' in ab: # OR ab.has_key('Guido')
print("\nGuido's address is", ab['Guido'])
Output:
$ python using_dict.py
Swaroop's address is [email protected]
There are 3 contacts in the address-book
Contact Swaroop at [email protected]
Contact Matsumoto at [email protected]
Contact Larry at [email protected]
Guido's address is [email protected]
How It Works:
We create the dictionary a b 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.
We can delete key-value pairs using our old friend - the d e l statement. We simply specify
the dictionary and the indexing operator for the key to be removed and pass it to the d e l
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 i t e m s 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 n a m e and a d d r e s s
correspondingly for each pair using the f o r . . i n loop and then print these values in the
Python en:Data Structures
67
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 i n operator or even the h a s _ k e y method
of the d i c t class. You can see the documentation for the complete list of methods of the
d i c t class using h e l p ( d i c t ) .
Keyword Arguments and Dictionaries
On a different note, if you have used keyword arguments in your functions, you have
already used dictionaries! Just think about it - the key-value pair is specified by you in
the parameter list of the function definition and when you access variables within your
function, it is just a key access of a dictionary (which is called the symbol table in
compiler design terminology).
Sequences
Lists, tuples and strings are examples of sequences, but what are sequences and what is so
special about them?
The major features is that they have membership tests (i.e. the i n and n o t i n expressions)
and indexing operations. The indexing operation which allows 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:
#!/usr/bin/python
# Filename: seq.py
shoplist = ['apple', 'mango', 'carrot', 'banana']
name = 'swaroop'
#
p
p
p
p
p
p
p
#
p
p
p
p
r
r
r
r
r
r
r
I
i
i
i
i
i
i
i
n
n
n
n
n
n
n
n
d
t
t
t
t
t
t
t
e
(
(
(
(
(
(
(
x
'
'
'
'
'
'
'
i
I
I
I
I
I
I
C
n
t
t
t
t
t
t
h
r
r
r
r
S
i
i
i
i
l
n
n
n
n
i
t
t
t
t
c
(
(
(
(
i
'
'
'
'
n
I
I
I
I
g
t
t
t
t
g
e
e
e
e
e
e
a
m
m
m
m
m
m
r
or
0
1
2
3
ac
e
e
e
e
o
m
m
m
m
n a
1
2
1
st
'
i
i
i
i
S
s
s
s
s
1 i
2 i
ter
t
t
t
a
l
o
o
o
r
u
'
'
'
'
s
s
b
,
,
,
,
'
'
0
is
3
e
t
sc
s
s
s
s
,
,
i
r
h
h
h
h
s
s
s
i
o
o
o
o
h
h
'
p
p
p
p
p
o
o
,
t
l
l
l
l
p
p
i
i
i
i
i
l
l
n
o
s
s
s
s
i
i
a
n
t
t
t
t
s
s
m
'
[
[
[
[
t
t
e
0
1
2
3
[
[
[
o
]
]
]
]
0
p
)
)
)
)
1
2
]
eration
is'
nd i
1 is
to e
,
s
'
n
sho
', s
, sh
d is
p
h
o
'
l
o
p
,
ist[
plis
list
sho
])
])
)
t
# Slicing on a string
1
t
[
p
:
[
1
l
3
2
:
i
]
:
s
)
])
1])
t[:])
Python en:Data Structures
p
p
p
p
r
r
r
r
i
i
i
i
n
n
n
n
t
t
t
t
(
(
(
(
'
'
'
'
c
c
c
c
h
h
h
h
a
a
a
a
y
m
m
m
m
m
m
r
m
m
m
m
r
r
r
r
th
0
1
2
3
ac
1
2
1
s
ac
ac
ac
ac
r
r
r
r
a
a
a
a
c
c
c
c
t
t
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e
e
e
e
r
r
r
r
on
i
i
i
i
1
2
te
t
t
t
ta
te
te
te
te
s
s
s
s
i
i
r
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o
o
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r
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se
a
m
c
b
s
s
0
3
e
t
s
s
s
s
q
p
a
a
a
b
c
s
s
s
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68
1
2
1
s
t
t
t
ta
y
e
o
o
n
a
r
a
t
o
o
o
r
3 is',
end is
-1 is'
t to en
nam
', n
, na
d is
e
a
m
'
[
m
e
,
1:3]
e[2:
[1:nam
)
])
1])
e[:])
r
b
r
,
ot']
anana']
rot']
'mango', 'carrot', 'banana']
Output:
$
I
I
I
I
I
I
C
I
I
I
I
c
c
c
c
t
t
t
t
t
t
h
t
t
t
t
h
h
h
h
p
e
e
e
e
e
e
a
e
e
e
e
a
a
a
a
.
p
n
r
n
a
a
i
i
nd
1
to
1
2
1
st
p
l
g
r
a
n
r
s
s
i
t
t
t
a
t
a
n
o
s
[
is
s
en
o
o
o
rt
'm
[
['
d
3
en
-1
t
a
'
m
i
i
d
n
c
a
s
s
go',
arro
ngo'
['a
wa
is a
is wa
o end
'ca
t',
, 'c
pple
r
'
a
'
roop
roo
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,
s h o p l i s t [ 0 ] fetches the first item and s h o p l i s t [ 3 ] fetches the fourth item in the
s h o p l i s t sequence.
The index can also be a negative number, in which case, the position is calculated from the
end of the sequence. Therefore, s h o p l i s t [ - 1 ] refers to the last item in the sequence and
s h o p l i s t [ - 2 ] fetches the second last item in the sequence.
The slicing operation is used by specifying the name of the sequence followed by an
optional pair of numbers separated by a colon within square brackets. Note that this is very
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, s h o p l i s t [ 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,
s h o p l i s t [ : ] returns a copy of the whole sequence.
Python en:Data Structures
You can also do slicing with negative positions. Negative numbers are used for positions
from the end of the sequence. For example, s h o p l i s t [ : - 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):
>
>
[
>
[
>
[
>
[
>
>
'
>
'
>
'
>
'
>
>
a
>
a
>
a
>
b
p
p
p
a
s
s
p
s
p
s
p
s
n
h
h
l
h
l
h
l
h
a
o
o
e
o
e
o
e
o
n
p
p
'
p
'
p
'
p
a
l
l
,
l
,
l
,
l
'
ist
ist
'm
ist
'c
ist
'b
ist
, '
[
a
[
a
[
a
[
c
=
:
n
:
r
:
n
:
a
:
g
:
r
:
a
:
r
[
1
o
2
o
3
n
r
'
]
'
]
t
]
a
1
o
apple', 'mango', 'carrot', 'banana']
, 'carrot', 'banana']
']
']
]
t', '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!
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.
Using sets, you can test for membership, whether it is a subset of another set, find the
intersection between two sets, and so on.
>
>
T
>
F
>
>
>
T
>
>
{
>
>
r
>
a
>
>
>
r
>
>
'
>
>
u
>
l
>
>
>
u
>
>
b
bri = set(['brazil', 'russia', 'india'])
'india' in bri
e
'
se
b
b
b
e
b
b
ra
usa' in bri
ric = bri.copy()
ric.add('china')
ric.issuperset(bri)
ri.remove('russia')
ri & bric # OR bri.intersection(bric)
zil', 'india'}
How It Works:
The example is pretty much self-explanatory because it involves basic set theory
mathematics taught in school.
69
Python en:Data Structures
70
References
When you create an object and assign it to a variable, the variable only refers to the object
and does not represent the object itself! That is, the variable name points to that part of
your computer's memory where the object is stored. This is called as binding of the name
to the object.
Generally, you don't need to be worried about this, but there is a subtle effect due to
references which you need to be aware of:
Example:
#!/usr/bin/python
# Filename: reference.py
p
s
m
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h
y
b
i
o
l
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n
p
i
e
t
l
s
c
(
i
t
t
'Simple Assignment')
st = ['apple', 'mango', 'carrot', 'banana']
= shoplist # mylist is just another name pointing to the same
!
del shoplist[0] # I purchased the first item, so I remove it from the
list
p
p
#
#
rin
rin
no
th
t
t
t
e
('sho
('myl
ice t
'app
p
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m
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ir
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yl
ho
mi
h
i
p
n
o
s
l
g
plist)
t)
ist and mylist both print the same list without
that they point to the same object
print('Copy by making a full slice')
mylist = shoplist[:] # make a copy by doing a full slice
del mylist[0] # remove first item
print('shoplist is', shoplist)
print('mylist is', mylist)
# notice that now the two lists are different
Output:
$
S
s
m
C
s
m
i
h
y
o
h
y
p
m
o
l
p
o
l
y
p
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h
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t
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li
st
on
A
st
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y
st
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ss
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ma
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e
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[
k
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[
fer
gnm
['
'ma
ing
['
'ca
e
e
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g
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ma
rr
ce.py
t
ngo',
o', '
full
ngo',
ot',
'
ca
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o
c
r
a
r
t
e
r
n
ot', 'banana']
', 'banana']
ot', 'banana']
a']
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
Python en:Data Structures
71
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.
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 s t r . Some useful methods of
this class are demonstrated in the next example. For a complete list of such methods, see
help(str).
Example:
#!/usr/bin/python
# Filename: str_methods.py
name = 'Swaroop' # This is a string object
if name.startswith('Swa'):
print('Yes, the string starts with "Swa"')
if 'a' in name:
print('Yes, it contains the string "a"')
if name.find('war') != -1:
print('Yes, it contains the string "war"')
delimiter = '_*_'
mylist = ['Brazil', 'Russia', 'India', 'China']
print(delimiter.join(mylist))
Output:
$
Y
Y
Y
B
e
e
e
r
p
s
s
s
a
y
,
,
,
z
th
t
i
i
il
o
h
t
t
_
n st
e st
con
con
*_Ru
r
r
t
t
s
_
i
a
a
s
m
n
i
i
i
e
g
n
n
a
th
s
s
s
_*
o
t
t
t
_
d
a
h
h
I
s
r
e
e
n
.py
ts w
str
str
dia_
i
i
i
*
t
n
n
_
h
g
g
C
"
"
"
hi
S
a
w
n
wa"
"
ar"
a
How It Works:
Here, we see a lot of the string methods in action. The s t a r t s w i t h method is used to find
out whether the string starts with the given string. The i n operator is used to check if a
given string is a part of the string.
The f i n d method is used to do find the position of the given string in the string or returns
-1 if it is not successful to find the substring. The s t r class also has a neat method to j o i n
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.
Python en:Data Structures
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.
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Python en: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.
The Problem
The problem is "I want a program which creates a backup of all my important files".
Although, this is a simple problem, there is not enough information for us to get started
with the 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.
1.
2.
3.
4.
5.
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 z i p command available by default in any standard Linux/Unix
distribution. Windows users can install (http:/ / gnuwin32. sourceforge. net/ downlinks/
zip. php) from the GnuWin32 project page (http:/ / gnuwin32. sourceforge. net/ packages/
zip. htm) and add C : \ P r o g r a m F i l e s \ G n u W i n 3 2 \ b i n 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 interface so
that we can pass arguments to it from our script.
72
Python en:Problem Solving
The Solution
As the design of our program is now reasonably stable, we can write the code which is an
implementation of our solution.
#!/usr/bin/python
# Filename: backup_ver1.py
import os
import time
#
s
#
s
1
ou
N
pa
.
r
o
c
T
ce
ti
es
he
=
ce
i
files and directories to be backed up are specified in a list.
['"C:\\My Documents"', 'C:\\Code']
we had to use double quotes inside the string for names with
n 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 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
if os.
pr
else:
pr
the backup
system(zip_command) == 0:
int('Successful backup to', target)
int('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 p r i n t ( z i p _ c o m m a n d ) just before the
o s . s y s t e m 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.
73
Python en:Problem Solving
We make use of the o s and t i m e modules by first importing them. Then, we specify the
files and directories to be backed up in the s o u r c e list. The target directory is where store
all the backup files and this is specified in the t a r g e t _ d i r variable. The name of the zip
archive that we are going to create is the current date and time which we find out using the
t i m e . s t r f t i m e ( ) function. It will also have the . z i p extension and will be stored in the
t a r g e t _ d i r directory.
Notice the use of o s . s e p variable - this gives the directory separator according to your
operating system i.e. it will be ' / ' in Linux, Unix, it will be ' \ \ ' in Windows and ' : ' in
Mac OS. Using o s . s e p instead of these characters directly will make our program portable
and work across these systems.
The t i m e . s t r f t i m e ( ) function takes a specification such as the one we have used in the
above program. The % Y specification will be replaced by the year without the century. The
% m specification will be replaced by the month as a decimal number between 0 1 and 1 2 and
so on. The complete list of such specifications can be found in the Python Reference Manual
(http:/ / docs. python. org/ dev/ 3. 0/ library/ time. html#time. strftime).
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 z i p _ c o m m a n d which contains the command that we are going to execute. You can
check if this command works by running it on the shell (Linux terminal or DOS prompt).
The z i p 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
- q r . 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 s o u r c e list into a string using the j o i n
method of strings which we have already seen how to use.
Then, we finally run the command using the o s . s y s t e m 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 : \ \ D o c u m e n t s ' or r ' C : \ D o c u m e n t s ' . However, do not use
' C : \ D o c u m e n t s ' 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 in typing the code, etc. Appropriately, you will have
to go back to the design phase or you will have to debug your program.
74
Python en:Problem Solving
75
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. First advantage is that your backups are stored in a hierarchical
manner and therefore it is much easier to manage. Second advantage is that the length of
the filenames are much shorter. Third advantage is that separate directories will help you
to easily check if you have taken a backup for each day since the directory would be
created only if you have taken a backup for that day.
#!/usr/bin/python
# Filename: 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
#
#
d
t
#
n
3
4
ir
od
T
ow
.
.
e
a
h
The
The
ctory
y = t
e cur
= tim
# Crea
if not
os
pr
te
o
.m
in
files are backed up into a zip file.
current day is the name of the subdirectory in the main
arget_dir + os.sep + time.strftime('%Y%m%d')
rent time is the name of the zip archive
e.strftime('%H%M%S')
t
s.
kd
t(
h
p
i
'
e
a
r
S
s
th
(t
uc
u
.
o
c
b
e
d
e
d
x
a
s
i
i
y
s
r
s
)
f
ect
ts(
#
ull
o
t
m
y
ry if
oday)
ake d
crea
it isn't already there
:
irectory
ted 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)
Python en:Problem Solving
else:
print('Backup FAILED')
Output:
$ python backup_ver2.py
Successfully created directory E:\Backup\20080702
Successful backup to E:\Backup\20080702\202311.zip
$ python backup_ver2.py
Successful backup to E:\Backup\20080702\202325.zip
How It Works:
Most of the program remains the same. The changes is that we check if there is a directory
with the current day as name inside the main backup directory using the o s . p a t h . e x i s t s
function. If it doesn't exist, we create it using the o s . m k d i r function.
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.
#!/usr/bin/python
# Filename: backup_ver3.py
import os
import time
#
s
#
s
1
ou
N
pa
.
r
o
c
The
ce =
tice
es i
files and directories to be backed up are specified in a list.
['"C:\\My Documents"', 'C:\\Code']
we had to use double quotes inside the string for names with
n 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
#
#
d
t
#
n
3
4
ir
od
T
ow
.
.
e
a
h
The
The
ctory
y = t
e cur
= tim
files are backed up into a zip file.
current day is the name of the subdirectory in the main
arget_dir + os.sep + time.strftime('%Y%m%d')
rent time is the name of the zip archive
e.strftime('%H%M%S')
76
Python en:Problem Solving
# Tak
comme
if le
t
else:
t
e
n
n
a
a c
t =
(com
rget
omme
inpu
ment
= t
n
t
)
o
t fr
('En
==
day
o
t
0
+
77
m the
er a
: # c
os.s
u
co
he
ep
ser
mmen
ck i
+ n
t
t
f
o
o c
-a
w +
reate the name of the zip file
> ')
comment was entered
'.zip'
arget = today + os.sep + now + '_' +
comment.replace(' ', '_') + '.zip'
# Crea
if not
os
pr
te
o
.m
in
t
s.
kd
t(
h
p
i
'
e
a
r
S
s
th
(t
uc
u
.
o
c
b
e
d
e
d
x
a
s
i
i
y
s
r
s
)
f
ect
ts(
#
ull
o
t
m
y
ry if
oday)
ake d
crea
it isn't already there
:
irectory
ted 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:
$ python 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 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.
Python en:Problem Solving
78
Fourth Version
#!/usr/bin/python
# Filename: backup_ver4.py
import os
import time
#
s
#
s
1
ou
N
pa
.
r
o
c
T
ce
ti
es
he
=
ce
i
files and directories to be backed up are specified in a list.
['"C:\\My Documents"', 'C:\\Code']
we had to use double quotes inside the string for names with
n 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
d
t
#
n
ire
oda
Th
ow
c
y
e
=
# Tak
comme
if le
t
else:
t
to
=
c
t
e
n
n
a
ry
target_dir + os.sep + time.strftime('%Y%m%d')
urrent time is the name of the zip archive
ime.strftime('%H%M%S')
a c
t =
(com
rget
omme
inpu
ment
= t
n
t
)
o
t fr
('En
==
day
o
t
0
+
m the
er a
: # c
os.s
u
co
he
ep
ser
mmen
ck i
+ n
t
t
f
o
o c
-a
w +
reate the name of the zip file
> ')
comment was entered
'.zip'
arget = today + os.sep + now + '_' + \
comment.replace(' ', '_') + '.zip'
# Crea
if not
os
pr
te
o
.m
in
t
s.
kd
t(
h
p
i
'
e
a
r
S
s
th
(t
uc
u
.
o
c
b
e
d
e
d
x
a
s
i
i
y
s
r
s
)
f
ect
ts(
#
ull
o
t
m
y
ry if
oday)
ake d
crea
it isn't already there
:
irectory
ted 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
if os.
pr
else:
pr
the backup
system(zip_command) == 0:
int('Successful backup to', target)
int('Backup FAILED')
Output:
Python en:Problem Solving
$
E
S
E:\Ba
p
nt
uc
ck
y
e
c
u
t
r
e
p
ho
a
ss
\2
n b
co
ful
008
ack
mme
ba
070
u
n
c
2
p
t
k
\
_v
up
20
79
er4.py
-> added new examples
to
2836_added_new_examples.zip
$ python 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 i n p u t function and then check if the
user actually entered something by finding out the length of the input using the l e n
function. If the user has just pressed e n t e r 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 . z i p extension. Notice that we are replacing spaces in the comment with
underscores - this is because managing filenames without spaces are much easier.
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 s y s . a r g v list and we can
add them to our s o u r c e list using the e x t e n d method provided by the l i s t class.
The most important refinement would be to not use the o s . s y s t e m way of creating archives
and instead using the z i p f i l e or t a r f i l e 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 o s . s y s t e m 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.
Can you try writing the fifth version that uses the zipfile (http:/ / docs. python. org/ dev/ 3.
0/ library/ zipfile. html) module instead of the o s . s y s t e m call?
Python en:Problem Solving
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.
2.
3.
4.
5.
6.
What (Analysis)
How (Design)
Do It (Implementation)
Test (Testing and Debugging)
Use (Operation or Deployment)
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.
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.
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80
Python en:Object Oriented Programming
Python en:Object Oriented
Programming
Introduction
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 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 i n t which translates to saying that variables that store integers are
variables which are instances (objects) of the i n t class.
Note for Static Language Programmers
Note that even integers are treated as objects (of the i n t class). This is unlike C++
and Java (before version 1.5) where integers are primitive native types. See
h e l p ( i n t ) 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. Variables 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 c l a s s keyword. The fields and methods of the class are listed
in an indented block.
The self
Class methods have only one specific difference from ordinary functions - they must have
an extra first name that has to be added to the beginning of the parameter list, but you do
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 s e l f .
Although, you can give any name for this parameter, it is strongly recommended that you
use the name s e l f - 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 s e l f .
81
Python en:Object Oriented Programming
Note for C++/Java/C# Programmers
The s e l f in Python is equivalent to the t h i s pointer in C++ and the t h i s reference
in Java and C#.
You must be wondering how Python gives the value for s e l f and why you don't need to
give a value for it. An example will make this clear. Say you have a class called M y C l a s s
and an instance of this class called m y o b j e c t . When you call a method of this object as
myobject.method(arg1,
a r g 2 ) , this is automatically converted by Python into
M y C l a s s . m e t h o d ( m y o b j e c t , a r g 1 , a r g 2 ) - this is all the special s e l f is about.
This also means that if you have a method which takes no arguments, then you still have to
have one argument - the s e l f .
Classes
The simplest class possible is shown in the following example.
#!/usr/bin/python
# Filename: simplestclass.py
class Person:
pass # An empty block
p = Person()
print(p)
Output:
$ python simplestclass.py
<__main__.Person object at 0x019F85F0>
How It Works:
We create a new class using the c l a s s 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 p a s s 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 P e r s o n class in the _ _ m a i n _ _ 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.
82
Python en:Object Oriented Programming
Object Methods
We have already discussed that classes/objects can have methods just like functions except
that we have an extra s e l f variable. We will now see an example.
#!/usr/bin/python
# Filename: method.py
class Person:
def sayHi(self):
print('Hello, how are you?')
p = Person()
p.sayHi()
# This short example can also be written as Person().sayHi()
Output:
$ python method.py
Hello, how are you?
How It Works:
Here we see the s e l f in action. Notice that the s a y H i method takes no parameters but
still has the s e l f in the function definition.
The __init__method
There are many method names which have special significance in Python classes. We will
see the significance of the _ _ i n i t _ _ method now.
The _ _ i n i t _ _ 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:
#!/usr/bin/python
# Filename: class_init.py
class Per
def _
s
def s
p
s
_
e
a
r
o
i
l
y
i
n
n
f
H
n
:
i
.
i
t
t
n
(
(
_
a
s
'
_
m
e
H
(
e
l
e
se
=
f)
ll
lf, name):
name
:
o, my name is', self.name)
p = Person('Swaroop')
p.sayHi()
# This short example can also be written as Person('Swaroop').sayHi()
Output:
83
Python en:Object Oriented Programming
$ python class_init.py
Hello, my name is Swaroop
How It Works:
Here, we define the _ _ i n i t _ _ method as taking a parameter n a m e (along with the usual
s e l f ). Here, we just create a new field also called n a m e . Notice these are two different
variables even though they are both called 'name'. The dotted notation allows us to
differentiate between them.
Most importantly, notice that we do not explicitly call the _ _ i n i t _ _ 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 s e l f . n a m e field in our methods which is demonstrated in the
s a y H i method.
Class And Object Variables
We have already discussed the functionality part of classes and objects (i.e. methods), 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:
#!/usr/bin/python
# Filename: objvar.py
class Robot:
'''Represents a robot, with a name.'''
# A class variable, counting the number of robots
population = 0
def _
'
s
p
_
'
e
r
i
'
l
i
n
I
f
n
i
n
.
t
t
i
n
(
_
t
a
'
_
i
m
(
(
a
e
I
sel
liz
=
nit
f
e
n
i
,
s
a
a
name):
the data.'''
me
lizing {0})'.format(self.name))
# When this person is created, the robot
# adds to the population
Robot.population += 1
84
Python en:Object Oriented Programming
def __del__(self):
'''I am dying.'''
print('{0} is being destroyed!'.format(self.name))
Robot.population -= 1
if Ro
p
else:
p
working.'.for
bot.population == 0:
rint('{0} was the last one.'.format(self.name))
rint('There are still {0:d} robots
mat(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 h
'
p
howMa
o
'
r
n
w
'
i
y
Many
Prin
nt('
= s
(
t
W
t
)
s
e
a
:
the current population.'''
have {0:d} robots.'.format(Robot.population))
ticmethod(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
Robot.howMany()
Output:
(
G
W
(
G
W
I
r
e
I
r
e
nit
eet
ha
nit
eet
ha
i
i
v
i
i
v
a
n
e
a
n
e
liz
gs,
1
liz
gs,
2
in
m
ro
in
m
ro
g
y
b
g
y
b
R
m
ot
C
m
ot
2
a
s
a
s
s
.
3
s
.
D2)
ters call me R2-D2.
PO)
ters call me C-3PO.
85
Python en:Object Oriented Programming
Robots can do some work here.
R
R
T
C
C
W
o
2
h
e
b
e
3
3
o
D
r
P
P
h
t
2
e
O
O
a
s h
is
ar
is
wa
ve
av
b
e
b
s
0
e
e
s
e
t
r
f
n
i
n
e
b
i
i g
t l
i g
h
o o
ni
d
l
d
la
ts
s
e
1
e
s
.
hed
str
ro
str
t o
o
b
o
n
t
y
o
y
e
h
e
t
e
.
e
d
s
d
ir work. So let's destroy them.
!
working.
!
How It Works:
This is a long example but helps demonstrate the nature of class and object variables. Here,
p o p u l a t i o n belongs to the R o b o t class and hence is a class variable. The n a m e variable
belongs to the object (it is assigned using s e l f ) and hence is an object variable.
Thus, we refer to the p o p u l a t i o n class variable as R o b o t . p o p u l a t i o n and not as
s e l f . p o p u l a t i o n . We refer to the object variable n a m e using s e l f . n a m e 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 h o w M a n y is actually a method that belongs to the class and not to the object. This
means we can define it as either a c l a s s m e t h o d or a s t a t i c m e t h o d depending on whether
we need to know which class we are part of. Since we don't need such information, we will
go for s t a t i c m e t h o d .
We could have also achieved the same using decorators (http:/ / www. ibm. com/
developerworks/ linux/ library/ l-cpdecor. html):
@stat
def h
'
p
i
o
'
r
c
w
'
i
m
M
P
n
e
a
r
t
t
n
i
(
h
y
n
'
o
(
t
W
d
):
s the current population.'''
e have {0:d} robots.'.format(Robot.population))
Decorators can be imagined to be a shortcut to calling an explicit statement, as we have
seen in this example.
Observe that the _ _ i n i t _ _ method is used to initialize the R o b o t instance with a name. In
this method, we increase the p o p u l a t i o n count by 1 since we have one more robot being
added. Also observe that the values of s e l f . n a m e 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
s e l f 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 R o b o t . _ _ d o c _ _ and the method docstring as
Robot.sayHi.__doc__
Just like the _ _ i n i t _ _ method, there is another special method _ _ d e l _ _ 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
R o b o t . p o p u l a t i o n count by 1.
86
Python en:Object Oriented Programming
The _ _ d e l _ _ 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
d e l statement which is what we have done here.
Note for C++/Java/C# Programmers
All class members (including the data members) are public and all the methods are
virtual in Python.
One exception: If you use data members with names using the double underscore
prefix such as _ _ p r i v a t e v a r , 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).
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.
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 S c h o o l M e m b e r 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
S c h o o l M e m b e r , 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 S c h o o l M e m b e r
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 S c h o o l M e m b e r class in this situation is known as the base class or the superclass. The
T e a c h e r and S t u d e n t classes are called the derived classes or subclasses.
We will now see this example as a program.
#!/usr/bin/python
# Filename: inherit.py
87
Python en:Object Oriented Programming
class Sch
'''Re
def _
s
s
p
o
p
_
e
e
r
o
r
i
l
l
i
l
e
n
f
f
n
M
s
i
.
.
t
e
e
t
n
a
(
m
n
_
a
g
'
b
t
_
m
e
(
r:
a
se
=
=
Ini
e
s
(
e
ny
lf,
na
age
tia
school member.'''
name, age):
me
lized SchoolMember: {0})'.format(self.name))
def tell(self):
'''Tell my details.'''
print('Name:"{0}" Age:"{1}"'.format(self.name, self.age), end="
")
class Tea
'''Re
def _
S
s
c
p
_
c
e
h
r
i
h
l
e
e
n
o
f
r
s
i
o
.
(
e
t
l
s
S
n
_
M
a
c
t
_
e
l
h
s
(
m
a
oo
a
se
be
ry
lM
t
lf
r.
=
e
e
,
_
mbe
ach
na
_in
sal
r
e
m
i
a
)
r
e
t
r
:
.'''
, age, salary):
__(self, name, age)
y
print('(Initialized Teacher: {0})'.format(self.name))
def tell(self):
SchoolMember.tell(self)
print('Salary: "{0:d}"'.format(self.salary))
class Stu
'''Re
def _
S
s
p
d
p
_
c
e
r
e
r
i
h
l
i
n
e
n
o
f
n
t
s
i
o
.
t
(
e
t
l
m
(
S
n
_
M
a
'
c
t
_
e
r
(
h
s
(
m
k
I
oo
a
se
be
s
ni
lM
s
lf
r.
=
ti
e
t
,
_
m
a
mbe
ude
na
_in
ark
liz
r
n
m
i
s
e
)
t
e
t
:
.'''
, age, marks):
__(self, name, age)
d 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:
$ python inherit.py
(Initialized SchoolMember: Mrs. Shrividya)
88
Python en:Object Oriented Programming
(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 _ _ i n i t _ _ method of the base class is
explicitly called using the s e l f 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 s e l f variable along with any arguments.
Notice that we can treat instances of T e a c h e r or S t u d e n t as just instances of the
S c h o o l M e m b e r when we use the t e l l method of the S c h o o l M e m b e r class.
Also, observe that the t e l l method of the subtype is called and not the t e l l method of the
S c h o o l M e m b e r 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.
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.
Previous Next
Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=2359
Contributors: Horstjens, Swaroop, 6 anonymous edits
89
Python en:Input Output
Python en:Input Output
Introduction
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 i n p u t ( ) and p r i n t ( ) functions respectively.
For output, we can also use the various methods of the s t r (string) class. For example, you
can use the r j u s t method to get a string which is right justified to a specified width. See
h e l p ( s t r ) 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.
Input from user
#!/usr/bin/python
# user_input.py
def reverse(text):
return text[::-1]
def is_palindrome(text):
return text == reverse(text)
someth
if (is
pr
else:
pr
ing = input('Enter text: ')
_palindrome(something)):
int("Yes, it is a palindrome")
int("No, it is not a palindrome")
Output:
$ python user_input.py
Enter text: sir
No, it is not a palindrome
$ python user_input.py
Enter text: madam
Yes, it is a palindrome
$ python 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 s e q [ 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
90
Python en:Input Output
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 i n p u t ( ) 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, the
i n p u t ( ) function will then return that text.
We take that text and reverse it. If the original text and reversed text are equal, then the
text is a palindrome (http:/ / en. wiktionary. org/ wiki/ 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?
Files
You can open and use files for reading or writing by creating an object of the f i l e class
and using its r e a d , r e a d l i n e or w r i t e 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 c l o s e method to
tell Python that we are done using the file.
Example:
#!/usr/bin/python
# Filename: using_file.py
p
P
W
i
o
r
h
f
em =
ogra
en t
you
us
'''
'
mm
he
w
e
''\
ing
wo
ann
Pyt
is fun
rk is done
a make your work also fun:
hon!
f = open('poem.txt', 'w') # open for 'w'riting
f.write(poem) # write text to file
f.close() # close the file
f = o
by de
while
l
i
pen
fau
Tr
ine
f l
('p
lt
ue:
=
en(
bre
print(l
f.close() #
oem.txt') # if no mode is specified, 'r'ead mode is assumed
f
l
a
i
.
i
k
n
c
readline()
ne) == 0: # Zero length indicates EOF
e, end='')
lose the file
Output:
$ python using_file.py
Programming is fun
91
Python en:Input Output
92
When the work is done
if you wanna make your work also fun:
use Python!
How It Works:
First, open a file by using the built-in o p e n 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 by dealing with a text file (' t ' ) or a binary
file (' b ' ). There are actually many more modes available and h e l p ( o p e n ) will give you
more details about them. By default, o p e n ( ) 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 w r i t e method of the
file object to write to the file and then we finally c l o s e 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 r e a d l i n e
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 deafult, the p r i n t ( ) function prints the text as well as an automatic newline to the
screen. We are suppressing the newline by specifying e n d = ' ' because the line that is read
from the file already ends with a newline character. Then, we finally c l o s e the file.
Now, check the contents of the p o e m . t x t file to confirm that the program has indeed
written and read from that file.
Pickle
Python provides a standard module called p i c k l e 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:
#!/usr/bin/python
# Filename: pickling.py
import pickle
#
s
#
s
t
ho
t
ho
h
p
h
p
e
l
e
l
#
f
p
f
W
=
ic
.c
ri
o
kl
lo
n
is
l
is
a
t
i
t
t
p
e
s
to the file
n(shoplistfile, 'wb')
dump(shoplist, f) # dump the object to a file
()
e
e
.
e
me o
file
st o
= [
f t
=
f t
'ap
h
'
h
p
e
s
i
l
f
ho
ng
e'
i
p
s
,
le
lis
to
'm
whe
t.d
bu
ang
re we will store the object
ata'
y
o', 'carrot']
del shoplist # destroy the shoplist variable
# Read back from the storage
Python en:Input Output
93
f = open(shoplistfile, 'rb')
storedlist = pickle.load(f) # load the object from the file
print(storedlist)
Output:
$ python pickling.py
['apple', 'mango', 'carrot']
How It Works:
To store an object in a file, we have to first o p e n the file in 'w'rite 'b'inary mode and then
call the d u m p function of the p i c k l e module. This process is called pickling.
Next, we retrieve the object using the l o a d function of the p i c k l e module which returns
the object. This process is called unpickling.
Summary
We have discussed various types of input/output and also file handling and using the pickle
module.
Next, we will explore the concept of exceptions.
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Contributors: Horstjens, Swaroop, 1 anonymous edits
Python en:Exceptions
Introduction
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.
Errors
Consider a simple p r i n t function call. What if we misspelt p r i n t as P r i n t ? Note the
capitalization. In this case, Python raises a syntax error.
>>> Prin
Tracebac
File "
Prin
NameErro
>>> prin
Hello Wo
t
k
<
t
r
t
r
('
(
py
('
:
('
ld
H
m
s
H
n
H
e
o
h
e
a
e
l
s
e
l
m
l
l
t
l
l
e
l
o W
re
l#0
o W
'P
o W
o
c
>
o
r
o
r
e
"
r
i
r
l
n
,
l
n
l
d')
t call last):
line 1, in <module>
d')
t' is not defined
d')
Python en:Exceptions
94
Observe that a N a m e E r r o r is raised and also the location where the error was detected is
printed. This is what an error handler for this error does.
Exceptions
We will try to read input from the user. Press c t r l - d and see what happens.
>>>
Ente
Trac
Fi
s
r
e
l
s
EOFEr
= inp
somet
back (
e "<py
= inp
ror: E
u
h
m
s
u
O
t
i
o
h
t
F
(
n
s
e
(
'
g
t
l
'
w
En
r
l#
En
he
t
e
2
t
n
e
>
c
>
e
r something --> ')
e
"
r
r
nt
, l
so
ead
c
i
m
i
a
n
e
n
l
e
t
g
l l
1,
hin
a
as
i
g
li
t
n
n
):
<module>
-> ')
e
Python raises an error called E O F E r r o r which basically means it found an end of file symbol
(which is represented by c t r l - d ) when it did not expect to see it.
Handling Exceptions
We can handle exceptions using the t r y . . e x c e p t statement. We basically put our usual
statements within the try-block and put all our error handlers in the except-block.
#!/usr/bin/python
# Filename: try_except.py
try:
t
excep
p
excep
p
else:
p
e
t
r
t
r
xt
E
in
K
in
O
t
e
t
=
F
(
y
(
E
'
b
'
i
r
W
o
Y
n
r
h
a
o
p
o
y
r
u
ut
r:
d
dI
c
('Enter something --> ')
id you do an EOF on me?')
nterrupt:
ancelled the operation.')
rint('You entered {0}'.format(text))
Output:
$ python try_except.py
Enter something -->
# Press ctrl-d
Why did you do an EOF on me?
$ python try_except.py
Enter something -->
# Press ctrl-c
You cancelled the operation.
$ python 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 t r y block and then
put handlers for the appropriate errors/exceptions in the e x c e p t clause/block. The e x c e p t
Python en:Exceptions
95
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 e x c e p t clause associated with every t r y 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 e l s e clause associated with a t r y . . e x c e p t block. The e l s e 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.
Raising Exceptions
You can raise exceptions using the r a i s e 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 arise should be class which directly or indirectly must
be a derived class of the E x c e p t i o n class.
#!/usr/bin/python
# Filename: raising.py
class Sho
'''A
def _
E
s
s
r
u
_
x
e
e
t
s
i
c
l
l
I
e
n
e
f
f
n
r
i
p
.
.
p
t
t
l
a
u
d
_
i
e
t
t
e
_
o
n
l
E
f
(
n
g
e
x
i
s
.
t
a
inpu
text
se S
wor
rror
Why
tInp
Shor
t
)
h
k
:
d
u
t
('
<
or
c
c
n
e
_
h
s
e
e
l
_
p
d
f
i
=
ti
e
,
ni
l
t =
o
x
l
t
e
a
n
c
e
_
n
t
(
e
n
_
g
l
E
p
g
(
t
e
x
t
t
s
h
a
c
i
h
e
e
o
,
l
ption):
n class.'''
atleast):
f)
st
try:
exce
exce
leas
else
text =
if len(
rai
# Other
pt EOFE
print('
pt Shor
print('
t {1}'\
.
:
print('
En
3
tI
an
ter something --> ')
:
nputException(len(text), 3)
continue as usual here
id you do an EOF on me?')
tException as ex:
InputException: The input was {0} long, expected at
format(ex.length, ex.atleast))
No exception was raised.')
Output:
$ python raising.py
Enter something --> a
Python en:Exceptions
96
ShortInputException: The input was 1 long, expected at least 3
$ python 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
S h o r t I n p u t E x c e p t i o n . It has two fields - l e n g t h which is the length of the given input, and
a t l e a s t which is the minimum length that the program was expecting.
In the e x c e p t clause, we mention the class of error which will be stored a s the variable
name to hold the corresponding error/exception object. This is analogous to parameters and
arguments in a function call. Within this particular e x c e p t clause, we use the l e n g t h and
a t l e a s t fields of the exception object to print an appropriate message to the user.
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
f i n a l l y block. Note that you can use an e x c e p t clause along with a f i n a l l y block for the
same corresponding t r y block. You will have to embed one within another if you want to
use both.
#!/usr/bin/python
# Filename: finally.py
import time
try:
f = ope
while T
lin
if
excep
p
final
f
p
p
t
t Ke
rint
ly:
.clo
rint
r
i
y
(
i
m
b
'
n
r
e
l
n
e
o
!
('p
ue:
=
en(
bre
t(l
.sl
ard
! Y
oe
#
f.
li
ak
in
ee
In
ou
m.
o
re
ne
t
u
a
)
xt')
r usual file-reading idiom
dline()
== 0:
e, e
p(2)
terr
can
nd
#
up
ce
='')
To make sure it runs for a while
t:
lled the reading from the file.')
se()
('(Cleaning up: Closed the file)')
Output:
$
P
W
i
!
pyth
rogra
hen t
f you
! You
on f
mmin
he w
wan
can
i
g
o
n
c
na
i
rk
a
el
lly
s f
is
mak
led
.p
un
d
e
t
y
one
your work also fun:
he reading from the file.
Python en:Exceptions
(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 t i m e . s l e e p function so that the program runs slowly
(Python is very fast by nature). When the program is still running, press c t r l - c to
interrupt/cancel the program.
Observe that the K e y b o a r d I n t e r r u p t exception is thrown and the program quits. However,
before the program exits, the finally clause is executed and the file object is always closed.
The with statement
Acquiring a resource in the t r y block and subsequently releasing the resource in the
f i n a l l y block is a common pattern. Hence, there is also a w i t h statement that enables this
to be done in a clean manner:
#!/usr/bin/python
# Filename: using_with.py
with open("poem.txt") as f:
for line in f:
print(line, end='')
How It Works:
The output should be same as the previous example. The difference here is that we are
using the o p e n function with the w i t h statement - we leave the closing of the file to be
done automatically by w i t h o p e n .
What happens behind the scenes is that there is a protocol used by the w i t h statement. It
fetches the object returned by the o p e n statement, let's call it "thefile" in this case.
It always calls the t h e f i l e . _ _ e n t e r _ _ function before starting the block of code under it
and always calls t h e f i l e . _ _ e x i t _ _ after finishing the block of code.
So the code that we would have written in a f i n a l l y block is should be taken care of
automatically by the _ _ e x i t _ _ method. This is what helps us to avoid having to use explicit
t r y . . f i n a l l y statements repeatedly.
More discussion on this topic is beyond scope of this book, so please refer PEP 343 (http:/ /
www. python. org/ dev/ peps/ pep-0343/ ) for comprehensive explanation.
Summary
We have discussed the usage of the t r y . . e x c e p t and t r y . . f i n a l l y 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.
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Contributors: Swaroop, 2 anonymous edits
97
Python en:Standard Library
Python en:Standard Library
Introduction
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 (http:/ / docs. python. org/ dev/ 3. 0/ library/ ) 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.
sys module
The s y s module contains system-specific functionality. We have already seen that the
s y s . a r g v 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 s y s module gives us such
functionality.
>
>
(
>
T
>
>
3
>
r
>
>
,
>
u
i
s
0
s
m
y
,
y
por
s.v
0,
s.v
t sy
ersi
'be
ersi
s
on_info
ta', 2)
on_info[0] >= 3
e
How It Works:
The s y s module has a v e r s i o n _ i n f o 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:
#
#
i
i
!/
F
mp
f
u
i
o
s
s
l
r
y
w
r
e
t
s
a
/bi
nam
sy
.ve
rni
R
n
e
s
r
n
u
/
:
,
s
g
n
py
v
w
io
s.
ti
t
e
a
n
w
m
h
r
r
_
a
e
o
s
n
i
r
W
n
i
i
n
n
a
o
n
f
(
r
n
g
o
"
n
c
s
[
N
i
heck.py
0] < 3:
eed Python 3.0 for this program to run",
ng)
else:
print('Proceed as normal')
Output:
98
Python en:Standard Library
$ python2.5 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 w a r n i n g s 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.
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
l o g g i n g module.
#!/usr/bin/python
# Filename: use_logging.py
import os, platform, logging
if pl
l
os.ge
else:
l
atform.platform().startswith('Windows'):
ogging_file = os.path.join(os.getenv('HOMEDRIVE'),
tenv('HOMEPATH'), 'test.log')
loggi
l
f
f
f
)
n
e
o
i
i
ogging_file = os.path.join(os.getenv('HOME'), 'test.log')
g
v
r
l
l
.
e
m
e
e
b
l
a
n
m
a
=
t
a
o
s
l
=
m
d
i
o
'
e
e
cCon
ggin
%(as
= l
= '
f
g
c
o
w
i
.
t
g
'
g
D
i
g
,
(
EBUG,
me)s : %(levelname)s : %(message)s',
ing_file,
logging.debug("Start of the program")
logging.info("Doing something")
logging.warning("Dying now")
Output:
$python use_logging.py
Logging to C:\Users\swaroop\test.log
If we check the contents of t e s t . l o g , it will look something like this:
2008-09-03 13:18:16,233 : DEBUG : Start of the program
2008-09-03 13:18:16,233 : INFO : Doing something
2008-09-03 13:18:16,233 : WARNING : Dying now
99
Python en:Standard Library
How It Works:
We use three modules from the standard library - the o s module for interacting with the
operating system, the p l a t f o r m module for information about the platform i.e. the
operating system and the l o g g i n g module to log information.
First, we check which operating system we are using by checking the string returned by
p l a t f o r m . p l a t f o r m ( ) (for more information, see i m p o r t p l a t f o r m ; h e l p ( p l a t f o r m ) ). 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 o s . p a t h . j o i n ( ) 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 l o g g i n g 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.
urllib and json modules
How much fun would it be if we could write our own program that will get search results
from the web? Let us explore that now.
This can be achieved using a few modules. First is the u r l l i b module that we can use to
fetch any webpage from the internet. We will make use of Yahoo! Search to get the search
results and luckily they can give us the results in a format called JSON which is easy for us
to parse because of the built-in j s o n module in the standard library.
TODO
This program doesn't work yet which seems to be a bug in Python 3.0 beta 2 (http:/ /
bugs. python. org/ issue3763).
#!/usr/bin/python
# Filename: yahoo_search.py
import sys
if sys.version_info[0] != 3:
sys.exit('This program needs Python 3.0')
import json
import urllib, urllib.parse, urllib.request, urllib.response
#
Y
'
S
'
A
j
E
h
G
H
l
A
t
e
O
2
R
t
t
O
2
C
p
_
p
H
:
y
A
s
_
/
o
P
v
B
/
u
P
V
A
s
r
_
3
S
e
I
4
E
a
own APP ID at http://developer.yahoo.com/wsregapp/
D =
HELWhdfUJbfDQzlJ2B57KFS_qs4I8D0Wz5U5_yCI1Awv8.lBSfPhwr'
=
rch.yahooapis.com/WebSearchService/V1/webSearch'
100
Python en:Standard Library
101
class YahooSearchError(Exception):
pass
# Taken fro
def search(
kwargs.
'ap
'qu
're
'st
'ou
})
url = S
result
if 'Err
rai
return
m
q
u
p
e
s
a
t
h
e
d
d
y
l
t
u
u
p
i
r
u
r
p
E
=
o
s
r
AR
j
r'
e
es
t
r
a
'
'
t
'
t
t
y
t
:
:
s
:
'
p:/
, r
e({
YA
qu
':
st
: '
CH_
son
in
Yah
ult
/developer.yahoo.com/python/python-json.html
esults=20, start=1, **kwargs):
H
e
r
a
j
O
r
e
r
s
BAS
.lo
re
ooS
['R
E
a
s
e
e
O
y
s
t
o
_APP_ID,
,
ults,
,
n'
d
u
a
s
+
(
l
r
u
'
r
:
h
t
?'
u lli
t
c Err
l Set
+ urllib.parse.urlencode(kwargs)
b.request.urlopen(url))
or(result['Error'])
']
query = input('What do you want to search for? ')
for result in search(query)['Result']:
print("{0} : {1}".format(result['Title'], result['Url']))
Output:
TODO
How It Works:
We can get the search results from a particular website by giving the text we are searching
for in a particular format. We have to specify many options which we combine using
k e y 1 = v a l u e 1 & k e y 2 = v a l u e 2 format which is handled by the u r l l i b . p a r s e . u r l e n c o d e ( )
function.
So for example, open this link in your web browser (http:/ / search. yahooapis. com/
WebSearchService/
V1/
webSearch?query=byte+
of+
python&
appid=jl22psvV34HELWhdfUJbfDQzlJ2B57KFS_qs4I8D0Wz5U5_yCI1Awv8.
lBSfPhwr&
results=20& start=1& output=json) and you will see 20 results, starting from the first
result, for the words "byte of python", and we are asking for the output in JSON format.
We make a connection to this URL using the u r l l i b . r e q u e s t . u r l o p e n ( ) function and pass
that file handle to j s o n . l o a d ( ) which will read the content and simultaneously convert it
to a Python object. We then loop through these results and display it to the end-user.
Python en:Standard Library
Module of the Week Series
There is much more to be explored in the standard library such as debugging (http:/ / docs.
python. org/ dev/ library/ pdb. html), handling command line options (http:/ / docs. python.
org/ dev/ 3. 0/ library/ getopt. html), regular expressions (http:/ / www. diveintopython. org/
regular_expressions/ index. html) and so on.
The best way to further explore the standard library is to read Doug Hellmann's excellent
Python Module of the Week (http:/ / www. doughellmann.com/ projects/ PyMOTW/ ) series.
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 (http:/ / docs. python. org/ dev/ 3. 0/ library/ ) 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.
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Contributors: Swaroop, 2 anonymous edits
Python en:More
Introduction
So far we have covered majority of the various aspects of Python that you will use. In this
chapter, we will cover some more aspects that will make our knowledge of Python more
well-rounded.
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.
>
.
.
>
>
2
>
'
>
.
.
>
>
> def
.
.
> err
> err
get_error_details():
return (2, 'second error details')
num, errstr = get_error_details()
num
>> errstr
second error details'
Notice that the usage of a , b = < s o m e e x p r e s s i o n > interprets the result of the expression
as a tuple with two values.
If you want to interpret the results as ( a , < e v e r y t h i n g e l s e > ) , then you just need to star
it just like you would in function parameters:
102
Python en:More
>
>
1
>
[
103
>> a, *b = [1, 2, 3, 4]
>> a
>> b
2, 3, 4]
This also means the fastest way to swap two variables in Python is:
>
>
>
(
>
>
>
8
>
>
>
,
a
a
a
5
= 5; b = 8
, b = b, a
, b
)
Special Methods
There are certain methods such as the _ _ i n i t _ _ and _ _ d e l _ _ 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 [ k e y ] indexing operation for your class (just like you use it for lists and
tuples), then all you have to do is implement the _ _ g e t i t e m _ _ ( ) method and your job is
done. If you think about it, this is what Python does for the l i s t 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 (http:/ / docs. python. org/ dev/ 3. 0/ reference/
datamodel. html#special-method-names).
Name
Explanation
__init__(self, ...)
This method is called just before the newly created object is returned for usage.
__del__(self)
Called just before the object is destroyed
__str__(self)
Called when we use the p r i n t function or when s t r ( ) 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 [ k e y ] indexing operation is used.
__len__(self)
Called when the built-in l e n ( ) function is used for the sequence object.
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:
>
>
.
Y
>
>
.
e
> flag = True
> if flag: print 'Yes'
.
s
Notice that the single statement is used in-place and not as a separate block. Although, 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
Python en:More
statement if you are using proper indentation.
Lambda Forms
A l a m b d a statement is used to create new function objects and then return them at
runtime.
#!/usr/bin/python
# Filename: lambda.py
def make_repeater(n):
return lambda s: s * n
twice = make_repeater(2)
print(twice('word'))
print(twice(5))
Output:
$ python lambda.py
wordword
10
How It Works:
Here, we use a function m a k e _ r e p e a t e r to create new function objects at runtime and
return it. A l a m b d a statement is used to create the function object. Essentially, the l a m b d a
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. Note that even a
p r i n t statement cannot be used inside a lambda form, only expressions.
TODO
Can we do a l i s t . s o r t ( ) by providing a compare function created using l a m b d a ?
points = [ { 'x' : 2, 'y' : 3 }, { 'x' : 4, 'y' : 1 } ]
# points.sort(lambda a, b : cmp(a['x'], b['x']))
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.
#!/usr/bin/python
# Filename: list_comprehension.py
listone = [2, 3, 4]
listtwo = [2*i for i in listone if i > 2]
print(listtwo)
Output:
104
Python en:More
105
$ python list_comprehension.py
[6, 8]
How It Works:
Here, we derive a new list by specifying the manipulation to be done (2 * i ) when some
condition is satisfied (i f 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.
Receiving Tuples and Lists in Functions
There is a special way of receiving parameters to a function as a tuple or a dictionary using
the * or * * prefix respectively. This is useful when taking variable number of arguments in
the function.
>
.
.
.
>
.
.
.
> def pow
.
'''
.
tot
.
for
ersu
Retu
al =
i i
m(power, *args):
rn the sum of each argument raised to specified power.'''
0
n args:
.
.
.
>
2
.
.
.
>
5
.
total += pow(i, power)
.
return total
.
> powersum(2, 3, 4)
>>> powersum(2, 10)
100
Because we have a * prefix on the a r g s variable, all extra arguments passed to the
function are stored in a r g s as a tuple. If a * * prefix had been used instead, the extra
parameters would be considered to be key/value pairs of a dictionary.
exec and eval
The e x e c function is used to execute Python statements which are stored in a string or file,
as opposed to written in the program itself. For example, we can generate a string
containing Python code at runtime and then execute these statements using the e x e c
statement:
>>> exec('print("Hello World")')
Hello World
Similarly, the e v a l function is used to evaluate valid Python expressions which are stored
in a string. A simple example is shown below.
>>> eval('2*3')
6
Python en:More
106
The assert statement
The a s s e r t 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 a s s e r t statement is ideal in this situation. When
the assert statement fails, an A s s e r t i o n E r r o r is raised.
>
>
>
'
>
[
>
T
>
>
>
i
>
]
>
r
>
>
>
t
>
>
a
F
Ass
m
a
m
em
m
y
s
y
'
y
list = ['item']
sert len(mylist) >= 1
list.pop()
list
ass
ceba
ile
erti
e
c
"
o
r
k
<
n
t l
(m
std
Err
e
o
i
o
n(mylist) >= 1
st recent call last):
n>", line 1, in <module>
r
The a s s e r t 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.
The repr function
The r e p r function is used to obtain a canonical string representation of the object. The
interesting part is that you will have e v a l ( r e p r ( o b j e c t ) ) = = o b j e c t most of the time.
>
>
>
"
>
[
>
T
>
>
>
[
>
'
>
r
>
>
>
'
>
i
>
u
i
i
r
it
e
te
e
e
.
e
e
v
m
v
=
a
p
m
a
'
a
p
r
'
l
]
l
[
p
(
]
(
]
end('item')
i)
"
repr(i))
(repr(i)) == i
Basically, the r e p r function is used to obtain a printable representation of the object. You
can control what your classes return for the r e p r function by defining the _ _ r e p r _ _
method in your class.
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.
Python en:More
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Python en: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)
Create a class to represent the person'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 a mail (http:/ / www. swaroopch. com/ contact/ ) thanking me for this great book ;-)
. This step is optional but recommended. Also, please consider making a donation,
contributing improvements or volunteering translations to support the continued
development of this book.
If you found that program easy, here's another one:
Implement the replace command (http:/ / unixhelp. ed. ac. uk/ CGI/
man-cgi?replace). 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, here are some ways to continue your journey with Python:
107
Python en:What Next
Example Code
The best way to learn a programming language is to write a lot of code and read a lot of
code:
•
•
•
•
The PLEAC project (http:/ / pleac. sourceforge. net/ pleac_python/ index. html)
Rosetta code repository (http:/ / www. rosettacode. org/ wiki/ Category:Python)
Python examples at java2s (http:/ / www. java2s. com/ Code/ Python/ CatalogPython. htm)
Python Cookbook (http:/ / code. activestate. com/ recipes/ langs/ python/ ) 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.
Questions and Answers
•
•
•
•
Official Python Dos and Don'ts (http:/ / docs. python. org/ dev/ howto/ doanddont. html)
Official Python FAQ (http:/ / www. python. org/ doc/ faq/ general/ )
Norvig's list of Infrequently Asked Questions (http:/ / norvig. com/ python-iaq.html)
Python Interview Q & A (http:/ / dev. fyicenter. com/ Interview-Questions/ Python/ index.
html)
• StackOverflow questions tagged with python (http:/ / beta. stackoverflow. com/
questions/ tagged/ python)
Tips and Tricks
• Python Tips & Tricks (http:/ / www. siafoo. net/ article/ 52)
• Advanced Software Carpentry using Python (http:/ / ivory. idyll. org/ articles/
advanced-swc/)
• Charming Python (http:/ / gnosis. cx/ publish/ tech_index_cp. html) is an excellent series
of Python-related articles by David Mertz.
Books, Papers, Tutorials, Videos
The logical next step after this book is to read Mark Pilgrim's awesome Dive Into Python
(http:/ / www. diveintopython. org) book which you can read fully online as well. The Dive
Into Python book explores topics such as regular expressions, XML processing, web
services, unit testing, etc. in detail.
Other useful resources are:
• ShowMeDo videos for Python (http:/ / showmedo. com/ videos/ python)
• GoogleTechTalks videos on Python (http:/ / youtube. com/
results?search_query=googletechtalks+python)
• Awaretek's comprehensive list of Python tutorials (http:/ / www. awaretek. com/ tutorials.
html)
• The Effbot's Python Zone (http:/ / effbot. org/ zone/ )
• Links at the end of every Python-URL! email (http:/ / groups. google. com/ group/ comp.
lang. python. announce/ t/ 37de95ef0326293d)
• Python Papers (http:/ / pythonpapers. org)
108
Python en:What Next
Discussion
If you are stuck with a Python problem, and don't know whom to ask, then the
comp.lang.python discussion group (http:/ / groups. google. com/ group/ comp. lang. python/
topics) is the best place to ask your question.
Make sure you do your homework and have tried solving the problem yourself first.
News
If you want to learn what is the latest in the world of Python, then follow the Official Python
Planet (http:/ / planet. python. org) and/or the Unofficial Python Planet (http:/ / www.
planetpython. org).
Installing libraries
There are a huge number of open source libraries at the Python Package Index (http:/ /
pypi. python. org/ pypi) which you can use in your own programs.
To install and use these libraries, you can use Philip J. Eby's excellent EasyInstall tool
(http:/ / peak. telecommunity. com/ DevCenter/ EasyInstall#using-easy-install).
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:
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 (http:/ / zetcode. com/ tutorials/ pyqt4/ )
or the PyQt book (http:/ / www. qtrac. eu/ pyqtbook. html).
PyGTK
This is the Python binding for the GTK+ toolkit which is the foundation upon which
GNOME is built. GTK+ has many quirks in usage but once you become comfortable,
you can create GUI apps fast. The Glade graphical interface designer is indispensable.
The documentation is yet to improve. GTK+ works well on Linux but its port to
Windows is incomplete. You can create both free as well as proprietary software using
GTK+. To get started, read the PyGTK tutorial (http:/ / www. pygtk. org/ tutorial. html).
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) (http:/ / spe. pycs. net/ ) and
109
Python en:What Next
110
the wxGlade (http:/ / wxglade. sourceforge. net/ ) GUI builder. You can create free as
well as proprietary software using wxPython. To get started, read the wxPython
tutorial (http:/ / zetcode. com/ wxpython/ ).
TkInter
This is one of the oldest GUI toolkits in existence. If you have used IDLE, you have
seen a TkInter program at work. It doesn't have one of the best look & feel because it
has an old-school look to it. TkInter is portable and works on both Linux/Unix as well
as Windows. Importantly, TkInter is part of the standard Python distribution. To get
started, read the Tkinter tutorial (http:/ / www. pythonware. com/ library/ tkinter/
introduction/ ).
For more choices, see the GuiProgramming wiki page at the official python website (http:/ /
www. python. org/ cgi-bin/ moinmoin/ GuiProgramming).
Summary of GUI Tools
Unfortunately, there is no one standard GUI tool for Python. I suggest that you choose one
of the above tools depending on your situation. The first factor is whether you are willing to
pay to use any of the GUI tools. The second factor is whether you want the program to run
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.
For a more detailed and comprehensive analysis, see Page 26 of the The Python Papers,
Volume 3, Issue 1 (http:/ / archive. pythonpapers. org/ ThePythonPapersVolume3Issue1. pdf).
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 (http:/ / www. jython. org)
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
(http:/
/
www.
aspx?ProjectName=IronPython)
codeplex.
com/
Wiki/
View.
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 (http:/ / codespeak. net/ pypy/ dist/ pypy/ doc/ home. html)
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 (http:/ / www. stackless. com)
A Python implementation that is specialized for thread-based performance.
Python en:What Next
There are also others such as CLPython (http:/ / common-lisp. net/ project/ clpython/ ) - a
Python implementation written in Common Lisp and IronMonkey (http:/ / wiki. mozilla. org/
Tamarin: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.
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!
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Python en:Appendix FLOSS
Free/Libre and Open Source Software (FLOSS)
FLOSS (http:/ / en. wikipedia. org/ wiki/ 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 operating system that the whole world is slowly embracing! It
was started by Linus Torvalds as a student. Now, it is giving competition to Microsoft
Windows. [ Linux Kernel (http:/ / www. kernel. org) ]
• 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 Linux off the CD! This allows you to completely try out the
new OS before installing it on your computer. [ Ubuntu Linux (http:/ / www. ubuntu.
com) ]
• OpenOffice.org. This is an excellent 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. [ OpenOffice
(http:/ / www. openoffice. org) ]
• Mozilla Firefox. This is the next generation web browser which is giving great
competition to Internet Explorer. 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.
111
Python en:Appendix FLOSS
• Its companion product Thunderbird is an excellent email client that makes reading email
a snap. [ Mozilla Firefox (http:/ / www. mozilla. org/ products/ firefox), Mozilla
Thunderbird (http:/ / www. mozilla. org/ products/ thunderbird) ]
• Mono. This is an open source implementation of the Microsoft .NET platform. It allows
.NET applications to be created and run on Linux, Windows, FreeBSD, Mac OS and many
other platforms as well. [ Mono (http:/ / www. mono-project. com), ECMA (http:/ / www.
ecma-international. org), Microsoft .NET (http:/ / www. microsoft. com/ net) ]
• Apache web server. This is the popular open source web server. In fact, it is the most
popular web server on the planet! It runs nearly more than half of the websites out there.
Yes, that's right - Apache handles more websites than all the competition (including
Microsoft IIS) combined. [ Apache (http:/ / httpd. apache. org) ]
• MySQL. This is an extremely popular open source database server. It is most famous for
it's blazing speed. It is the M in the famous LAMP stack which runs most of the websites
on the internet. [ MySQL (http:/ / www. mysql. com) ]
• 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? ;-) [ VLC media player (http:/ /
www. videolan. org/ vlc/ ) ]
• GeexBox is a Linux distribution that is designed to play movies as soon as you boot up
from the CD! [ GeexBox (http:/ / geexbox. org/ en/ start. html) ]
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 (http:/ / www. linux. com)
LinuxToday (http:/ / www. linuxtoday.com)
NewsForge (http:/ / www. newsforge. com)
DistroWatch (http:/ / www. distrowatch. com)
Visit the following websites for more information on FLOSS:
• SourceForge (http:/ / www. sourceforge. net)
• FreshMeat (http:/ / www. freshmeat. net)
So, go ahead and explore the vast, free and open world of FLOSS!
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112
Python en:Appendix About
Python en:Appendix About
Colophon
Almost all of the software that I have used in the creation of this book are free and open
source software.
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).
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. The standard default
fonts are used as well. The standard fonts are used as well. 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.
Now
For this seventh draft, I'm using MediaWiki (http:/ / www. mediawiki. org) as the basis of my
setup (http:/ / www. swaroopch. com/ notes/ ). Now I edit everything online and the readers
can directly read/edit/discuss within the wiki website.
I still use Vim for editing thanks to the ViewSourceWith extension for Firefox (https:/ /
addons. mozilla. org/ en-US/ firefox/ addon/ 394) that integrates with Vim.
113
Python en:Appendix About
About The Author
http:/ / www. swaroopch. com/ about/
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Contributors: Swaroop
Python en:Appendix Revision History
• 1.90
• 04/09/2008 and still in progress
• Revival after a gap of 3.5 years!
• Updating to Python 3.0
• Rewrite using MediaWiki (again)
• 1.20
• 13/01/2005
• Complete rewrite using Quanta+ on FC3 with lot of corrections and updates. Many
new examples. Rewrote my DocBook setup from scratch.
• 1.15
• 28/03/2004
• Minor revisions
• 1.12
• 16/03/2004
• Additions and corrections.
• 1.10
• 09/03/2004
• More typo corrections, thanks to many enthusiastic and helpful readers.
• 1.00
• 08/03/2004
• After tremendous feedback and suggestions from readers, I have made significant
revisions to the content along with typo corrections.
• 0.99
• 22/02/2004
• Added a new chapter on modules. Added details about variable number of arguments
in functions.
• 0.98
• 16/02/2004
• Wrote a Python script and CSS stylesheet to improve XHTML output, including a
crude-yet-functional lexical analyzer for automatic VIM-like syntax highlighting of the
program listings.
• 0.97
• 13/02/2004
• Another completely rewritten draft, in DocBook XML (again). Book has improved a lot
- it is more coherent and readable.
114
Python en:Appendix Revision History
• 0.93
• 25/01/2004
• Added IDLE talk and more Windows-specific stuff
• 0.92
• 05/01/2004
• Changes to few examples.
• 0.91
• 30/12/2003
• Corrected typos. Improvised many topics.
• 0.90
• 18/12/2003
• Added 2 more chapters. OpenOffice format with revisions.
• 0.60
• 21/11/2003
• Fully rewritten and expanded.
• 0.20
• 20/11/2003
• Corrected some typos and errors.
• 0.15
• 20/11/2003
• Converted to DocBook XML.
• 0.10
• 14/11/2003
• Initial draft using KWord.
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115
Python en:Appendix Changes for Python 3000
Python en:Appendix Changes for
Python 3000
• Vim and Emacs editors
• http:/ / henry. precheur. org/ 2008/ 4/ 18/ Indenting%20Python%20with%20VIM. html
• http:/ / www. enigmacurry. com/ 2008/ 05/ 09/ emacs-as-a-powerful-python-ide/
• String - unicode only
• http:/ / docs. python. org/ dev/ 3. 0/ tutorial/ introduction. html#about-unicode
• Non-ASCII identifiers allowed
• http:/ / www. python. org/ dev/ peps/ pep-3131/
• print() function
• http:/ / www. python. org/ dev/ peps/ pep-3105/
• raw_input() becomes input()
• http:/ / www. python. org/ dev/ peps/ pep-3111/
• Integer Literal Support and Syntax
• http:/ / www. python. org/ dev/ peps/ pep-3127/
• nonlocal statement
• http:/ / www. python. org/ dev/ peps/ pep-3104/
• Functions can take * argument (varargs) for lists and keyword-only arguments
• http:/ / www. python. org/ dev/ peps/ pep-3102/
• Functions can have annotations (make a passing note?)
• http:/ / www. python. org/ dev/ peps/ pep-3107/
• Better explanation of modules, packages and their organization (including __init__.py,
etc.)
• http:/ / ivory. idyll. org/ articles/ advanced-swc/#packages
• String .format() instead of % operator
• http:/ / www. python. org/ dev/ peps/ pep-3101/
• http:/ / docs. python. org/ dev/ library/ string. html#formatstrings
• Dict method changes
• http:/ / www. python. org/ dev/ peps/ pep-3106/
• Built-in set class, in data structures chapter
• Problem Solving
• Use http:/ / gnuwin32. sourceforge. net/ packages/ zip. htm on Windows
• Classes
• http:/ / docs. python. org/ dev/ 3. 0/ reference/ datamodel. html
• Metaclasses
• http:/ / www. python. org/ dev/ peps/ pep-3115/
• Abstract Base Classes
• http:/ / www. python. org/ dev/ peps/ pep-3119/
• Not sure if any changes required for New I/O
• http:/ / www. python. org/ dev/ peps/ pep-3116/
• Exception handling
116
Python en:Appendix Changes for Python 3000
• http:/ / www. python. org/ dev/ peps/ pep-0352/
• http:/ / www. python. org/ dev/ peps/ pep-3109/
• http:/ / www. python. org/ dev/ peps/ pep-3110/
• Standard Library - interesting additions
•
•
•
•
•
•
Reorganization : http:/ / www. python. org/ dev/ peps/ pep-3108/
http:/ / docs. python. org/ dev/ library/ warnings. html
http:/ / docs. python. org/ dev/ library/ logging. html (important)
http:/ / docs. python. org/ dev/ library/ urllib. html
http:/ / docs. python. org/ dev/ library/ json. html
Debugging
• http:/ / docs. python. org/ dev/ library/ pdb. html
• http:/ / docs. python. org/ dev/ 3. 0/ library/ trace. html
• eval, repr/ascii functions
• getopt/optparse - how to write a standard command-line program using python?
• something like replace?
• http:/ / hpux. connect. org. uk/ hppd/ hpux/ Users/ replace-2. 24/ man. html
• More
• Unpacking can take * argument
• http:/ / www. python. org/ dev/ peps/ pep-3132/
• with statement
• http:/ / www. python. org/ dev/ peps/ pep-0343/
• What Next?
• Implement 'replace'
• http:/ / unixhelp. ed. ac. uk/ CGI/ man-cgi?replace
• Mention use of PyPI
• Q&A
• http:/ / docs. python. org/ dev/ howto/ doanddont. html
• http:/ / www. python. org/ doc/ faq/ general/
• http:/ / norvig. com/ python-iaq.html
• Books & Resources
•
•
•
•
•
http:/ / www. coderholic. com/ free-python-programming-books/
http:/ / pythonpapers. org
http:/ / www. mobilepythonbook.org
http:/ / effbot. org/ zone/
Links at the end of every Python-URL! email
• http:/ / groups. google. com/ group/ comp. lang. python. announce/ t/
37de95ef0326293d
• Examples
• http:/ / www. rosettacode. org
• http:/ / dev. fyicenter. com/ Interview-Questions/ Python/ index. html
• http:/ / www. java2s. com/ Code/ Python/ CatalogPython. htm
• Tips & Tricks
• http:/ / www. siafoo. net/ article/ 52
Source: http:/ / www. swaroopch. com/ mediawiki/ index. php? oldid=242
117
Python en:Appendix Changes for Python 3000
Contributors: Swaroop
License
Creative Commons Attribution-Share Alike 3.0 Unported
http:/ / creativecommons. org/ licenses/ by-sa/ 3. 0/
118
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