This slide is very useful for python beginners.Python training in Chennai at Credo Systemz helps you to get an extensive knowledge of Python programming language. Python course training by Credo Systemz is an instructor-led training conducted in Chennai premises.

1. PYTHON LNGUAGE
Overview of Python
Benish.D
Cs.benish272@gmail.com

2. PYTHON INTRODUCTION
 Python is a widely used general-purpose, high level programming language. It was
initially designed by Guido van Rossum in 1991 and developed by Python Software
Foundation.
 It was mainly developed for emphasis on code readability, and its syntax allows
programmers to express concepts in fewer lines of code.
 Python is a programming language that lets you work quickly and integrate systems
more efficiently.
 There are two major Python versions- Python 2 and Python 3. Both are quite different.
8 reasons you should be using Python
1. Quick to setup:
 Python is easy to download, even for the newbie; careful documentation takes you
through the download and setup steps in either Windows, Mac, or Linux
environments.
 Tons of support and documentation make Python learning fairly manageable.
 If you want to jump right into Python without any need for download on your
machine, just go to one of many tutorials like Credo systemz.
2. Python is fast:
 Python has developed a reputation as a solid, high-performance language. Lots has
been done in recent years to get to this point.
 The PyPy project aims to speed up Python as a whole (and is doing a great job of it).
 And Numba is another tool that can offer amazing speedups by implementing high
performance functions written directly in Python.

3. 3. Python has broad support:
 The applications for Python are broad and varied; it’s used by individuals and big
industry players alike in everything from systems automation, testing, and ETL to
gaming, CGI and web development.
 Disney uses Python to help power their creative process. And Mozilla releases tons
of open source packages built in Python.
 Bank of America uses Python to build new products and interfaces within the bank’s
technology infrastructure.
4. Ease of use:
 Python gets a lot of accolades for being easy to learn, and rightfully so. The learning
curve is very gradual.
 Other languages can be quite steep. Python places a heavy emphasis on readability, as
shown by its comparison with other object-oriented languages.
 The first code example below is written in C++:
 Python is much more intuitive looking and in fact appears like everyday English.
 As one writer has well said, “With Python and the proper combination of ambition
and attention, you could whip together a game in a day knowing nothing before you
started.”
5. Big Data:
 Python’s growing ecosystem and support network has been significantly enhanced by
the popularization of Big Data in recent years. Based on a 2013 poll, Python is the
second most popular language in data science, used by 39% of respondents (after R’s
61%).
 Python offers a very mature numeric and scientific computing ecosystem (NumPy &
SciPy) and in the trade-off between scale and sophistication, Python is seen as a nice
compromise.
 The advantage of a rich data community with large amounts of toolkits and features
makes Python a powerful tool for medium-scale data processing.
6. Money:
 Across a number of industry metrics and rankings, demand for Python job skills are
rising sharply. For example, while the overall hiring demand for IT professionals

4. dipped year over year by 5% as of January 2014, the opposite was the case for Python
programmers.
 During this period demand rose by 8.7%. The average salary for Python programmers
in the U.S. is just over $100K and demand continues to rise.
7. Why not web development with Python?
 Python is usually associated as a scripting language heavily used in Big Data and
analytics, and there’s no doubt that is where it excels. But did you know that it can be
used to build online applications? In case you didn’t know.
 Django — the popular open source web application framework written in Python —
is the foundation of such sites as Pinterest, The New York Times, The Guardian, Bit
Bucket, and Instagram.
 Python is a growing ecosystem for web development; here are some options to
explore.
8. Easy ways to learn:
 There are many ways to learn code today, and in particular Python – MOOCs, online
tutorials, and code bootcamps (including online options). As an example, Udacity –
one of the first MOOCs – on the market, offered a signature course called Intro to
Computer Science, which since its inception in 2012 has introduced over 400,000
students worldwide to Python.
 The course links theory with practice by having students build an actual search engine
using Python; the course was recently revised to also include the addition of a social
network component.
 Learning Python today has never been easier or more accessible
Disadvantages of Python
 As an interpreted language, Python has a slow speed of execution. It is slower than C
and C++ because it works with an interpreter, not the compiler.

5.  The language is seen as less suitable for mobile development and game development.
It is often used on desktop and server, but there are only several mobile applications
that were developed with Python. Another disadvantage Python has is the runtime
error. The language has a lot of design limits and needs more testing time. The
programmer has the possibility to see bugs only during run time.
 Python has high memory consumption and is not used in web browsers because it is
not secure. Language flexibility is considered among both advantages and
disadvantages of Python.
 Developers like Python for its simplicity in learning and coding, so much that it might
be difficult for some of them to learn and use other languages.
 In spite of all the disadvantages of Python programming language, it has a lot more
pros than cons.
Advantages of Python
 Compared to other programming languages Python is the most broadly applied by the
developers lately. Within the next paragraphs, we will take a look at the advantages of
Python programming language for developers in contrast with other languages.
 The main Python language advantages are that it is easy to read and easy to learn. It is
easier to write a program in Python than in C or C++. With this language, you gain
the possibility to think clearly while coding, which also makes the code easier to
sustain. Which reduces the cost for maintenance of the program and seen as one of
Python programming advantages.
 So, what are the advantages of Python that make this language special? The answer is
that Python has some unique characteristics that are valuable for programmers
because they make coding easier. Another advantage of Python programming is that
no bug can originate a segmentation fault.
 An important advantage of Python language is that it has wide applicability, and is
extensively used by scientists, engineers, and mathematicians. It is for this reason that
Python is so useful for prototyping and all kinds of experiments.
 It is used in many groundbreaking fields. It is also used when producing animation for
movies and in machine learning.
 The language includes a large library with memory management which is another one
of the advantages of Python programming.
Advantages of using Python over other languages
 C++ or any other typical scripting language might be easier to use for constructing
mobile applications or games, however, Python is better for automating build systems,
collecting test data, server-side applications.
 Going through Python pros and cons, there is a need to highlight one of the most
valuable advantages of Python language.
 Python has far-reaching libraries and blank designs and it’s boosting developer’s
productivity.

6. Is Python easy to learn for beginners?
Our aim is to help you :
 Understand all about Python with our market relevant course.
 Learn Python coding.
 Understand its components from basic to complex like OOPS, inbuilt libraries, etc.
 Understand how to use Python in application across domains of web developments,
graphics, data science etc.
 Become a Python professional so you can build your own apps.
 Give placement support so you can fully exploit enormous job opportunities that
Python brings and earn big.
What are topics in Python?
There are many topics are available for python programming such as follow:
 Classes, Objects, Loops, Exceptions.
 List, Tuples, Dictionary.
 Regular expressions.
 CGI programming.
 Socket programming.
 Multi threading.
 GUI programming.
 Network application Programming
Why Python in Trend Now?
1. Why Python programming is so much in demand nowadays1. First of all, Data
science is booming nowadays. For related development, Python is put to use the most.
Reason?Availability of numerous libraries such as NumPy, ScikitLearn, SciPy,
PyBrain, etc
 Python comes with a data analytics tool, Pandas which is of great use to data scientist
and developers
 Machine learning algorithm is easy to obtain in Python e.g.: Scikit-Learn and
TensorFlow
 Presence of Third party module which makes it compatible with all other
programming languages and platform. Due to it’s increased speed and productivity,
Python is the top prior option for developers in creating complex multi-protocol
network application
2. Apart from the development of artificial intelligence and Data Science application and
programs. Python is extensively used for web, mobile, and desktop-based software
development. Reason? The language is so much simpler to use.

7. 3. Owing to obvious reasons career opportunity of Python is also in an all-time rise. The
major share of the traffic that websites that deal with Python share are owing to this high
demand.It has to be noted that 22% of the Python developers are either 1-2 years of
experience cementing the fact that there is a large requirement of new developers.
Where Python is Used?
Python is used in many application domains. Here's a sampling.
Web and Internet Development
Python offers many choices for web development:
 Frameworks such as Django and Pyramid.
 Micro-frameworks such as Flask and Bottle.
 Advanced content management systems such as Plone and django CMS.
Python's standard library supports many Internet protocols:
 HTML and XML
 JSON
 E-mail processing.
 Support for FTP, IMAP, and other Internet protocols.
 Easy-to-use Socket interface.
And the Package Index has yet more libraries:
 Request, a powerful HTTP client library.
 Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML.
 Feed parser for parsing RSS/Atom feeds.
 Paramiko, implementing the SSH2 protocol.
 Twisted Python, a framework for asynchronous network programming.
Scientific and Numeric:
Python is widely used in Scientific and numeric computing:
 SciPy is a collection of packages for mathematics, science, and engineering.
 Pandas is a data analysis and modeling library.
 I Python is a powerful interactive shell that features easy editing and recording of a
work session, and supports visualizations and parallel computing.
 The Credo Systemz teaches basic skills for scientific computing, running bootcamps
and providing open-access teaching materials.
Education:
Python is a superb language for teaching programming, both at the introductory level and in
more advanced courses.

8.  Books such as How to Think Like a Computer Scientist, Python Programming: An
Introduction to Computer Science, and Practical Programming.
 The Education Special Interest Group is a good place to discuss teaching issues.
Desktop GUIs:
The Tk GUI library is included with most binary distributions of Python.
Some toolkits that are usable on several platforms are available separately:
 wxWidgets
 Kivy, for writing multitouch applications.
 Qt via pyqt or pyside
Platform-specific toolkits are also available:
 GTK+
 Microsoft Foundation Classes through the win32 extensions.
Software Development:
Python is often used as a support language for software developers, for build control and
management, testing, and in many other ways.
 SCons for build control.
 Buildbot and Apache Gump for automated continuous compilation and testing.
 Roundup or Trac for bug tracking and project management.
Business Applications:
Python is also used to build ERP and e-commerce systems:
 Odoo is an all-in-one management software that offers a range of business
applications that form a complete suite of enterprise management applications.
 Tryton is a three-tier high-level general purpose application platform.
Benefits of Learning Python
There are many benefits of learning Python, especially as your first language, which we will
discuss.
Other benefits include:
1) Python can be used to develop prototypes, and quickly because it is so easy to work with
and read.
2) Most automation, data mining, and big data platforms rely on Python. This is because it is
the ideal language to work with for general purpose tasks.

9. 3) Python allows for a more productive coding environment than massive languages like C#
and Java. Experienced coders tend to stay more organized and productive when working with
Python, as well.
4) Python is easy to read, even if you're not a skilled programmer. Anyone can begin working
with the language, all it takes is a bit of patience and a lot of practice. Plus, this makes it an
ideal candidate for use among multi-programmer and large development teams.
5) Python powers Django, a complete and open source web application framework.
Frameworks - like Ruby on Rails - can be used to simplify the development process.
6) It has a massive support base thanks to the fact that it is open source and community
developed. Millions of like-minded developers work with the language on a daily basis and
continue to improve core functionality. The latest version of Python continues to receive
enhancements and updates as time progresses. This is a great way to network with other
developers.
I believe This article gave the required information about Python.
To know more click the link below Python programming language
Comparing Python to Other Languages
 Python is often compared to other interpreted languages such as Java, JavaScript,
Perl, Tcl, or Smalltalk. Comparisons to C++, Common Lisp and Scheme can also be
enlightening. In this section I will briefly compare Python to each of these languages.
 These comparisons concentrate on language issues only. In practice, the choice of a
programming language is often dictated by other real-world constraints such as cost,
availability, training, and prior investment, or even emotional attachment.

10. Java
Python programs are generally expected to run slower than Java programs, but they also take
much less time to develop. Python programs are typically 3-5 times shorter than equivalent
Java programs. This difference can be attributed to Python's built-in high-level data types and
its dynamic typing. For example, a Python programmer wastes no time declaring the types of
arguments or variables, and Python's powerful polymorphic list and dictionary types, for
which rich syntactic support is built straight into the language, find a use in almost every
Python program.
For these reasons, Python is much better suited as a "glue" language, while Java is better
characterized as a low-level implementation language. In fact, the two together make an
excellent combination. Components can be developed in Java and combined to form
applications in Python; Python can also be used to prototype components until their design
can be "hardened" in a Java implementation.
Java script
Python's "object-based" subset is roughly equivalent to JavaScript. Like JavaScript (and
unlike Java), Python supports a programming style that uses simple functions and variables
without engaging in class definitions. However, for JavaScript, that's all there is. Python, on
the other hand, supports writing much larger programs and better code reuse through a true
object-oriented programming style, where classes and inheritance play an important role.
Perl
Python and Perl come from a similar background (Unix scripting, which both have long
outgrown), and sport many similar features, but have a different philosophy. Perl emphasizes
support for common application-oriented tasks, e.g. by having built-in regular expressions,
file scanning and report generating features.
Tcl
Like Python, Tcl is usable as an application extension language, as well as a stand-alone
programming language. However, Tcl, which traditionally stores all data as strings, is weak
on data structures, and executes typical code much slower than Python. Tcl also lacks
features needed for writing large programs, such as modular namespaces. Thus, while a
"typical" large application using Tcl usually contains Tcl extensions written in C or C++ that
are specific to that application, an equivalent Python application can often be written in "pure
Python".
Tcl 8.0 addresses the speed issuse by providing a bytecode compiler with limited data type
support, and adds namespaces. However, it is still a much more cumbersome programming
language.
Smalltalk
Perhaps the biggest difference between Python and Smalltalk is Python's more "mainstream"
syntax, which gives it a leg up on programmer training. Like Smalltalk, Python has dynamic

11. typing and binding, and everything in Python is an object. However, Python distinguishes
built-in object types from user-defined classes, and currently doesn't allow inheritance from
built-in types.
Python has a different philosophy regarding the development environment and distribution of
code. Where Smalltalk traditionally has a monolithic "system image" which comprises both
the environment and the user's program, Python stores both standard modules and user
modules in individual files which can easily be rearranged or distributed outside the system.
C++
Almost everything said for Java also applies for C++, just more so: where Python code is
typically 3-5 times shorter than equivalent Java code, it is often 5-10 times shorter than
equivalent C++ code! Anecdotal evidence suggests that one Python programmer can finish in
two months what two C++ programmers can't complete in a year. Python shines as a glue
language, used to combine components written in C++.
Common Lisp and Scheme
These languages are close to Python in their dynamic semantics, but so different in their
approach to syntax that a comparison becomes almost a religious argument: is Lisp's lack of
syntax an advantage or a disadvantage? It should be noted that Python has introspective
capabilities similar to those of Lisp, and Python programs can construct and execute program
fragments on the fly. Usually, real-world properties are decisive: Common Lisp is big (in
every sense), and the Scheme world is fragmented between many incompatible versions,
where Python has a single, free, compact implementation.
Top 10 Reasons To Learn Python

12. Programming languages have been around for ages, and every decade sees the launch of a
new language sweeping developers off their feet. Python is considered as one of the most
popular and in-demand programming language. A recent Stack Overflow survey showed that
Python has taken over languages such as Java, C, C++ and has made its way to the top. This
makes Python certification one of the most sought-after programming certifications. Through
this blog, I will be listing down the top 10 reasons to learn Python.
Get ready to fall in love with Python!!
Below are the major features and applications due to which people choose Python as their
first programming language:
1. Python’s Popularity & High Salary
 Python engineers have some of the highest salaries in the industry. The average
Python Developer salary in the United States is approximately $116,028 per year.
 Also, Python has a strong spike in popularity over the last 1year. Refer the below
screenshot taken from Google Trends.
 I hope my blog on “Top 10 reasons to learn Python” was relevant for you. To get in-
depth knowledge on Python along with its various applications, check out our
interactive, live-online Credo systemz Python training here, that comes with 24*7
support to guide you throughout your learning period.
2. Data Science
 Python is the leading language of many data scientist. For years, academic scholars
and private researchers were using the MATLAB language for scientific research but
it all started to change with the release of Python numerical engines such as
‘Numpy’ and ‘Pandas’.
 Python also deals with the tabular, matrix as well as statistical data and it even
visualizes it with popular libraries such as ‘Matplotlib’ and ‘Seaborn‘.
3. Scripting & Automation
Many people only knows that Python is a programming language, but Python can also be
used as Scripting language. In scripting:
 The code is written in the form of scripts and get executed
 Machine reads and interprets the code
 Error checking is done during Runtime
Once the code is checked, it can be used several times. So by automation, you can automate
certain tasks in a program.
4. Big Data
 Python handles a lot of hassles of data. It supports parallel computing where you can
use Python for Hadoop as well. In Python, you have a library called “Pydoop” and

13. you can write a MapReduce program in Python and process data present in the HDFS
cluster.
 There are other libraries such as ‘Dask‘ and ‘Pyspark‘ for big data
processing. Therefore, Python is widely used for Big Data where you can easily
process it!
5. Testing Framework
 Python is great for validating ideas or products for established companies. Python has
many built-in testing frameworks that covers debugging & fastest workflows. There
are a lot of tools and modules to make things easier such as Selenium and Splinter.
 It supports testing with cross-platform & cross-browser with frameworks such
as PyTest and RobotFramework. Testing is a tedious task and Python is the booster
for it, so every tester should definitely go for it!
6. Computer Graphics
 Python is largely used in small, large, online or offline projects. It is used to build
GUI and desktop applications. It uses ‘Tkinter‘ library to provide fast & easy way to
create applications.
 It is also used in game development where you can write the logic of using a module
‘pygame’ which also runs on android devices.
7. Artificial Intelligence
 AI is the next huge development in the tech world. You can actually make a machine
mimic the human brain which has the power to think, analyze and make decisions.
 Furthermore, libraries such as Keras and TensorFlow bring machine learning
functionality into the mix. It gives the ability to learn without being explicitly
programmed. Also, we have libraries such as openCv that helps computer vision or
image recognition.
8. Web Development
 Python has an array of frameworks for developing websites. The popular frameworks
are Django, Flask, Pylons etc. Since these frameworks are written in Python, its the
core reason which makes the code a lot faster and stable.
 You can also perform web scraping where you can fetch details from any other
websites. You will also be impressed as many websites such as Instagram, bit bucket,
Pinterest are build on these frameworks only.
9. Portable & Extensible
 The portable and extensible properties of Python allow you to perform cross-language
operations seamlessly. Python is supported by most platforms present in the industry
today ranging from Windows to Linux to Macintosh, Solaris, Play station, among
others.
 Python’s extensibility features allow you to integrate Java as well as .NET
components. You can also invoke C and C++ libraries.

14. 10. Simple & Easy To Learn
So at number 10, Python is extremely simple and easy to learn. It is a very powerful language
and it closely resembles the English language!
So, what contributes to its simplicity? Python is
 Free & open source
 High-level
 Interpreted
 Blessed with large community
Furthermore, in Python, you don’t have to deal with complex syntax.
If you have to print ‘hello world’, you have to write above three lines whereas in Python, just
one line is sufficient to print “hello world”. It’s that SIMPLE guys!
So the 10th reason lies in the simplicity of the code which makes the best suit for beginners.
Conclusion
I believe the trial has shown conclusively that it is both possible and desirable to use Python
as the principal teaching language:
 it is Free (as in both cost and source code).
 it is trivial to install on a Windows PC allowing students to take their interest further.
For many the hurdle of installing a Pascal or C compiler on a Windows machine is
either too expensive or too complicated;
 it is a flexible tool that allows both the teaching of traditional procedural
programming and modern OOP; It can be used to teach a large number of transferable
skills;
 it is a real-world programming language that can be and is used in academia and the
commercial world;
 it appears to be quicker to learn and, in combination with its many libraries, this offers
the possibility of more rapid student development allowing the course to be made
more challenging and varied;
 and most importantly, its clean syntax offers increased understanding and enjoyment
for students;
Python should be used as the first year teaching language. If used it will be possible to teach
students more programming and less of the peculiarities of a particular language. Teaching a
mid-level language like C in just one day is inadvisable. Too much time must be spent
teaching C and not enough time teaching generic skills to students with no programming
experience.
In conclusion, Python offers the optimum compromise of teachability and applicability.

15. where-can-I-learn-Python-easily
What is python ?
There are two primary factors why we have to use Python® is software quality and developer
productivity. It’s commonly used in a variety of domains like Web programming, Internet
Scripting, database, numeric and scientific programming, Gaming thus it also known as
general purpose language.
The major technical strengths of this language are readability, easy to use and learn, it’s free
and supported object-oriented, it is portable.
Python Training has dynamically typed language so every operation can be done on the fly.
Python codes can be shipped or placed on the web more securely as it execution involves
Python® Virtual Machine ( PVM ) and bytecode compilation which is platform independent.
Python is the high level language with features of object oriented programming.
 Clear syntax and expressive
 Supports Object Oriented and Functional Programming
 Highly Portable, runs almost anywhere- highend server, workstations
 Uses machine independent byte codes
 Designed to be extensible using C/C++,thus allowing access to many external
libraries
Below are the Python implementations that we see in the coding world.
 Cpython ( c ) (most common)
 PyPy (python)
 JyThon (Java)
 IronPython(.Net)
Important Features
 Programs are written as text files ,and with the .py extension
 Each module has its own namespace
 Name space within a module is global
 .py files executed directly are programs or scripts
 .py files referenced by import statement are modules
 Variables are not needed for introduction
 Indentation plays a crucial role in here
Click Here to Check Latest Updated – Python Interview Questions and Answers
Python® can communicate to other parts of the application using the variety of component
integration. For an example using CPython component, python can call C/C++ libraries and
can be called from C/C++ programs. It will also have support for accessing java objects,
.NET objects through Jython, IronPython respectively.

16. As in Python, everything is the object, every operation seems to be easier than other scripting
languages. Python® codes are equal to one third and one-fifth of C/C++ and Java programs
in term of a number of lines. It has powerful memory management to reuse garbage
collections.
Click Here to Check Latest Updated – Python Tutorials
 Python supports different types of objects like numbers, string, tuples, list, the
dictionary to store data and do operations on stored data. It has common methods and
operations on sequence objects ( list, string, tuples ) like indexing, slicing, extended
slicing.
Why it is in Trend ?
 This is because Python is in trend with its myriad uses in data science, machine
learning, deep learning, artificial intelligence, etc. And since so many of the current
students are learning Python, it is obvious that its importance will increase even more
in the future.
So Why is Python So Popular?
 We have already established that Python is the fastest growing programming language
and also well on the way to becoming the most popular programming language in the
world. Now, let’s try to understand the reasons for this incredible phenomenon.
1. Python is Easy To Use
 Who likes excessively complicated things? No one, that’s who.
 And that’s one of the reasons for the growing popularity of Python.
 It is simple with an easily readable syntax. In addition to this, Python is also
supremely efficient.
 It allows developers to complete more work using fewer lines of code.
2. Python has a Supportive Community
 Python has been around since 1990 and that is ample time to create a supportive
community.
 Because of this support, Python learners can easily improve their knowledge, which
only leads to increasing popularity.
3. Python has multiple Libraries and Frameworks
 Python is already quite popular and consequently, it has hundreds of different libraries
and frameworks that can be used by developers.
 Some of the popular libraries of Python are NumPy and SciPy for scientific
computing, Django for web development, BeautifulSoup
for XML and HTML parsing, scikit-learn for machine learning applications, nltk for
natural language processing, etc.

17. 4. Python has Corporate Support
 Did you think that a language becomes popular just like that? No….Corporate support
is a big part of it.
 Many top companies such as Google, Facebook, Mozilla, Amazon, Quora, etc use
Python for their products.
 In fact, Google has practically adopted Python for many of its platforms and
applications.
 It also provides various guides and tutorials for working with Python in Credo
systemz.
5. Python is used in Big Data and Machine Learning
 Big Data and Machine Learning are the hottest trends in modern times. And Python is
used for much of the research and development in these fields.
 There are many Python tools for analytics and data science such as Scikit-Learn,
Theano, etc. Also, Python is used with big data using tools such as Pandas, PySpark,
etc.
Why Learn Python ?
If you are new to coding, you should start with the Python language because it is powerful
without being overly complicated. Python is a relatively new language, so it’s more
streamlined than older languages, making it more intuitive and quicker to pick up.
If you are looking to add a language to your existing quiver, the demand for Python
programmers is huge. The average Python developer salary in the US is over $120,000.
That’s not shabby!
If you are really interested to learn Python language. There is a Python Course available
at Credo Systemz which is the leading Python Training Institute in Chennai . And also
provides a one-hour free demo session in Python. You can decide whether to join or not after
the session.
Why should I learn python from Besant Technologies?
We are the best Python training institute in Chennai where the training’s in python are
provided with real time example. Our Python Course in Chennai Syllabus is designed
according to the needs of the corporate client which will surely help you to clear the
interviews easily.
From the past 12 years, our goal is to build a successful career of the students. At Credo
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MNC’s. Below given are 10 reasons that will clear all your doubts before joining us.
 Best Faculty: Whether you are new to python or already know python our faculty will
deal with you accordingly. The faculty at Credo systemz are professionals in the field

18. of programming especially python with 10+ years of experience. Our faculty
members have proven their knowledge in python with the success of their students.
 Updated and Relevant content: Our courses are designed by the faculty which has
more than 10 years of experience in Python. We periodically update our courses and
keep them simple so that it is easy to understand by a learner.
 Personal attention to each member: Our faculty provides attention to each and every
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19. 10 Things To Know About Python
let’s discuss ten of some of the important concepts that Python programmers should know.
1. Python Version Numbers
While this is technically not a programming feature, it’s still crucial to know the current
versions of Python just so we’re all on the same page. Python versions are numbered as
A.B.C., where the three letters represent (in decreasing order) important changes in the
language. So, for instance, going from 2.7.3 to 2.7.4 means that the Python build made some
minor bug fixes, while going from 2.xx to 3.xx represents a major change. Note the ‘x’ here,
which is intentional; if a Python feature can apply to version number 2.7.C for any valid ‘C’
value, then we put in an ‘x’ and refer to Python 2.7.x. We can also omit the ‘x’ entirely and
just use 2.7.
As of this writing (July 2013), Python has two stable versions commonly used: 2.7 and 3.3.
Less important is the third character, but right now 2.7.5 and 3.3.2 are the current versions,
both of which were released on May 15, 2013. The short answer is that, while both 2.7 and
3.3 are perfectly fine to use, 3.3 is the future of the language and someone just starting
Python today should probably use Python 3.3 over 2.7. Of course, if one is in the middle of
an extensive research project that makes heavy use of 2.7, then it might not make sense to
upgrade to 3.3 right away. This is actually quite similar to my current situation, since I’m
using a good number of my own Python 2.7 scripts to help me analyze algorithmic
combinatorics on words. Once August arrives, I’ll fully transition to Python 3.3. In the

20. meantime, though, I’ve done quite a bit of reading on Python 3’s new versions and I have
3.3.2 installed (in addition to 2.7.4) on my laptop, so this post and its code syntax will assume
that we’re using Python 3.
One important thing to note, though, is that Python 3 is intentionally backwards
incompatible. Backward compatibility is often a desired feature of programming languages
and software that routinely undergo revisions, since it means that input from older versions
(e.g. older Python programs) can still run under the latest builds. In this case, Python 2 code
will not be guaranteed to run successfully if using Python 3, so some conversion may be
necessary to allow code to properly run. Backwards incompatibility was necessary in order to
allow Python 3 to be more clear, concise and use additional features.
2. Using the Python Shell
Python is an interpreter language. It means it executes the code line by line. Python provides
a Python Shell (also known as Python Interactive Shell) which is used to execute a single
Python command and get the result.
Python Shell waits for the input command from the user. As soon as the user enters the
command, it executes it and displays the result.

21. 3. Using ‘os’ and ‘sys’
What is OS PY?
The OS module in Python provides a way of using operating system dependent
functionality. The functions that the OS module provides allows you to interface with the
underlying operating system that Python is running on – be that Windows, Mac or Linux
What is SYS in Python?
28.1. sys — System-specific parameters and functions. This module provides access to some
variables used or maintained by the interpreter and to functions that interact strongly with the
interpreter. It is always available. ... If no script name was passed to the Python interpreter,
argv[0] is the empty string
First, let’s go over the sys module. Possibly the biggest advantage that it offers to the
programmer is the use of command line inputs to the program. Say you’ve built a large
program that will perform some task that depends on inputs from the user. For instance, in
my machine learning class last semester, I implemented the k-means clustering algorithm.
This is a learning algorithm that is given data and can classify it into groups depending on
how many clusters are given as input. It’s clear that this can be useful in many life
applications. Someone who has standardized data on medical patients’ records (e.g. blood-
sugar levels, height, weight, etc.) may want to classify patients into two “clusters,” which

22. could be (1) healthy or (2) ill. Or perhaps there could be n clusters, where patients classified
into lower numbered clusters have a better outlook than those with high numbers.
4. List Comprehension
List comprehensions provide a concise way to create lists.
It consists of brackets containing an expression followed by a for clause, then
zero or more for or if clauses. The expressions can be anything, meaning you can
put in all kinds of objects in lists.
The result will be a new list resulting from evaluating the expression in the
context of the for and if clauses which follow it.
The list comprehension always returns a result list.
If you used to do it like this:
new_list = []
for i in old_list:
if filter(i):
new_list.append(expressions(i))
You can obtain the same thing using list comprehension:
new_list = [expression(i) for i in old_list if filter(i)]
Syntax
The list comprehension starts with a '[' and ']', to help you remember that the
result is going to be a list.
The basic syntax is
[ expression for item in list if conditional ]
This is equivalent to:
for item in list:
if conditional:
expression
Let's break this down and see what it does
new_list = [expression(i) for i in old_list if filter(i)]
new_list
The new list (result).
expression(i)
Expression is based on the variable used for each element in the old list.
for i in old_list
The word for followed by the variable name to use, followed by the word in the
old list.
if filter(i)
Apply a filter with an If-statement.
This blog shows an example of how to visually break down the list comprehension:
new_range = [i * i for i in range(5) if i % 2 == 0]
Which corresponds to:

23. *result* = [*transform* *iteration* *filter* ]
The * operator is used to repeat. The filter part answers the question if the
item should be transformed.
Examples
Now when we know the syntax of list comprehensions, let's show some examples and
how you can use it.
Create a simple list
Let's start easy by creating a simple list.
x = [i for i in range(10)]
print x
# This will give the output:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
That's how you can create a simple list.
Create a list using loops and list comprehension
For the next example, assume we want to create a list of squares.
# You can either use loops:
squares = []
for x in range(10):
squares.append(x**2)
print squares
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
# Or you can use list comprehensions to get the same result:
squares = [x**2 for x in range(10)]
print squares
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
Just remember the syntax: [ expression for item in list if conditional ]
Multiplying parts of a list.
Multiply every part of a list by three and assign it to a new list.
list1 = [3,4,5]
multiplied = [item*3 for item in list1]
print multiplied
[9,12,15]
Note how the item*3 multiplies each piece by 3.

24. Show the first letter of each word
We will take the first letter of each word and make a list out of it.
listOfWords = ["this","is","a","list","of","words"]
items = [ word[0] for word in listOfWords ]
print items
The output should be: ['t', 'i', 'a', 'l', 'o', 'w']
Lower/Upper case converter
Let's show how easy you can convert lower case / upper case letters.
>>> [x.lower() for x in ["A","B","C"]]
['a', 'b', 'c']
>>> [x.upper() for x in ["a","b","c"]]
['A', 'B', 'C']
Print numbers only from a given string
This example show how to extract all the numbers from a string.
string = "Hello 12345 World"
numbers = [x for x in string if x.isdigit()]
print numbers
>> ['1', '2', '3', '4', '5']
Change x.isdigit() to x.isalpha() if you don't want any numbers.
Parsing a file using list comprehension
In this example, we can see how to get specific lines out from a text file.
Create a text file and put in some text in it.
this is line1
this is line2
this is line3
this is line4
this is line5
Save the file as test.txt
# Then create the filter by using list comprehension:
fh = open("test.txt", "r")
result = [i for i in fh if "line3" in i]
print result
Output: ['this is line3
']

25. Using list comprehension in functions
Now, let's see how we can use list comprehension in functions.
# Create a function and name it double:
def double(x):
return x*2
# If you now just print that function with a value in it, it should look like this:
>>> print double(10)
20
We can easily use list comprehension on that function.
>>> [double(x) for x in range(10)]
print double
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
# You can put in conditions:
>>> [double(x) for x in range(10) if x%2==0]
[0, 4, 8, 12, 16]
# You can add more arguments:
>>> [x+y for x in [10,30,50] for y in [20,40,60]]
[30, 50, 70, 50, 70, 90, 70, 90, 110]
5. Slicing
Python slice function syntax is:
class slice(stop)
class slice(start, stop[, step])
Note that slice function returns slice object. We can pass this object as a set of indices with
sequences such as string, list, tuple etc.
Python slice function allows us to create a stepwise sub-sequence easily without doing
complete iteration on the existing sequence.
slice() function arguments
 start: specifies the start of the index value. It’s optional and defaults to None.
 stop: specifies the end of the index value. This is a mandatory parameter.
 step: specifies the steps to take from start to stop index. It’s an optional parameter and
defaults to None.
Python slice object has read-only data attributes – start, stop and step – which return the
argument values (or default value).
Let’s see how to create slice objects.

26. s = slice(1, 10, 2) # indexes 1,3,5,7,9
print(type(s))
print(s.start)
print(s.stop)
print(s.step)
s = slice(5) # indexes 0,1,2,3,4
print(s.start)
print(s.stop)
print(s.step)
Output:
1
10
2
None
5
None
Python slice object has no use on its own, it’s useful when used in conjunction with
sequences to create a sub-sequence.
6. Dictionaries and Sets
Sets and dictionaries are ideal data structures to be used when your data has no intrinsic
order, but does have a unique object that can be used to reference it (the reference object is
normally a string, but can be any hashable type). This reference object is called the “key,”
while the data is the “value.” Dictionaries and sets are almost identical, except that sets do not
actually contain values: a set is simply a collection of unique keys. As the name implies, sets
are very useful for doing set operations.
Example 4-1. Phone book lookup with a list
def find_phonenumber(phonebook, name):
for n, p in phonebook:
if n == name:
return p
return None
phonebook = [
("John Doe", "555-555-5555"),
("Albert Einstein", "212-555-5555"),
]
print "John Doe's phone number is", find_phonenumber(phonebook, "John Do
7. Copying Structures (and Basic Memory Management)
One of the major challenges in writing (somewhat) large-scale Python programs is to keep
memory usage at a minimum. However, managing memory in Python is easy—if you just
don’t care. Python allocates memory transparently, manages objects using a reference count
system, and frees memory when an object’s reference count falls to zero. In theory, it’s swell.

27. In practice, you need to know a few things about Python memory management to get a
memory-efficient program running. One of the things you should know, or at least get a good
feel about, is the sizes of basic Python objects. Another thing is how Python manages its
memory internally.
So let us begin with the size of basic objects. In Python, there’s not a lot of primitive data
types: there are ints, longs (an unlimited precision version of ints), floats (which are doubles),
tuples, strings, lists, dictionaries, and classes.
8. Generators
Generators are functions that can be paused and resumed on the fly, returning an object that
can be iterated over. Unlike lists, they are lazy and thus produce items one at a time and only
when asked. So they are much more memory efficient when dealing with large data sets. This
article details how to create generator functions and expressions as well as why you
would want to use them in the first place
What are generators in Python?
There is a lot of overhead in building an iterator in Python; we have to implement a class with
__iter__() and __next__() method, keep track of internal states, raise StopIteration when there
was no values to be returned etc.
This is both lengthy and counter intuitive. Generator comes into rescue in such situations.
Python generators are a simple way of creating iterators. All the overhead we mentioned
above are automatically handled by generators in Python.
Simply speaking, a generator is a function that returns an object (iterator) which we can
iterate over (one value at a time).
How to create a generator in Python?
It is fairly simple to create a generator in Python. It is as easy as defining a normal function
with yield statement instead of a return statement.
If a function contains at least one yield statement (it may contain other yield or return
statements), it becomes a generator function. Both yield and return will return some value
from a function.
The difference is that, while a return statement terminates a function entirely, yield statement
pauses the function saving all its states and later continues from there on successive calls.
9. File Management

28. he term file management in the context of computers refers to the manipulation of data in a
file or files and documents on a computer. Though everybody has an understanding of the
term file, we present a formal definition anyway:
A file or a computer file is a chunk of logically related data or information which can be used
by computer programs. Usually a file is kept on a permanent storage media, e.g. a hard drive
disk. A unique name and path is used by human users or in programs or scripts to access a
file for reading and modification purposes.
The term "file" - as we have described it in the previous paragraph - appeared in the history
of computers very early. Usage can be tracked down to the year 1952, when punch cards
where used.
A programming language without the capability to store and retrieve previously stored
information would be hardly useful.
The most basic tasks involved in file manipulation are reading data from files and writing or
appending data to files.
10. Classes and Functions
What are classes and objects in Python?
Python is an object oriented programming language. Unlike procedure oriented
programming, where the main emphasis is on functions, object oriented programming stress
on objects.
Object is simply a collection of data (variables) and methods (functions) that act on those
data. And, class is a blueprint for the object.
We can think of class as a sketch (prototype) of a house. It contains all the details about the
floors, doors, windows etc. Based on these descriptions we build the house. House is the
object.
As, many houses can be made from a description, we can create many objects from a class.
An object is also called an instance of a class and the process of creating this object is called
instantiation.
Class Objects
Class objects support two kinds of operations: attribute references and instantiation.
Attribute references use the standard syntax used for all attribute references in Python:
obj.name. Valid attribute names are all the names that were in the class’s namespace when
the class object was created. So, if the class definition looked like this:
class MyClass:
"""A simple example class"""
i = 12345

29. def f(self):
return 'hello world'
then MyClass.i and MyClass.f are valid attribute references, returning an integer and a
function object, respectively. Class attributes can also be assigned to, so you can change the
value of MyClass.i by assignment. __doc__ is also a valid attribute, returning the docstring
belonging to the class: "A simple example class".
Class instantiation uses function notation. Just pretend that the class object is a parameterless
function that returns a new instance of the class. For example (assuming the above class):
x = MyClass()
creates a new instance of the class and assigns this object to the local variable x.
The instantiation operation (“calling” a class object) creates an empty object. Many classes
like to create objects with instances customized to a specific initial state. Therefore a class
may define a special method named __init__(), like this:
def __init__(self):
self.data = []
When a class defines an __init__() method, class instantiation automatically invokes
__init__() for the newly-created class instance. So in this example, a new, initialized instance
can be obtained by:
x = MyClass()
Of course, the __init__() method may have arguments for greater flexibility. In that case,
arguments given to the class instantiation operator are passed on to __init__(). For example,
>>>
>>> class Complex:
... def __init__(self, realpart, imagpart):
... self.r = realpart
... self.i = imagpart
...
>>> x = Complex(3.0, -4.5)
>>> x.r, x.i
(3.0, -4.5)
Function
You can define functions to provide the required functionality. Here are simple rules to
define a function in Python.
 Function blocks begin with the keyword def followed by the function name and
parentheses ( ( ) ).
 Any input parameters or arguments should be placed within these parentheses. You
can also define parameters inside these parentheses.

30.  The first statement of a function can be an optional statement - the documentation
string of the function or docstring.
 The code block within every function starts with a colon (:) and is indented.
 The statement return [expression] exits a function, optionally passing back an
expression to the caller. A return statement with no arguments is the same as return
None.
Syntax
def functionname( parameters ):
"function_docstring"
function_suite
return [expression]
By default, parameters have a positional behavior and you need to inform them in the same
order that they were defined.
Example
The following function takes a string as input parameter and prints it on standard screen.
def printme( str ):
"This prints a passed string into this function"
print str
return
Recommended links :
1. where-can-I-learn-Python-easily
2. Python-programming-language
3. Python an easy language to learn
4. Programming with Python: Hands-On Introduction for Beginners
5. Python Language Introduction
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