Showing posts with label pythononlinetraining. Show all posts
Showing posts with label pythononlinetraining. Show all posts

Wednesday, 15 March 2017

Interesting Things About Python


Introduction to Python
Python is one of the scripting language programs and which supports many open source language. 90% of peoples are using python for web development because it is easy and reliable to use. As a result of many open source techniques python helps to build application at faster and efficient manner
Uses of python
Python is widely used to develop various applications and it can support various OS like windows, UNIX, Linux… Many companies like Google, Yahoo, and Bing are using python
Feature of python
  • The main feature of python is that the codes are being written in c, c++ and it has readable syntax.
  • It has dynamic syntax.
  • Sound introspection capabilities.
  • Python also supports various integration techniques.
  • Python is an user friendly application.
  • It has less code than java.

Friday, 10 March 2017

Brief Overview Of Python


Introduction

Welcome! Are you completely new to programming? If not then we presume that you will be looking for information about why and how to get started with python. Fortunately you are a fresher or experienced programmer in any programming language would pick up Python very quickly. It’s easy for beginners use and learn, so jump in! Join Python Training in Chennai at Besant Technologies to Learn from here and finally remove ‘L’ from it!

About Python

Python is the world’s most popular and versatile programming language has advanced data structure and effective object oriented programming concept that has been used in large companies such as Google, Yahoo, CERN and also in NASA. Python provides constructs which intended to enable clear programs on both small as well as large scale.

Monday, 6 March 2017

12 Reasons to Learn Python Programming


You will grasp that easily
It is always a difficult task to learn a new language, but this is not with Python. Python is designed to be easily grasped by a novice programmer. The python codes are easily readable by the developer who has little bit knowledge about codes. The standard library opens a lot of functionalities which will help you execute complex functionalities without any problem.
You will get many opportunities
Yes, you will be able to peek out through the window of programming through python. Python has a different object oriented approach which is preferred by a lot of the leading languages like Ruby, JavaScript, C#, etc.
First choice for Web Development
Python has an array of frameworks which provides a lot of flexibility in case of web development with python. There are many web frameworks offered by python like TurboGears, Pylons, Zope2, etc.


Wednesday, 1 March 2017

Goals and Architecture Overview of Python


The main is to provide a compliant, flexible and fast implementation of the Python Language which uses the RPython tool chain to enable new advanced high-level features without having to encode the low-level details. This is called as PyPy.

High Level Goals
Our main motivation to develop the translation framework that provides a full featured, customizable, fast and very compliant Python implementation, working on and interacting with a large variety of platforms and allowing the quick introduction of new advanced language features.
This Python implementation is written in RPython as a relatively simple interpreter, in some respects, it is easier to understand than CPython, that is C reference implementation of Python. Using its high level flexibility to quickly experiment the features or implementation techniques in a traditional approach, require pervasive changes to the source code.
For example, PyPy’s Python interpreter provides a lazily computed object which is a small extension that would require global changes in CPython.
Another example is the garbage collection technique: changing CPython to use a garbage collector not based on reference counting, whereas in PyPy it’s an issue localized in the translation framework which is fully orthogonal to the interpreter source code.
PyPy Python Interpreter
PyPy’s Python Interpreter is written in RPython that implements the full Python language. This interpreter very closely emulates the behavior of CPython and contains the following key components:
Bytecode Compiler - This is responsible for producing the Python code objects from the source code of a user application. The bytecode compiler is the preprocessing phase which produces a compact bytecode format via a chain of flexible passes (tokenizer, lexer, parser, abstract syntax tree builder, bytecode generator).
Bytecode Evaluator – It’s responsible for interpreting the Python code objects. The bytecode evaluator interprets this bytecode. It does most of its work by delegating all actual manipulations of user objects to the object space. The latter can be thought of as the library of built-in types. It defines the implementation of the user objects, like integers and lists, as well as the operations between them, like addition or truth-value-testing.
Standard Object Space – This is responsible for creating and manipulating the Python objects that are seen by the application. The division between bytecode evaluator and object space gives a lot of flexibility. One can plug in different object spaces to get different or enriched behaviour of the Python object.

If You Have any Queries?. Mention it in the Comment Section, We will Clarify You Soon..!

Tuesday, 28 February 2017

Top Interview Questions and Answers for Python


1) What is Python?
Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable which uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.
2) Mention five benefits of using Python?
·          Python comprises of a huge standard library for most Internet platforms like Email, HTML, etc.
·          Python does not require explicit memory management as the interpreter itself allocates the memory to new variables and free them automatically
·          Provide easy readability due to use of square brackets
·          Easy-to-learn for beginners
·          Having the built-in data types saves programming time and effort from declaring variables

3) What is pickling and unpickling?
Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function is called pickling.  While the process of retrieving original Python objects from the stored string representation is called unpickling.

Monday, 27 February 2017

Applications of Python



3D CAD/CAM

FreeCAD is an Open Source CAx RAD based on Open Cascade, Qt and Python. It features some key concepts like Macro recording, Workbenches, ability to run as a server and dynamically loadable Application extensions and its designed to be platform independent.
Fandango is planned to be a full featured CAD program and has C++ core extensible by scripts. Currently the memory core for entity management is ready, scripting works wonderfully thanks to the ease of embedding and extending of Python. A KDE+XML user interface is now in place, controlling the keyboard and mouse.
Vintech RCAM is a CAD/CAM system for true shape nesting and NC programming of laser, plasma, oxy-fuel and water-jet cutting machines. Vintech RCAM is platform independent and now it runs under Windows XP, Windows 7 and Linux. The main programing language of the system is Python, which defines the advanced methodology and the dynamic system development.

Audio/Video Applications

cplay - Curses-based Linux multimedia jukebox
Freeseer - Conference recording software and screencast tool
Freevo - Linux multimedia jukebox
TimPlayer - Py-GTK based music player using GStreamer

Click Here To Obtain Source…

Thursday, 23 February 2017

Exceptions in Python


What is an Exception?
An Exception is an event or error that would happen during the execution of a program that would disturbs their execution. Whenever there is an error, Python generates an exception that could be handled. It basically prevents the program from getting crashed. When a Python script raises an exception, it must either handle the exception immediately otherwise it terminates and quits.
Why we use Exceptions
There was a valid as well as invalid exceptions occurred many times. Exceptions are convenient in many ways for handling errors and also the special conditions in a program. If we have some set of code which produces error, at that time we can use exception handling technique.

Handling an exception


If you have some suspicious code that may raise an exception, you can defend your program by placing the suspicious code in a try: block. After the try: block, include a except: statement, followed by a block of code that handles the problem as elegantly as possible.
If you have any queries? Mention it in the comment section, we will clarify you soon…!

Wednesday, 22 February 2017

Introduction to Python for Big data Analytics


Hi everyone, if you are a fresher or experienced having lot of queries for learning which programming language. Don’t worry… we are providing a Webinar on Python for Big data Analytics. The title of the webinar is . We will be discussing the essential topics in detail and any queries can be rectified during the session.
Topics to be covered:
1. Introduction to Python
2. Python and Big Data
3. Python and Data Science
4. Key features of Python and their usage in Business Analytics
5. Business Analytics with Python – Real world Use Cases
Why Python?
Python is an interpreted, interactive, high level programming language similar to PERL with ease of accessibility, readability and having a simple syntax. Python is a preferred choice among professionals looking into Big Data Analytics and its feature of being a general-purpose, high level programming with a gradual learning curve makes it popular as compared to other programming languages.
Nowadays, most organizations would shift their emphasis to Big Data Analytics with an expected investment of over $50 billion. A simple and scalable tool is needed to analyze the big data, which has been answered by Python. In the today’s situation some of the most top organizations from search engine giants, like Google to NASA that are using Python for different purposes.
For more information also check out our on ‘Big Data Processing with Apache Storm’. Click Here to know more!   
If you have any queries?..Mention it in the comment section, we will clarify you!



Tuesday, 21 February 2017

Brief Overview of Python

Introduction

Welcome! Are you completely new to programming? If not then we presume that you will be looking for information about why and how to get started with python. Fortunately you are a fresher or experienced programmer in any programming language would pick up Python very quickly. It’s easy for beginners use and learn, so jump in! Join Python Training in Chennai at Besant Technologies to Learn from here and finally remove ‘L’ from it!

Tuesday, 14 February 2017

Why Learn Python?


Python is the great language for beginners which are easy to learn and maintain. To start programming in python, it’s easy to complete a program within two days. By using other languages it is extremely vast because in that go into its packages, like its machine learning packages, SciPy packages, Matplotlib and so on. So, it might take more time to complete.
  • Python’s biggest strength is that its bulk of library is portable.
  • There are millions of people around the world are working on Python and making contributions to its development.
  • It’s an open-source language. If you have Python in your system means write your own piece of package and then submit it for approval.
  • There are hundreds and thousands of packages available that are portable and helps in programming to clarify some of the stuff.
PyCharm
It is a GUI-based development environment having the Python packages connected to Python. For example, everyone has Twitter and Facebook accounts. How do analyze date from Twitter and Facebook? PyCharm package is used to
  • pull streaming data from Twitter or Facebook,
  • save it and conduct a search in it,
  • do a sentiment analysis, or
  • Run some kind of machine learning algorithm on it.
Many people worked hard in order to create these packages. Accordingly, all you have to do is read a little bit of documentation about this package and start implementing, instead of writing thousands of lines of code. Even in Python, you may end up it by writing 50-60 lines of code.
Machine Learning
Machine learning algorithms are mostly used to create artificial intelligence in machines which are also available in SciKit Learn. It has been optimized in a way that the machine learning code would write in just 4-5 lines. Use this package, invoke those procedures and functions, pass the data, fit your model and then predict the outcome which is very easy. Python has made lot of things easier and it is still being contributed by thousands of developers across the world. It’s going to get much better and that is why it’s becoming popular.
Data Analytics
With libraries like PyDoop and SciPy, it’s a dream come true for Big Data Analytics. Nowadays, there are tons of data flowing from everywhere, those would be analyzed first. In some organizations, they have the data from the past 70 years, while in others they have data from past 30-40 years and it’s too huge. They would store this data in some database somewhere, and it might be lost. Let’s take data of 1970s; but who cares about the 1970s data in this age? However, to find a trend, those data’s are important in a way. It’s not just important, it’s necessary to find a trend.
For example, I am in a computer manufacturing company and I want to find a trend as to what’s happening. You might have heard about forecasting and how people do that. Basically, they capture the data of the past 2-3 years. Let’s say, last year in March, the sales were 1 million, in April the number was 2 million, in May 3 million, and so on and so forth. They would just take this data and then extrapolate it to this year. Then, they assume that since last year in August, it was 1 million, this year too in August, it might be 1 million. That’s how they extrapolate it. So just look at the amount of data taken. May be in a couple of years when they average out the data of those years, they may do a moving average or use some kind of statistical algorithm but with a limited amount of data.
With the advent of Hadoop and Big Data, Data Processing has changed. Nowadays, we can process the data for 30 years and find a pattern, which might be anything. It should be sin wave or cosine wave to some graph, which is not any kind of wave, but just a zigzag graph which tell the pattern. In order to implement those algorithms with so much of data with the help of libraries like, PyDoop and SciPy.
Growing Interest in Python
Last 30 years the python has been there, but the growth of interest started in July, 2010. The name python is originated from the play in London (UK) doesn’t derive from the animal python (snake). In July 2010 the interest of Python started growing well to today itself. Most of the organizations, particularly the one dealing with data and Data Analytics asking the experienced and also having knowledgeable person in python.


If you have any queries? Mention it in the comment section, we will clarify you!

Friday, 10 February 2017

Range Functions and Sequences in Python


Range() generates lists containing arithmetic progression.
Three variations of range() function
>> range(stop) – Starts from 0 till (stop – 1)
>> range(start,stop) – Ends at (stop – 1)
>> range(start,stop,step) – Step cannot be 0, default is 1
Example of Range Function
range(stop) - If the range is defined as 5, it would simply show the list of numbers falling in the range from 0 to 5. The default range starts from 0 and stops before 5, as defined.
range(start, stop) – The point of starting as well as stopping is defined in this. As shown in the example below, the start range has been defined as 5, while stop range as 10. Hence, it would display the numbers 5, 6, 7, 8, 9, which range between 5 to 10.
range(start, stop, step) - The first two values defined here are the same, start and stop, while the third one is step, which means the difference between every two consecutive numbers. For example, if range is defined in this way: range(0, 10, 2). It will give away numbers between 0 to 10, but with a difference of 2, in this way: [0, 2, 4, 6, 8]. The step here cannot be given 0 value. It has to be 1 or greater than 1.
Sequences in Python
A sequence is the succession of values bound together by a container that reflects their type. Almost every stream that we put in Python is a sequence.
Types of Sequences
  • Lists
  • Tuples
  • Xrange
  • String
The python is supported by some other sequences are strings, lists, tuples and Xrange objects. Python has a bevy of methods and formatting operations that can perform.
List
  • A list is a sort of container which holds the number of other objects, in a given order.
  • The list type implements the sequence protocol which allows adding and removing objects from the sequence.
  • It is an ordered set of elements enclosed in square brackets.
Simple definition of list – li = []
li = list() # empty list
li = list(sequence)
li = list(expression for variable in sequence)
example
            >>> list(a)
            [‘e’, ‘x’, ‘a’, ‘m’, ‘p’, ‘l’, ‘e’]
            >>> list3 = [‘Hadoop’, ‘Python’, ‘Data Science’, ‘Pig’, ‘hive’]
            >>> list3
            [‘Hadoop’, ‘Python’, ‘Data Science’, ‘Pig’, ‘hive’]
            >>> list3[2:]
            [‘Data Science’, ‘Pig’, ‘hive’]
            >>> list3[2:3]
            [‘Data Science’]
            >>> list3[2:4]
            [‘Data Science’, ‘Pig’]
            >>> list3[2:5]
            [‘Data Science’, ‘Pig’, ‘hive’]
            >>>
Accessing List Elements
To access the elements of a list:
n = len(li)
item = li[index] #Indexing
slice = li[start:stop] #Slicing
List Indexing

list[i] returns the value at index i, where i is an integer. A negative index accesses elements from the end of the list counting backwards. The last element of any non-empty list is always li[-1]. Python raises an IndexError exception, if the index is outside the list.

Accessing Command Line Arguments

Python supports the creation of programs that would run on the command line, completely with command-line arguments. It provides getopt modules that parse the command line options and arguments. The Python sys module provides access to any of the command-line arguments via sys.argv. It solves two purposes:
  • sys.argv is the list of command line arguments
  • len(sys.argv) is the number of command line arguments that are in the command line
  • sys.argv[0] is the program, i.e. script name

Executing Python

The python should be executed in the following
$python Commands.py inp1, inp2 inp3

Example

import sys
print ‘Number of arguments:’, len (sys.argv), ‘arguments.’
print ‘Argument List:’, str(sys.argv)
It will produce the following output:
Number of arguments: 4 arguments.
Argument List: [‘sample.py’, ‘inp1’, ‘inp2’, ‘inp3’]
If you have any queries? Mention them in the comments section and we will clarify you.

Wednesday, 8 February 2017

Introduction to strings in python


In Python, the strings should be created by simply enclosing the characters in quotes. Python does not support the character types. These are treated as length-one strings, and are also considered as substrings. Substrings are immutable and can’t be changed once created.
Strings are the ordered blocks of text that are enclosed in single or double quotations. Thus, whatever is written in quotes, is considered as string. Though it can be written in single or double quotations, double quotation marks allow the user to extend strings over multiple lines without backslashes, which is usually the signal of continuation of an expression, e.g., ‘abc’, “ABC”.

Concatenation and Repetition

  • Strings are concatenated with the +sign:
>>> ‘abc’+‘def’
‘abcdef’
  • Strings are repeated with the *sign:
>>> ‘abc’*3
‘abcabcabc’

Indexing and Slicing Operation

  • Python starts the indexing at ‘0’
  • A string s will have indexes running from 0 to len(s)-1 (where len(s) is the length of s) in integer quantities.
  • S[i] fetches the ‘i’th element in the s.

Built-in String Methods

Following are the built-in String Methods that can be used in Python:
  • capitalize() – This method is used to capitalize the first letter of string.
  • count(str, beg= 0, end=len(string)) – Used to count how many times  the str occurs in string or in a substring of string, if beginning index ‘beg’ and ending index ‘end’ are given.
  • encode(encoding=‘UTF-8’,errors=‘strict’) – This method is used to return the encoded string version of string; on error, default raises a ValueError, unless the error is given with ‘ignore’ or ‘replace’.
  • decode (encoding=‘UTF-8’, errors=‘strict’) – This method is used to decode the string using the codec registered for Encoding. Encoding defaults to the default string function.
  • index(str, beg=0, end=len(string))- Same as find(), but it raises an exception if str is not found.
  • max(str)- Used to return the max alphabetical character from the string str.
  • min(str)- This is used to return the min alphabetical character from the string str.
  • replace(old, new [, max])- This method is used replace all the occurrences of ‘old’ in string with ‘new’ or maximum occurrences if max is given.
  • upper()- This method is used to convert the lowercase letters in a string to uppercase.

If you have any queries? Mention them in the comments section and we will clarify you.