Functions and Built-in Functions in Python

Function

A function is the simplest callable object in Python.

NOTE: For Indentation either use TAB space or 4 space characters, never both.

def tax(bill):
“””Adds 25% tax to a restaurant bill.”””
bill *= 1.25
print “With tax: %f” % bill
return bill

def tip(bill):
“””Adds 35% tip to a restaurant bill.”””
bill *= 1.35
print “With tip: %f” % bill
return bill

meal_cost = 100
meal_with_tax = tax(meal_cost)
meal_with_tip = tip(meal_with_tax)

Function Syntax

def spam():                                             /*Header*/
“”” This is spam function”””            /* Comment*/
print “Spaceship!”                            /*body*/

spam()

Call and Response

def square(n):
“””Returns the square of a number.”””
squared = n**2
print “%d squared is %d.” % (n, squared)
return squared

square(5)

Parameters and Arguments

A function can require as many parameters as you’d like, but when called the function, it should generally pass in a matching number of arguments.

def power(base, exponent):  # Add your parameters here!
result = base**exponent
print “%d to the power of %d is %d.” % (base, exponent, result)

power(20, 6)  # Add your arguments here!

Functions Calling Functions

A function can call another function.

def n_plus_one(n):
return n + 1

def couple_add(n):
return n_plus_one(n) + 2

Importing Module

A module is a file that contains definitions, including variables and functions, that we can use once it is imported.

import math
print math.sqrt(25)

math includes a number of useful variables and functions, and sqrt() is one of those functions. In order to access math, all you need is the import keyword. When you simply import a module this way, it’s called a generic import.

It’s possible to import only specific variables or functions from a given module. Pulling in just a single function from a module is called a function import.

# Import *just* the sqrt function from math

from math import sqrt

if we want all the variables and functions in a module but don’t want to have to constantly type math then we can use

# Import *everything* from the math module

from math import *

Built-in Functions

max()

The max() function takes any number of arguments and returns the largest one.

>> maximum = max(10,35,64)
>> print maximum

min()

min() function returns the smallest of a given series of arguments.

>> minimum = (10,35,64)
>> print minimum

abs()

The abs() function returns the absolute value of the number it takes as an argument, it gives the number’s distance from 0 on an imagined number line.
>> absolute = abs(-42)
>> print absolute

type()

The type() function returns the type of the data it receives as an argument.

>> print type(42)
>> print type(4.2)
>> print type(‘spam’)

Now let us see the code which returns biggest, smallest and absolute values.

def biggest_number(*args):
print max(args)
return max(args)

def smallest_number(*args):
print min(args)
return min(args)

def distance_from_zero(arg):
print abs(arg)
return abs(arg)

biggest_number(-105, -53, 51, 100)
smallest_number(-106, -55, 54, 105)
distance_from_zero(-104)

These are some of the functions and built-in functions in python.

Google Analytics for Jan-Feb-March 2018(Q4 )

The statistics for MOHANMA.COM for Jan-Feb-March(starting Jan 26th to 31st March) are as shown above.

There have been a total of 737 sessions with 1673 pageviews.

The Bounce Rate of the website is 66.76%, which is pretty good as lower the bounce rate better the performance of website.

New visitors account for 76.5% of total visitors and returning visitors account for 23.5%.

India accounts for the highest traffic, with Karnataka being the leading region to in-flowing traffic with 576 sessions so far.

Among devices, mobile phones lead the traffic generated followed by desktop and lastly by tablets.

Apple iphones are the leading mobile phones used to access the website followed by Xiaomi and Motorola phones.

Thanks to everyone who have been visiting the website.

Love,

Mohan M A

Basics of Python – Part 2

Start with Basics of Python – Part 1

Dot Notation

Using dot notation with strings.
Let us consider an example where we convert the string to upper case using dot notation.

>>> mysore = “The city is awesome !”

>>> print len(mysore)
>>> print mysore.upper()

Printing strings

>>> print(“This String”)

Printing Variables

>>> Stone_cold = “Stunner”
>>> print(Stone_cold)

Concatenation

Combining strings together is called concatenation . The + operator combine the strings.

>>> print “Indian “+ “Air ” +”Force ”

The space after the word is to make the string look like sentence.

String Conversion

The str() method converts non-strings into strings.

>>> print “Sourav Ganguly scored “+ str(100) + “on his Test Debut”

String Formatting

The % operator after a string combines a string with variables. The % operator will replace  %s in the string with the string variable.

Example 1:
>>> string_1 = “Sourav”
>>> string_2 = “Dada”

>>> print “Indian captain %s is also called as %s.” % (string_1, string_2)

Example 2:

>>> batsman = raw_input(“Who is the batsman?”)
>>> captain = raw_input(“Who is the captain?”)
>>> series = raw_input(“Which series did he win for India?”)

>>> print “The Indian %s and %s Sourav Ganguly won %s series for India.” % (batsman, captain, series)

Date and Time 

We can import datetime function from datetime module.

>>> from datetime import datetime

Current Date and Time

Here is the code to print current date and time.

>>> from datetime import datetime
>>> now = datetime.now()
>>> print datetime.now()

Control Flow

The ability to choose from different situations based on what’s happening in the program.

>>> x = int(input(“Please enter an integer: “))

Please enter an integer: 35

>>> if x < 0:

…     x = 0

…     print(‘Negative changed to zero’)

… elif x == 0:

…     print(‘Zero’)

… elif x == 1:

…     print(‘Single’)

… else:

…     print(‘More’)

if statements, for statements, range fuction, break and continue, else clause loops, pass statements are few of the control flow statements.

Comparators

Equal to (==)
Not equal to (!=)
Less than (<)
Less than or equal to (<=)
Greater than (>)
Greater than or equal to (>=)

Boolean Operators

AND 

OR 

NOT

Conditional Syntax

The statements used for decision making are called conditional statements.

if condition_1:

statement_block_1

elif condition_2:

statement_block_2

else:

statement_block_3

This post concludes basics of python.

Basics of Python – Part 1

Download the python interpreter from this link . Choose either 3.0 or 2.0 version depending upon your compatibility. In this exercise version 2.0 was used for examples. Based on the current and future trends I would recommend 3.0.

Now let us look into some basic concepts in python programming language.

Variables:

As with most programming languages, assigning a value for a variable is as simple as:
a = 10

Booleans:

The two switch states True or False can be assigned to a variable.
a = True
(or)
a = False

Reassigning variable values:

A variable b = 10 can be given a value as b = 5 in the next line, and the value can be printed using
print b

Indentation:

Indentation is one of the most important aspect of python, either use a Tab space or 4 white spaces but not both. Here’s an example of a simple python function.

def example()
var = 15
return var
print example()

Single-line Comment:

Use # at the beginning of a line to give a single line comment.
# This is a single line comment in python.

Multi-line Comments:

If the comment is more than one line use double inverted comma’s thrice at the start and end of the comment.
“”” This is a multi-line
comment”””

Basic Math Operations:

All basic math operations such as addition(+), subtraction(-), multiplication(*) and division(%) can be performed similar to other programming languages.
>>print 36 + 64
100
>>print 200 – 100
100
>>print 10 * 10
100
>>print 1000 / 10
100

Exponentiation:

In python, the function of exponential can be performed using ** keys.
>> chairs = 10 ** 2
>> print chairs
100

Modulo:

Modulo operation can be performed using %.

Strings:

Assigning strings values and printing them.
python = “Hello world!”
print(“python”)

Escaping characters:

In python both single quotes and double quotes can be used for commenting. When using single quote, the interpreter doesn’t understands the code. In such cases we can use escape characters such as backslash(\).
‘Isn\’t it the python?’

Accessing by Index:

We can access any character of a string by indexing. Indexing starts from 0.
>>sixth_letter = “python”[5]
>>print sixth_letter
n

String methods:

We can calculate length of the string using len()
>>python = “Indian”
>>len(python)
>>print len(python)
6

We can convert lower case string to upper case string
>>python = “indian”
>>”indian”.upper()
>>print python.upper()
INDIAN

We can convert upper case string to lower case string
>>python = “INDIAN”
>>”INDIAN”.lower()
>>print python.lower()
indian

We can convert a variable to a string
>>pi = 3.14
>>print str(pi)
3.14

So, this concludes basics of python part-1.

Understanding Apache Spark

In my last blog post I had discussed about data, now let us understand a modern tool to process huge datasets(BigData) so as to extract insights from data.

Apache Spark – A fast and general engine for large-scale data processing. Spark is a more sophisticated version of data processing engine compared to engines using MapReduce model.

One of the key feature with Apache Spark is Resilient distributed datasets(RDD’s). These are data structures available in Spark.

Spark can run on Hadoop YARN cluster. The biggest advantage to keep large datasets in memory adds to the capability of Spark over MapReduce.

Applications types that find Spark’s processing model helpful are:

  1. Iterative algorithms
  2. Interactive analysis

Other areas which make Spark more adoptable are:

Spark DAG(Directed Acyclic Graph) – This component of the engine helps to convert variable number of operations into a single job.

User Experience – Spark makes user experience smooth by having a plethora of API’s to perform data processing tasks.

Spark has API’s in these languages: Scala, Java, Python and R.

Spark programming comprising of the Spark shell(also known as Spark CLI or Spark REPL) makes it simple to work on datasets. REPL stands for read-eval-print loop.

Spark on the other hand provides modules for:

  1. Machine learning(MLib) – Provides a framework for distributed machine learning.
  2. Graph processing(Graphx) – Provides a framework for distributed graph processing.
  3. Stream processing(Spark Streaming) – Helpful for streaming(real-time) analytics. Data ingestion takes place in mini-batches and RDD transformations are performed upon these mini-batches.
  4. SQL(Spark SQL) – Provides data abstraction known as SchemaRDD which supports structured and semi-structured data.

These components operate on Spark core. Spark core provides platform for in memory computing and referencing datasets in external storage systems.

Companies that are using Apache Spark – Google, Facebook, Twitter, Amazon, Oracle, et al.

Spark services are provided on notable cloud platforms such as Google Cloud Platform(GCP), Amazon Web Services(AWS) and Microsoft Azure.

Source: Apache Spark

 

Data: The new “OIL” of Information Era

Dataoil

Anything and everything that can be produced, which we can quantify is referred as data. In simple words granular information is data. Automobiles and machinery have been running on oil extracted from earth. In the Internet age devices, machines and all mundane activities shall be driven by data.

All data that exists can be classified into three forms:

  1. Structured Data
  2. Semi-structured Data
  3. Unstructured Data

Structured Data – Structured data is a standardized format for providing information. Examples: Sensor data, machine generated data, etc.

Semi-structured Data – Semi structured Data does not exist in standard form but can be used to derive structured form with little effort. Examples: JSON, XML, etc.

Unstructured Data – Unstructured Data is any data that is not organized but may contain data which can be extracted. Examples: Social media data, Human languages, etc.

Most global tech giants operate from data generated by their users. Google, Amazon, Facebook, Uber, et al. come under the same umbrella. The insights derived from structured and semi structured data can help us in decision making. The magnitude and scale at which these companies generate data is astounding.

Databases play a very important role in storing data. But traditional databases are no longer a choice to store data in today’s fast moving world. New age file systems and infrastructure have started operating to cater the demands of ever expanding Internet space.

In the human world, the voice, speech, text, walking speed, everything can be classified as unstructured data, since we can derive a lot of insights from them. A mobile device per individual is pretty much sufficient to analyse the behavior of a sizable population in a region.

Data collected from a population for a relatively considerable time can be used to derive patterns about the population. Hence, data is the driving force which will fuel innovation and economy from here.

Bengaluru and the spirit of Entrepreneurship

Here is a list of reasons for Bengaluru being a favorite location to start-up:

1 – Technology Infrastructure :- High end systems, high speed internet, ask for anything new in the field of technology, it’s usually first implemented in Bengaluru. That gets Bengaluru a premium tag.

2 – Workforce & Talent :- A plethora of highly qualified professionals makes it a easy choice for most of the entrepreneur’s to choose Bengaluru to kick-start their venture. Engineer’s and Business professionals are a new class of the neatly woven fabric in Bengaluru.

3 – Geographic location :- Weather in Bengaluru is usually pleasant with room temperature hovering between 23°C to 27°C throughout the year with summer being an exception. Bengaluru is the king among metropolitan cities of India, when it comes to weather.

4 – Koramangala :- The Heart of Entrepreneurship for the whole nation is located at koramangala. Visit any street in this locality of Bengaluru and you shall encounter a new venture or business being built. Koramangala is a place that every entrepreneur must visit at-least once in their lifetime.

5 – Government support :- The Karnataka Government has been one of the most proactive government in the country as far as Entrepreneurship is considered. Some of the highly successful Information Technology & Bio-technology ventures started off from Bengaluru by the initial support offered by Karnataka Government. ITPL and many SEZ’s in the city are examples for it.

6 – Cosmopolitan Nature :- This is the ultimate reason for Entrepreneurship to be cherished in Bengaluru. People from different parts of the country live and work in Bengaluru, surely Bengaluru is a “Melting pot”.

7 – Cost of living :- Of late the costs have been going up in Bengaluru considering inflation and other factors. But it’s still affordable for middle class to survive. Cost of living is comparatively cheaper than Delhi and Mumbai.

8 – Education :- The city hosts a series of exceptional institutions, IISc and IIM being the cream. Even at secondary and higher secondary level there are many noteworthy institutions.

9 – Law and Order :- Law & order is usually stable with few huff and puff at times. Law & order is one more reason to choose Bengaluru as a business location.

10 – Healthcare :- Many healthcare bodies are spread-out through the city, there are specialized units in the city where foreigner’s are addressed too. Healthcare facilities are cheaper in Bengaluru compared to International standards.

Bengaluru is the first Indian city to have it’s own logo.

BE”ngalur“U”, BE and U in Bengaluru stands for “Be You”.

Google Analytics for MOHANMA.COM : Launch(26th Jan) to 2nd March

Firstly, thanks to everyone who have visited mohanma.com. The above image shows the global footprint of mohanma.com.

The total number of sessions so far has been 563. India leads in web traffic with 493 sessions. Followed by United States of America, Australia and United Kingdom. Traffic has been flowing in from different parts of Europe, Canada, Peru, China, Japan, etc as well.

To be frank, I have been surprised with the kind of response that mohanma.com has been receiving from day 1. Thanks to all the readers, well-wishers who have been pouring in their feedback via WhatsApp, Facebook and the comments section on website.

Love,

Mohan M A

Difference between Process and Thread in Java

 

ProcessThread
1) Part of Concurrent Programming.1) Integral part of Concurrent Programming.
2) A process has a self-contained execution environment. 2) A thread is a lightweight process.
3) Process has its own memory space.3) Threads share the process's resources, including memory and open files.
4) Processes are synonymous with programs or applications.4) Threads do things such as memory management and signal handling.
5) A Java application can create additional processes using a ProcessBuilder object.5) A Main thread has the ability to create additional threads.
6) To facilitate communication between processes, most operating systems support Inter Process Communication (IPC) resources, such as pipes and sockets.6) Threads exist within a process. This makes for efficient, but potentially problematic, communication.

Processing time for a single core is shared among processes and threads through an OS feature called time slicing.

Time Slice or Preemption : A technique to implement multitasking in operating systems. The period of time for which a process is allowed to run in a preemptive multitasking system is generally called the time slice or quantum. The scheduler is run once every time slice to choose the next process to run.

Source: 1) The Java™ Tutorials
        2) Wikipedia

Object-Oriented Programming (OOP)

OOP is based on “objects“. An object can perform a set of functions. The functions that the object performs defines the object’s behavior.

For example, the Batsman(object) can play shots or a Bowler(object) can Bowl.

Languages that support object-oriented programming have four important aspects:

1. Abstraction
2. Encapsulation
3. Inheritance
4. Polymorphism

Abstraction involves the process to define objects that represent abstract actions which can perform work,
report on and change their state, and interact with other objects in the system.

Encapsulation is the process of enclosing data and functions into a single element.

Inheritance is when an object or class is based on another object,
using parent objects properties to maintain the same behavior in the child object.

Polymorphism is the method of having a single interface to objects of different types.

Object-oriented programming (OOP) is a programming paradigm

Objects — > data — > fields — > attributes — > methods(code)

Some of the popular languages that support Object-Oriented Programming

Java, Python, C++, C#, Perl, Ruby , Objective-C, PHP, et al.