Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands.

Python is derived from many other languages, including ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell and other scripting languages.

Python is copyrighted. Like Perl, Python source code is now available under the GNU General Public License (GPL).

Python is now maintained by a core development team at the institute, although Guido van Rossum still holds a vital role in directing its progress.

On December 3, 2008, Python 3.0 (also called "Py3K") was released. It was designed to rectify the fundamental flaw of the language.

On December 3, 2008, Python 3.0 (also called "Py3K") was released. It was designed to rectify the fundamental flaw of the language.

Easy-to-learn −

Python has few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language quickly.

Easy-to-read −

Python code is more clearly defined and visible to the eyes.

Easy-to-maintain −

Python's source code is fairly easy-to-maintain.

A broad standard library −

Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.

Interactive Mode −

Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.

Portable −

Python can run on a wide variety of hardware platforms and has the same interface on all platforms.

Extendable −

You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.

Databases −

Python provides interfaces to all major commercial databases.

GUI Programming −

Python supports GUI applications that can be created and ported to many system calls, libraries, and windows systems, such as Windows MFC, Macintosh, and the X Window system of Unix.

Scalable −

Python provides a better structure and support for large programs than shell scripting.

Apart from the above-mentioned features, Python has a big list of good features, few are listed below −

 - It supports functional and structured programming methods as well as OOP.

 - It can be used as a scripting language or can be compiled to byte-code for building large applications.

 - It provides very high-level dynamic data types and supports dynamic type checking. IT supports automatic garbage collection.

 - It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.

Python is known for its general-purpose nature that makes it applicable in almost every domain of software development. Python makes its presence in every emerging field. It is the fastest-growing programming language and can develop any application.

Here, we are specifying application areas where Python can be applied.

1) Web Applications

We can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautiful soup, Feedparser, etc. One of Python web-framework named Django is used on Instagram. Python provides many useful frameworks, and these are given below:

• Django and Pyramid framework(Use for heavy applications)
• Flask and Bottle (Micro-framework)
• Plone and Django CMS (Advance Content management)

2) Desktop GUI Applications

The GUI stands for the Graphical User Interface, which provides a smooth interaction to any application. Python provides a Tk GUI library to develop a user interface. Some popular GUI libraries are given below.

• Tkinter or Tk
• wxWidgetM
• Kivy (used for writing multitouch applications )
• PyQt or Pyside

3) Console-based Application

Console-based applications run from the command-line or shell. These applications are computer program which are used commands to execute. This kind of application was more popular in the old generation of computers. Python can develop this kind of application very effectively. It is famous for having REPL, which means the Read-Eval-Print Loop that makes it the most suitable language for the command-line applications.

Python provides many free library or module which helps to build the command-line apps. The necessary IO libraries are used to read and write. It helps to parse argument and create console help text out-of-the-box. There are also advance libraries that can develop independent console apps.

4) Software Development

Python is useful for the software development process. It works as a support language and can be used to build control and management, testing, etc.

• SCons is used to build control.
• Buildbot and Apache Gumps are used for automated continuous compilation and testing.
• Round or Trac for bug tracking and project management.

5) Scientific and Numeric

This is the era of Artificial intelligence where the machine can perform the task the same as the human. Python language is the most suitable language for Artificial intelligence or machine learning. It consists of many scientific and mathematical libraries, which makes easy to solve complex calculations.

Implementing machine learning algorithms require complex mathematical calculation. Python has many libraries for scientific and numeric such as Numpy, Pandas, Scipy, Scikit-learn, etc. If you have some basic knowledge of Python, you need to import libraries on the top of the code. Few popular frameworks of machine libraries are given below.

• SciPy
• Scikit-learn
• NumPy
• Pandas
• Matplotlib

6) Business Applications

Business Applications differ from standard applications. E-commerce and ERP are an example of a business application. This kind of application requires extensively, scalability and readability, and Python provides all these features.

Oddo is an example of the all-in-one Python-based application which offers a range of business applications. Python provides a Tryton platform which is used to develop the business application.

7) Audio or Video-based Applications

Python is flexible to perform multiple tasks and can be used to create multimedia applications. Some multimedia applications which are made by using Python are TimPlayer, cplay, etc. The few multimedia libraries are given below.

• Gstreamer
• Pyglet
• QT Phonon

8) 3D CAD Applications

The CAD (Computer-aided design) is used to design engineering related architecture. It is used to develop the 3D representation of a part of a system. Python can create a 3D CAD application by using the following functionalities.

• Fandango (Popular )
• CAMVOX
• HeeksCNC
• AnyCAD
• RCAM

9) Enterprise Applications

Python can be used to create applications that can be used within an Enterprise or an Organization. Some real-time applications are OpenERP, Tryton, Picalo, etc.

10) Image Processing Application

Python contains many libraries that are used to work with the image. The image can be manipulated according to our requirements. Some libraries of image processing are given below.

• OpenCV
• Pillow
• SimpleITK

In this topic, we have described all types of applications where Python plays an essential role in the development of these applications. In the next tutorial, we will learn more concepts about Python.

How to Install Python (Environment Set-up)

In this section of the tutorial, we will discuss the installation of Python on various operating systems.

Installation on Windows

Visit the link https://www.python.org/downloads/ to download the latest release of Python. In this process, we will install Python 3.6.7 on our Windows operating system.

Double-click the executable file, which is downloaded; the following window will open. Select Customize installation and proceed.

The following window shows all the optional features. All the features need to be installed and are checked by default; we need to click next to continue.

The following window shows a list of advanced options. Check all the options which you want to install and click next. Here, we must notice that the first check-box (install for all users) must be checked.

Now, we are ready to install python-3.6.7. Let's install it.

Now, try to run python on the command prompt. Type the command python in case of python2 or python3 in case of python3. It will show an error as given in the below image. It is because we haven't set the path.

To set the path of python, we need to the right click on "my computer" and go to Properties → Advanced → Environment Variables.

Add the new path variable in the user variable section.

Type PATH as the variable name and set the path to the installation directory of the python shown in the below image.

Now, the path is set; we are ready to run python on our local system. Restart CMD, and type python again. It will open the python interpreter shell where we can execute the python statements.

Installation on Mac

To install python3 on MacOS, visit the link https://www.javatpoint.com/how-to-install-python-on-macand follow the instructions given in the tutorial.

Installation on CentOS

To install Python3 on CentOS, visit the link https://www.javatpoint.com/how-to-install-python-on-centosand follow the instructions given in the tutorial.

Installation on Ubuntu

To install Python3 on Ubuntu, visit the link https://www.javatpoint.com/how-to-install-python-in-ubuntu and follow the instructions given in the tutorial.

We assume that you have the Python interpreter set in PATHvariable. Now, try to run this program as follows −

On Linux

$  python  test.py

This produces the following result −

Hello,  Python!

On Windows

C:\Python34>Python  test.py This produces the following result − Hello,  Python!

Let us try another way to execute a Python script in Linux. Here is the modified test.py file −

print  ("Hello,  Python!")

We assume that you have Python interpreter available in the /usr/bin directory. Now, try to run this program as follows −

$  chmod  +x  test.py           #  This  is  to  make  file  executable

$./test.py

This produces the following result −

Hello,  Python!

-d          :  debug  output  from  parser  (also  PYTHONDEBUG=x)

-E          :  ignore  environment  variables  (such  as  PYTHONPATH)

-h          :  print  this  help  message  and  exit

[  etc.  ] 

 Variables are nothing but reserved memory locations to store values. It means that when you create a variable, you reserve some space in the memory.

 var1 = 1

Python Lists

Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One of the differences between them is that all the items belonging to a list can be of different data types.

The values stored in a list can be accessed using the slice operator ([ ] and [:]) with indexes starting at 0 at the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator, and the asterisk (*) is the repetition operator. For example −

A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parenthesis.

The main difference between lists and tuples are − Lists are enclosed in brackets ( [ ] ) and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only lists. For example −

list =  ['abcd', 786, 2.23, 'john', 70.2]

 dict_keys(['name',  'dept',  'code'])

dict_values(['john',  'sales',  6734])

Dictionaries have no concept of order among the elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.

Data Type Conversion

Sometimes, you may need to perform conversions between the built-in types. To convert between types, you simply use the type-names as a function.

There are several built-in functions to perform a conversion from one data type to another. These functions return a new object representing the converted value.

 Operators are the constructs, which can manipulate the value of operands. Consider the expression 4 + 5 = 9. Here, 4 and 5 are called the operands and + is called the operator.

Python Comparison Operators

These operators compare the values on either side of them and decide the relation among them. They are also called Relational operators.

Assume variable a holds the value 10 and variable b holds the value 20, then −

Show Example

Python Assignment Operators

Assume variable a holds the value 10 and variable b holds the value 20, then −

Show Example

Python Bitwise Operators

Bitwise operator works on bits and performs a bit-by-bit operation. Assume if a = 60; and b = 13; Now in a binary format they will be as follows −

a = 0011 1100

b = 0000 1101

-----------------

a&b = 0000 1100

a|b = 0011 1101

a^b = 0011 0001

~a = 1100 0011

Python's built-in function bin() can be used to obtain a binary representation of an integer number.

The following Bitwise operators are supported by Python language −

Show Example

Python Logical Operators

The following logical operators are supported by Python language. Assume variable a holds True and variable b holds False then −

Python Membership Operators

Python’s membership operators test for membership in a sequence, such as strings, lists, or tuples. There are two membership operators as explained below −

Show Example

Python Identity Operators

Identity operators compare the memory locations of two objects. There are two Identity operators as explained below −

Show Example

Python Operators Precedence

The following table lists all operators from highest precedence to the lowest.

Show Example

 Decision-making is the anticipation of conditions occurring during the execution of a program and specified actions taken according to the conditions.

Decision structures evaluate multiple expressions, which produce TRUE or FALSE as the outcome. You need to determine which action to take and which statements to execute if the outcome is TRUE or FALSE otherwise.

Following is the general form of a typical decision-making structure found in most of the programming languages −

Python programming language assumes any non-zero and non-null values as TRUE, and any zero or null values as FALSE value.

Python programming language provides the following types of decision-making statements.

Let us go through each decision-making statement quickly.

Single Statement Suites

If the suite of an if clause consists only of a single line, it may go on the same line as the header statement.

Example

Here is an example of a one-line if clause −

var = 100

if  (  var     ==  100  )  :  

    print  ("Value of  expression is 100")

    print  ("Good  bye!")

Output

When the above code is executed, it produces the following result −

Value  of  expression  is  100 Good bye!

if Statements

if condition : statement

or

if condition :

statement-1

statement-2 

....

If condition is true then statements will be executed.

Example:

if-else Statements:

if condition :

    Action-1

else :

    Action-2

if condition is true then Action-1 will be executed otherwise Action-2 will be executed.

Example:

if-elif-else Statements:

Syntax:

if condition1:

    Action-1

elif condition2:

    Action-2

elif condition3:

    Action-3

elif condition4:

    Action-4

...

else:

    Default Action

Example:

 In general, statements are executed sequentially − The first statement in a function is executed first, followed by the second, and so on. There may be a situation when you need to execute a block of code several number of times.

Programming languages provide various control structures that allow more complicated execution paths.

A loop statement allows us to execute a statement or group of statements multiple times. The following diagram illustrates a loop statement −

Python programming language provides the following types of loops to handle looping requirements.

Loop Control Statements

The Loop control statements change the execution from its normal sequence. When the execution leaves a scope, all automatic objects that were created in that scope are destroyed.

Python supports the following control statements.

Let us go through the loop control statements briefly.

for loop:

If we want to execute some action for every element present in some sequence(it may be string or collection)then we should go for for loop.

Syntax:

for x in sequence :

    body

where sequence can be string or any collection.

Body will be executed for every element present in the sequence.

Eg 1: To print characters present in the given string

Eg 2: To print characters present in string index wise:

Eg 3: To print Hello Pybron 5 times

Eg 4: To display numbers from 0 to 5

Eg 5: To display odd numbers from 0 to 15

while loop:

If we want to execute a group of statements iteratively until some condition false, then we should go for while loop.

Syntax:

while condition :

    body

Eg 1: To print numbers from 1 to 5 by using while loop

Nested Loops:

Sometimes we can take a loop inside another loop, which is also known as nested loops.

Eg: Write a program to dispaly *'s in Right angled triangled form

Eg. Write a program to display *'s in pyramid style(also known as an equivalent triangle)

Break

We can use break statement inside loops to break loop execution based on some condition.

continue:

We can use continue statement to skip current iteration and continue next iteration.

Eg 1: To print odd numbers in the range 0 to 9

Pass

In Python, the pass keyword is used to execute nothing; it means, when we don't want to execute code, the pass can be used to execute empty. It is the same as the name refers to. It just makes the control to pass by without executing any code.

Iterator

Iterator is an object which allows a programmer to traverse through all the elements of a collection, regardless of its specific implementation. In Python, an iterator object implements two methods, iter() and next().

String, List or Tuple objects can be used to create an Iterator.

list = [1,2,3,4]

it = iter(list)  #  this builds an iterator object

print (next(it))  #prints next available element in iterator

Iterator object can be traversed using regular for statement

for x in it:

    print(x, end="  ")

or using next() function 

while True:

    try:

        print(next(it))

    except StopIteration:

        sys.exit() #you have to nimport sys module for this

Generator

A generator is a function that produces or yields a sequence of values using yield method.

When a generator function is called, it returns a generator object without even beginning execution of the function. When the next() method is called for the first time, the function starts executing until it reaches the yield statement, which returns the yielded value. The yield keeps track i.e. remembers the last execution and the second next() call continues from previous value.

Example

The following example defines a generator, which generates an iterator for all the Fibonacci numbers

import sys

def fibonacci(n):  #generator  function

a, b, counter = 0, 1, 0

while True:

    if (counter > n): 

        return

    yield a

    a, b = b, a + b 

    counter += 1

f = fibonacci(5)  #f is iterator object

while True:

    try:

        print(next(f),  end="  ") 

    except StopIteration:

        sys.exit()

Number data types store numeric values. They are immutable data types. This means, changing the value of a number data type results in a newly allocated object.

Number objects are created when you assign a value to them.

For example −

var1 = 1

var2 = 10

You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −

del  var1[,var2[,var3[ ...... ,varN]]]]

You can delete a single object or multiple objects by using the del statement. For example −

del  var

del  var_a,  var_b

Python supports different numerical types −

int (signed integers) −

They are often called just integers or ints. They are positive or negative whole numbers with no decimal point. Integers in Python 3 are of unlimited size. Python 2 has two integer types - int and long. There is no 'long integer' in Python 3 anymore.

float (floating point real values) −

Also called floats, they represent real numbers and are written with a decimal point dividing the integer and the fractional parts. Floats may also be in scientific notation, with E or e indicating the power of 10 (2.5e2 = 2.5 x 102 = 250).

complex (complex numbers) −

They are of the form a + bJ, where a and b are floats and J (or j) represents the square root of -1 (which is an imaginary number). The real part of the number is a, and the imaginary part is b. Complex numbers are not used much in Python programming.

It is possible to represent an integer in hexa-decimal or octal form

>>>  number  =  0xA0F  #Hexa-decimal

>>>  number

2575

>>>  number  =  0o37  #Octal

>>>  number

31

Examples

Here are some examples of numbers.

A complex number consists of an ordered pair of real floating-point numbers denoted by a + bj, where a is the real part and b is the imaginary part of the complex number.

Number Type Conversion

Python converts numbers internally in an expression containing mixed types to a common type for evaluation. Sometimes, you need to coerce a number explicitly from one type to another to satisfy the requirements of an operator or function parameter.

Type int(x) to convert x to a plain integer.

Type long(x) to convert x to a long integer.

Type float(x) to convert x to a floating-point number.

Type complex(x) to convert x to a complex number with real part x and imaginary part zero.
Type complex(x, y) to convert x and y to a complex number with real part x and imaginary part y. x and y are numeric expressions

Mathematical Functions

Python includes the following functions that perform mathematical calculations.

Random Number Functions

Random numbers are used for games, simulations, testing, security, and privacy applications. Python includes the following functions that are commonly used.

Trigonometric Functions

Python includes the following functions that perform trigonometric calculations.

Mathematical Constants

The module also defines two mathematical constants −

 Strings are amongst the most popular types in Python. We can create them simply by enclosing characters in quotes. Python treats single quotes the same as double-quotes. Creating strings is as simple as assigning a value to a variable.

For example −

var1 = 'Hello World!'

var1 = 'Hello World!'

print("Updated String:- ", var1[:6]  +  'Python') When the above code is executed, it produces the following result −

Updated  String:-   Hello Python

Escape Characters

The following table is a list of escape or non-printable characters that can be represented with backslash notation.

An escape character gets interpreted; in a single-quoted as well as double-quoted strings.

String Special Operators

Assume string variable a holds 'Hello' and variable b holds 'Python', then −

String Formatting Operator

One of Python's coolest features is the string format operator %. This operator is unique to strings and makes up for the pack of having functions from C's printf() family.

Following is a simple example −

print  ("My  name  is  %s  and  weight  is  %d  kg!"  %  ('Zara',  21))

When the above code is executed, it produces the following result −

My name is Zara and weight is 21 kg!

Here is the list of complete set of symbols which can be used along with % −

Other supported symbols and functionality are listed in the following table −

Triple Quotes

Python's triple quotes come to the rescue by allowing strings to span multiple lines, including verbatim NEWLINEs, TABs, and any other special characters.

The syntax for triple quotes consists of three consecutive single or double-quotes.

 para_str  =  """ this is a long string that is made up of several lines and non-printable characters such as TAB ( \t ) and they will show up that way when displayed. NEWLINEs within the string, whether explicitly given like this within the brackets [ \n ], or just a NEWLINE within the variable assignment will also show up. """

print  (para_str) 

When the above code is executed, it produces the following result. Note how every single special character has been converted to its printed form, right down to the last NEWLINE at the end of the string between the "up." and closing triple quotes. Also, note that NEWLINEs occur either with an explicit carriage return at the end of a line or its escape code (\n) −

Output

this is a long string that is made up of several lines and non-printable characters such as TAB ( \t ) and they will show up that way when displayed. NEWLINEs within the string, whether explicitly given like this within the brackets [ \n ], or just a NEWLINE within the variable assignment will also show up.

Raw strings do not treat the backslash as a special character at all. Every character you put into a raw string stays the way you wrote it −

print  ('C:\\nowhere')

When the above code is executed, it produces the following result −

C:\nowhere

Now let's make use of raw string. We would put expression in r'expression' as follows −

print  (r'C:\\nowhere')

When the above code is executed, it produces the following result −

C:\\nowhere

Unicode String

In Python 3, all strings are represented in Unicode.In Python 2 are stored internally as 8-bit ASCII, hence it is required to attach 'u' to make it Unicode. It is no longer necessary now.

Built-in String Methods

Python includes the following built-in methods to manipulate strings −