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  • Features

    Python – FeaturesPython is a feature-rich, high-level, interpreted, interactive, and object-oriented scripting language. Python is a versatile and very popular programming language due to its features such as readability, simplicity, extensive libraries, and many more. In this tutorial, we will learn about the various features of Python that make it a powerful and versatile programming language.

    Python Important Features

    Python’s most important features are as follows:

    Easy to Learn

    This is one of the most important reasons for the popularity of Python. Python has a limited set of keywords. Its features such as simple syntax, usage of indentation to avoid clutter of curly brackets and dynamic typing that doesn’t necessitate prior declaration of variable help a beginner to learn Python quickly and easily.

    Dynamically Typed

    Python is a dynamically typed programming language. In Python, you don’t need to specify the variable time at the time of the variable declaration. The types are specified at the runtime based on the assigned value due to its dynamically typed feature.

    Interpreter Based

    Instructions in any programming languages must be translated into machine code for the processor to execute them. Programming languages are either compiler based or interpreter based.

    In case of a compiler, a machine language version of the entire source program is generated. The conversion fails even if there is a single erroneous statement. Hence, the development process is tedious for the beginners. The C family languages (including C, C++, Java, C# etc) are compiler based.

    Python is an interpreter based language. The interpreter takes one instruction from the source code at a time, translates it into machine code and executes it. Instructions before the first occurrence of error are executed. With this feature, it is easier to debug the program and thus proves useful for the beginner level programmer to gain confidence gradually. Python therefore is a beginner-friendly language.

    Interactive

    Standard Python distribution comes with an interactive shell that works on the principle of REPL (Read Evaluate Print Loop). The shell presents a Python prompt >>>. You can type any valid Python expression and press Enter. Python interpreter immediately returns the response and the prompt comes back to read the next expression.

    >>>2*3+17>>>print("Hello World")
Hello World

    The interactive mode is especially useful to get familiar with a library and test out its functionality. You can try out small code snippets in interactive mode before writing a program.

    Multi-paradigm

    Python is a completely object-oriented language. Everything in a Python program is an object. However, Python conveniently encapsulates its object orientation to be used as an imperative or procedural language such as C. Python also provides certain functionality that resembles functional programming. Moreover, certain third-party tools have been developed to support other programming paradigms such as aspect-oriented and logic programming.

    Standard Library

    Even though it has a very few keywords (only Thirty Five), Python software is distributed with a standard library made of large number of modules and packages. Thus Python has out of box support for programming needs such as serialization, data compression, internet data handling, and many more. Python is known for its batteries included approach.

    Some of the Python’s popular modules are:

    Open Source and Cross Platform

    Python’s standard distribution can be downloaded from https://www.python.org/downloads/ without any restrictions. You can download pre-compiled binaries for various operating system platforms. In addition, the source code is also freely available, which is why it comes under open source category.

    Python software (along with the documentation) is distributed under Python Software Foundation License. It is a BSD style permissive software license and compatible to GNU GPL (General Public License).

    Python is a cross-platform language. Pre-compiled binaries are available for use on various operating system platforms such as Windows, Linux, Mac OS, Android OS. The reference implementation of Python is called CPython and is written in C. You can download the source code and compile it for your OS platform.

    A Python program is first compiled to an intermediate platform independent byte code. The virtual machine inside the interpreter then executes the byte code. This behaviour makes Python a cross-platform language, and thus a Python program can be easily ported from one OS platform to other.

    GUI Applications

    Python’s standard distribution has an excellent graphics library called TKinter. It is a Python port for the vastly popular GUI toolkit called TCL/Tk. You can build attractive user-friendly GUI applications in Python. GUI toolkits are generally written in C/C++. Many of them have been ported to Python. Examples are PyQt, WxWidgets, PySimpleGUI etc.

    Database Connectivity

    Almost any type of database can be used as a backend with the Python application. DB-API is a set of specifications for database driver software to let Python communicate with a relational database. With many third party libraries, Python can also work with NoSQL databases such as MongoDB.

    Extensible

    The term extensibility implies the ability to add new features or modify existing features. As stated earlier, CPython (which is Python’s reference implementation) is written in C. Hence one can easily write modules/libraries in C and incorporate them in the standard library. There are other implementations of Python such as Jython (written in Java) and IPython (written in C#). Hence, it is possible to write and merge new functionality in these implementations with Java and C# respectively.

    Active Developer Community

    As a result of Python’s popularity and open-source nature, a large number of Python developers often interact with online forums and conferences. Python Software Foundation also has a significant member base, involved in the organization’s mission to “Promote, Protect, and Advance the Python Programming Language“

    Python also enjoys a significant institutional support. Major IT companies Google, Microsoft, and Meta contribute immensely by preparing documentation and other resources.

    Apart from the above-mentioned features, Python has another 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.

  • History of Python

    Python was developed by Guido van Rossum (a Dutch programmer) in the late 1980s 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. Guido van Rossum wanted Python to be a high-level language that was powerful yet readable and easy to use.

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

    For many uninitiated people, the word Python is related to a species of snake. Rossum though attributes the choice of the name Python to a popular comedy series Monty Python’s Flying Circus on BBC.

    Being the principal architect of Python, the developer community conferred upon him the title of Benevolent Dictator for Life (BDFL). However, in 2018, Rossum relinquished the title. Thereafter, the development and distribution of the reference implementation of Python is handled by a nonprofit organization Python Software Foundation.

    Who Invented Python?

    Python was invented by a Dutch Programmer Guido Van Rossum in the late 1980s. He began working on Python in December 1989 as a hobby project while working at the Centrum Wiskunde & Informatica (CWI) in the Netherlands. Python’s first version (0.9.0) was released in 1991.

    Evolution of Python The Major Python Versions

    Following are the important stages in the history of Python −

    Python 0.9.0

    Python’s first published version is 0.9. It was released in February 1991. It consisted of features such as classes with inheritance, exception handling, and core data types like lists and dictionaries..

    Python 1.0

    In January 1994, version 1.0 was released, armed with functional programming tools, features like support for complex numbers etc and module system which allows a better code organization and reuse.

    Python 2.0

    Next major version − Python 2.0 was launched in October 2000. Many new features such as list comprehension, garbage collection and Unicode support were included with it. Throughout the 2000s, Python 2.x became the dominant version, gaining traction in industries ranging from web development to scientific research. Various useful libraries like like NumPy, SciPy, and Django were also developed.

    Python 3.0

    Python 3.0, a completely revamped version of Python was released in December 2008. The primary objective of this revamp was to remove a lot of discrepancies that had crept in Python 2.x versions. Python 3 was backported to Python 2.6. It also included a utility named as python2to3 to facilitate automatic translation of Python 2 code to Python 3. Python 3 provided new syntax, unicode support and Improved integer division.

    EOL for Python 2.x

    Even after the release of Python 3, Python Software Foundation continued to support the Python 2 branch with incremental micro versions till 2019. However, it decided to discontinue the support by the end of year 2020, at which time Python 2.7.17 was the last version in the branch.

    Current Version of Python

    Meanwhile, more and more features have been incorporated into Python’s 3.x branch. As of date, Python 3.11.2 is the current stable version, released in February 2023.

    What’s New in Python 3.11?

    One of the most important features of Python’s version 3.11 is the significant improvement in speed. According to Python’s official documentation, this version is faster than the previous version (3.10) by up to 60%. It also states that the standard benchmark suite shows a 25% faster execution rate.

    • Python 3.11 has a better exception messaging. Instead of generating a long traceback on the occurrence of an exception, we now get the exact expression causing the error.
    • As per the recommendations of PEP 678, the add_note() method is added to the BaseException class. You can call this method inside the except clause and pass a custom error message.
    • It also adds the cbroot() function in the maths module. It returns the cube root of a given number.
    • A new module tomllib is added in the standard library. TOML (Tom’s Obvious Minimal Language) can be parsed with tomlib module function.

    Python in the Future

    Python is evolving everyday where Python 3.x receiving regular updates. Python’s developers community is focusing on performance improvements making it more efficient while retaining its ease of use.

    Python is being heavily used for machine learning, AI, and data science, so for sure its future remains bright. It’s role in these rapidly growing fields ensures that Python will stay relevant for years.

    Python is also increasingly becoming the first programming language taught in schools and universities worldwide, solidifying its place in the tech landscape.

    Frequently Asked Questions About Python History

    1. Who created Python?

    Python created by Guido Van Rossum, a Dutch Programmer.

    2. Why Python is called Python?

    Python does not have any relation to Snake. The name of the Python programming language was inspired by a British Comedy Group Monty Python.

    3. When was Python’s first version released?

    Python’s first version was released in February 1991.

    4. What was the first version of Python?

    Python’s first version was Python 0.9.0

    5. When was Python 3.0 version released?

    Python 3.0 version was released in December 2008.

  • Higher order functions

    in Python allows you to manipulate functions for increasing the flexibility and re-usability of your code. You can create higher-order functions using nested scopes or callable objects.

    Additionally, the functools module provides utilities for working with higher-order functions, making it easier to create decorators and other function-manipulating constructs. This tutorial will explore the concept of higher-order functions in Python and demonstrate how to create them.

    What is a Higher-Order Function?

    A higher-order function is a function that either, takes one or more functions as arguments or returns a function as its result. Below you can observe the some of the properties of the higher-order function in Python −

    • A function can be stored in a variable.
    • A function can be passed as a parameter to another function.
    • A high order functions can be stored in the form of lists, hash tables, etc.
    • Function can be returned from a function.

    To create higher-order function in Python you can use nested scopes or callable objects. Below we will discuss about them briefly.

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    Creating Higher Order Function with Nested Scopes

    One way to defining a higher-order function in Python is by using nested scopes. This involves defining a function within another function and returns the inner function.

    Example

    Let’s observe following example for creating a higher order function in Python. In this example, the multiplier function takes one argument, a, and returns another function multiply, which calculates the value a * b

    defmultiplier(a):# Nested function with second number   defmultiply(b):# Multiplication of two numbers  return a * b 
   return multiply   

# Assigning nested multiply function to a variable  
multiply_second_number = multiplier(5)# Using variable as high order function  
Result = multiply_second_number(10)# Printing result  print("Multiplication of Two numbers is: ", Result)

    Output

    On executing the above program, you will get the following results −

    Multiplication of Two numbers is:  50

    Creating Higher-Order Functions with Callable Objects

    Another approach to create higher-order functions is by using callable objects. This involves defining a class with a __call__ method.

    Example

    Here is the another approach to creating higher-order functions is using callable objects.

    classMultiplier:def__init__(self, factor):

      self.factor = factor
    
   def__call__(self, x):return self.factor * x
 
# Create an instance of the Multiplier class
multiply_second_number = Multiplier(2)# Call the  Multiplier object to computes factor * x
Result = multiply_second_number(100)# Printing result  print("Multiplication of Two numbers is: ", Result)

    Output

    On executing the above program, you will get the following results −

    Multiplication of Two numbers is:  200

    Higher-order functions with the ‘functools’ Module

    The functools module provides higher-order functions that act on or return other functions. Any callable object can be treated as a function for the purposes of this module.

    Working with Higher-order functions using the wraps()

    In this example, my_decorator is a higher-order function that modifies the behavior of invite function using the functools.wraps() function.

    import functools

defmy_decorator(f):@functools.wraps(f)defwrapper(*args,**kwargs):print("Calling", f.__name__)return f(*args,**kwargs)return wrapper

@my_decoratordefinvite(name):print(f"Welcome to, {name}!")

invite("Tutorialspoint")

    Output

    On executing the above program, you will get the following results −

    Calling invite
Welcome to, Tutorialspoint!

    Working with Higher-order functions using the partial()

    The partial() function of the functools module is used to create a callable ‘partial’ object. This object itself behaves like a function. The partial() function receives another function as argument and freezes some portion of a functions arguments resulting in a new object with a simplified signature.

    Example

    In following example, a user defined function myfunction() is used as argument to a partial function by setting default value on one of the arguments of original function.

    import functools
defmyfunction(a,b):return a*b

partfunction = functools.partial(myfunction,b =10)print(partfunction(10))

    Output

    On executing the above program, you will get the following results −

    100

    Working with Higher-order functions using the reduce()

    Similar to the above approach the functools module provides the reduce() function, that receives two arguments, a function and an iterable. And, it returns a single value. The argument function is applied cumulatively two arguments in the list from left to right. Result of the function in first call becomes first argument and third item in list becomes second. This is repeated till list is exhausted.

    Example

    import functools
defmult(x,y):return x*y

# Define a number to calculate factorial
n =4
num = functools.reduce(mult,range(1, n+1))print(f'Factorial of {n}: ',num)

    Output

    On executing the above program, you will get the following results −

    Factorial of 4:  24