Python is a feature-rich and general-purpose coding language which has literally swept over the field of programming. Py: Python is the most commonly used language among developers, and is a clear favorite among data scientists and developers alike, thanks to its clear, easy-to-read syntax and extensive libraries. In this article, we will go under the hood of Python, look at its important features, and dissect why professionals, as well as beginners, find Python loveable. Humble history of Python
Guido van Rossum released Python in 1991.
The post Who Invented Python first appeared on Programming with Mosh. It was written to be a straight forward and intuitive language thereby reducing the barrier to entry associated with text driven programming. Py has seen many improvements and changes in recent years, the most recent major release was in 2008 with the release of togelup Python 3.
Growing in popularity Py has soared in popularity in recent years, on account of its flexibility and accessibility. With a large community of developers behind it, the language continues to improve and develop new libraries and frameworks mean it is easy to get started. This teamwork is what has contributed to Python being one of the most popular programming languages in the world.
Features and Benefit of Python
One of the features which separates Py from the rest of the programming languages is its beautiful and simple syntax. Py introduces new indentation and that defines blocks of code which makes it look more cleaner and readble. This simplicity not only helps to bind the learners from scratch but also becomes a productive playground for professionals.
Another important thing to keep in mind is that Py has a huge library that comes preinstalled, that means there are a lot of tools and modules available out of the box. If it’s from file operations to complex mathematical calculations the standard library got you covered. Py also comes with a very large number of third-party packages and frameworks that you can install to extend these basic features. For those that do not know what it is, here is the official NPM explanation: npm is the package manager for javascript and the world’s largest software registry — a collection of packages of reusable code that developers can use to save time and effort.
Syntax and basic concepts in Py
Python also is designed to make code look like instructions in plain text. The above code looks good in terms of visually so and easy to understand due to no explicit braces or keywords. This language enables developers to write code in not only procedural but also object-oriented programming paradigms, so that one can use it as per the requirement.
Dynamic typing: Py contains dynamic typing while passing the value of a variable to some other variable. This flexibility means that you do not have to specify the type of a variable as Py can do this for you and therefore makes Py much more efficient to write in since you do not have to declare the variable types.
Furthermore, Python has many data types help Py developers to store and manipulate data such as numbers, strings, lists, tuples, dictionaries, and sets, etc.
Python variables and data types
Python is a strongly typed dynamic language. Data types are important and need to be explicitly declared as jupyter does not support data type conversion. Numbers can be of the integer type or float or complex type. A string is effected as a sequence of characters that can be processed in a number of built-in method.
Lists: Lists are just collections of items, ordered and changeable
Tuples: Tuples are like lists, but they seem immutable.
Dictionaries : Dictionaries are python equivalent of a hash table, they are also related with key-value pairs and set are unordered collections of unique elements.
Dynamically Typed — Variables in Python can store values of different types during their lifetime. You create a variable by giving it a name then you assign a value to it, and later you can reassign them with another value. When it comes to unpacking that data, Py comes to our help to do that with just one line.
Python control flow statements
The control flow statements are used in Py to control this flow on the basis of some conditions. The if-else statement is used to implement more than one condition for an algorithm. A while loop will run repeatedly for the block of code that you provide as long as a particular condition is true. For loop: For loop is used to iterate over a sequence or collection of items.
Python supports other control flow statements such as break to exit a loop prematurely, continue to skip the rest of the loop in the current iteration and pass as a placeholder.
Python Function and Module
In Py, functions are a group of related statements that perform a specific task. This helps to organize code in logical units and makes it modular and maintainable for developers. Functions can take an input, and produce and out put, they can have parameters and return values.
Py Modules Module is nothing but.py script file which consists of Py code, It is grouped into packages. Modules help developers split their code into smaller, more manageable files, which can help them engage into collaboration and reuse the code from one project to another. The module in Python is nothing but a functional block element that contains various functionalities to do some specific work. Py provides an inbuilt of more than 200+ # modules in its standard library.
OOPs in Python:
One of the core types of programming Py supports is object-oriented programming (OOP); this is the creation and manipulation of objects, which can store the data and state that you need. OOP Object,OOP Objects are instances of classes that can have properties,and methods. Inheritance: You can use inheritance, you do not have to also in some cases but you can if you need them. Then it provides encapsulation, polymorphism and many more other complex and scalable applications.
OOP enables developer to prepare the reusable and modular code, so that code organization and code readability can be improve. Python is preferred by many programmers when it comes to writing large applications because Python supports object-oriented programming, so it is easy to deal with complex software systems with Python.
Libraries And Frameworks In Python
One of the major selling points of Python is the broad and capable library and framework ecosystem that it has. From web development to data analysis, machine learning and automation, you name a domain and Python has a library or framework, directly proportional to your task to help you.
Py has some of the widely used frameworks like Django & Flask for web development which take care of a lot of common tools and structure you need to build robust and scalable web applications. There are plentiful of libraries that can be used for data analysis such as NumPy, Pandas for data manipulation and Matplotlib for data visualization. Among the libraries in Machine Learning, popular ones like scikit-learn and TensorFlow offer a laundry list of algorithms, and abstractions for creating and running models.
CONCLUSION — FUTURE OF PYTHON
There also seems to be no stopping in the popularity of Py. The simplicity, scalability and ecosystem of libraries & frameworks that python provides make it a great option for any level of developer. Given the continuing evolution of tech, Python seems poised to remain one of those forces for the foreseeable future.
All of these points add on to make Python user-friendly, readable and with a multitude of functions which is why it has become popular amongst professionals and students. The large standard library, third-party packages, and active community further boost its adoption. So, if you are new or experienced developers then one language you must know is Py. If you like reading this article then please consider reading our article about Chamomile.
