Python just took a big jump forward in 2021

Python is one of the languages that is witnessing incredible growth and popularity year by year. In 2017, Stackoverflow calculated that python would beat all other programming languages by 2020 as it has become the fastest-growing programming language in the world. It was created by Guido van Rossum, and first released on February 20, 1991.

“Python is an experiment in how much freedom programmers need. Too much freedom and nobody can read another’s code; too little and expressiveness is endangered

-Guido Van Rossum

One of the amazing features of Python is the fact that it is actually one person’s work. Usually, new programming languages are developed and published by large companies employing lots of professionals, and due to copyright rules, it is very hard to name any of the people involved in the project. Python is an exception. Learning Python gives the programmer a wide variety of career paths to choose from. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications.

Learning Python allows the programmer to focus on solving problems, rather than focusing on syntax. Its relative size and simplified syntax give it an edge over languages like Java and C++, yet the abundance of libraries gives it the power needed to accomplish great things.

Use the Django Framework to Rapidly Develop Web Apps

Django is a user-friendly web framework in Python that’s widespread in its use. Here’s an overview of what makes it so useful

Django is a high-level web framework in Python that allows users to easily build web applications rapidly with minimal code. The Django framework follows the model-view-controller (MVC) design pattern. This setup facilitates the easy development of complex database-driven web apps. Through these design patterns, Django emphasizes the reusability of components. It also follows the don’t-repeat-yourself (DRY) principle, which reduces repetition in software through abstraction and data normalization to avoid redundant code.

Django can be used in a variety of web applications, including customer relationship management systems (CRMs), social media applications, online marketplaces, on-demand delivery applications, and many more. Lots of familiar web applications currently use Django, including Instagram, Dropbox, Spotify, and Mozilla, among several others. As you might suspect based on its widespread use, the MVC design pattern enables rapid development, scalability, and security in web applications.

DJANGO IN USE: INSTAGRAM

Now that we’ve seen some of the benefits of Django, let’s look at a specific instance of its application in practice. The quality of Instagram’s user experience and service is in large part due to much of its core functionality being written in Django. For example, Instagram uses the Django application Sentry for error reporting. This allows Instagram developers to diagnose bugs, modify code and optimize the performance of application components.


Instagram is also built on top of a Django tool called Dynostats, which also allows you to monitor the efficiency of application components. Using Dynostats, developers can monitor user requests, application responses, application latency, and more. This allows developers to easily pin down the causes of an application slowing down and which leads to solutions faster.

Why Python is Best for AI, ML, and Deep Learning

The Python programming language has been in the game for so long, and it is here to stay.

Artificial intelligence projects are different from traditional software projects. The difference lies in the technology stack, the skills required for AI-based projects, and the need for in-depth research. To implement AI aspirations, you need to use a programming language that is stable, flexible, and has available tools. Python provides all of these, which is why we see many Python AI projects today.

Python facilitates developers to increase the confidence and productivity about their developing software from development to deployment and maintenance. The benefits of making Python the perfect solution for machine learning and AI-driven projects include simplicity and consistency, flexibility, access to powerful AI and machine learning (ML) libraries and frameworks, platform independence, and large communities. These things increase the popularity of the language.

BUILD YOUR CAREER WITH PYTHON

Here’s the list of the top Python jobs that you can pursue to boost your career in Python

Python is one of the most popular programming languages across the globe and it offers the most promising career opportunities as well. This demand for Python developers is increasing every year. There is a reason why this high-level programming language is so popular. The python language is one of the most accessible programming languages available because it has simplified syntax and is not complicated, which gives more emphasis on natural language. Python is also one of the best tools for creating dynamic scripts on large as well as small scales.

List of top Python jobs for 2021:

●       Python Developer

●       Python Web Developer

●       Full-Stack Developer

●       Machine Learning Engineer

●       Data Analyst

●       Software Developer

Python Developer

The most suitable job that you must get into after acquiring skills in python is python developer. A Python Developer is responsible for the coding, designing, deploying, and debugging of development projects, typically on the server-side (or back-end). They may, however, also help organizations with their technological framework.

Python Web Developer

A Python web developer is responsible for writing server-side web application logic. Python web developers usually develop back-end components, connect the application with the other third-party web services, and support the front-end developers by integrating their work with the Python application.

Full-Stack Developer

A full-stack developer is someone who works with the back end of an application as well as the front end. Full-stack developers have to have some skills in a wide variety of coding niches, from databases to graphic design and UI/UX management to do their job well. The full-stack engineer job description usually includes using a range of different technologies and languages to develop applications. Full Stack Developers approach software holistically since they cater to both user experience and functionality

Machine Learning Engineer

In the last couple of years, the job postings for this position have increased to about 330%. If you are skilled in Python, you will be given the preference above other candidates. The role of a machine learning engineer is to build and train machines, programs, and other computer-based systems for applying these to making predictions. Python becomes ideal for this role because of its capability of data automation and algorithms

Data Analyst

One of the most common uses for Python is its ability to create and manage data structures quickly. Pandas, for instance, offers a plethora of tools to manipulate, analyze, and even represent data structures and complex datasets. Additionally, you can use Python /R to write your own data analysis algorithms that can be directly integrated into your business intelligence tools via API.

Software Developer

The role of a software developer engages in identifying, designing, installing, and testing a software system they’ve built for a company from the ground up. It can range from creating internal programs that can help businesses be more efficient to producing systems that can be sold. When software developers deliver a software system, they also maintain and update the program to ensure that all security problems are fixed, and it operates with new databases. Python is a common language used in the software development process, making knowledge of the language key to landing a job as a software developer.

It seems that Python is winning these days, in part because of the rise of data science and its ecosystem of machine-learning software libraries like NumPy, Pandas, Google’s TensorFlow, and Facebook’s PyTorch.Python, which started as a simple scripting language, as an alternative to Perl, has become mature. Its ease of learning, its huge amount of libraries, and its widespread use in all kinds of domains have made it the most popular programming language of today.

Ref: Python Developer Training

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Author: Sandeep Krishnan
Department: Python
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