Why Python is Getting Popular!
A lot of people who are learning data science ask why Python is getting famous and how important it is to learn Python now! After looking at its popularity in recent times we can definitely say it’s very important. In this article, I am going to discuss the reason for the popularity and interview aspect for Python.
Easy to learn
Python is optimized for the developer’s time! Programmers who know both Python and C++ can agree that Python is slow but the number of lines of code for logic is less in Python compared to C++. In a time when, RAM and computational power are readily available, and hiring developers cost a fortune, it is evident to choose a language optimized for time. The learning curve for Python is minimal and that makes it the most popular language for students. The use of Python in technologies like AI, Data Science, Web Applications design, Game development, etc have made Python a general-purpose language and answers why it is popular. To get started with Python programming, you need to understand few fundamental aspects of how to master any programming language! The key here is practice, a lot of practice. As a beginner, you should at least spend 3 to 4 hours practicing. Here is the list of contents that will help you to get started.
- Computer science fundamentals like Memory, OS, bits, ports, and information transfer are required before starting as a programmer.
- Find a good IDE. If you are learning data science mostly you will be using Jupyterlab but for production work, it is better to use Spyder or PyCharm along with it.
- Learn version control systems like Git. This is an essential tool for a good programmer.
- Now to get started with the actual programming you can focus on operators, data types, dunder methods, functions, string formatting, file handling, and classes.
- Never read other’s code and assume you can do it! First, try by yourself multiple times. It is okay to get errors. After trying multiple times, you are still getting errors then take reference from resources like Stackoverflow. Practice lots of questions on daily basis on websites like Hackerank etc to get good at logic.
- Once you learn the fundamental logic, try to build small projects like tic-tac-toe games using Python, Minesweeper, or maybe create your own small bank! Try to approach the problem in both object-oriented ways and using functions.
One language solves all
As mentioned earlier, Python is popular for its wide application across verticals. But one of the major reasons for popularity will be to provide integration in both the development and production environment. Managing a large project is complex and time complexity in SDLC can be dragged for multiple factors. The development and Operations team has to work in sync to optimize efficient CI/CD. One of the common challenges tech teams faces when development and deployment environments have different languages. Due to the general-purpose behavior of Python, both teams can use the same language and save a lot of time. Let’s assume that you want to join a company as a data scientist. Only knowing the basics of Python will not be sufficient. The below libraries are specific to data science and if you are looking for other job roles like web application developer then you can find them on Google.
- Learn data science packages like Numpy, Scipy, Pandas, Matplotlib, Seaborn, Plotly, Sklearn, etc.
- For a deeper understanding of data science concepts like image processing and natural language processing, you might need to learn packages like PyTorch or Tensorflow.
- Let’s assume you have successfully created an application and you want to test it with real users! Learn flask or Django. This will be helpful for deployment.
- If you want to develop the frontend and backend logic you can also check the Plotly dash.
As you can see almost everything can be done in Python and justifies why Python is getting popular!
Maintainability and Scalability
An application goes through multiple iterations before final production and gets updates throughout its life. So, maintaining the code and making it accessible to a large set of users is a mammoth task. Python is more readable than other programming languages making it easy to comprehend and easy to maintain. Application size in Python is generally smaller due to its high-level programming paradigm and thus can easily scale to multiple users without burning lots of cloud resources. When it comes to microservices and cloud deployment Docker and Cloud providers have tons of pre-built methods and images to speed the process.
Large community and open source
Python community is one of the largest and most active ones in Stackoverflow. You get instant solutions to all the programming-related challenges and it is growing in number. Python is open source making it cherry on the cake. With all the inevitable ingredients for a perfect programming language, it’s just a matter of time since Python will put its complete supremacy over other programming languages in the near future.
This article was part of our initiative to make you guys more educated about how to learn data science and Python as a beginner. In case you are searching for offline data science courses in Bangalore, you can enquire here. If you want to have a good fundamental about the topic you can watch the MIT videos
. Thanks for reading and best wishes with your AI endeavor.