Why python

Python is everywhere. You may not even realize how widespread it is. Download the PDF. Why Use Python? Python is popular and widely supported Python is quickly ascending to the forefront of the most popular programming languages in the world. The incredible growth of Python is shown very clearly by StackOverflow: Its continuous rise in popularity is reflected in the TIOBE index and Coding Dojo identifies Python as one of the most in-demand programming languages of Writing Python code is easy, which speeds up development Python is accessible by design, making it one of the fastest languages in terms of speed of development.

Python gives you tried and tested scalability No one can really predict when your user numbers will start surging and scalability will become a priority. Takeaways Why Python, then?

If you really need to find the one language to rule them all, the choice is clear. Python for Web Development. Moreover, the trends are pushing for more and more impressive web apps that, among others, include: flawless mobile and desktop versions, asymmetrical layouts, Progressive Web Apps, integrated animations, ML-powered chatbots.

Advantages of Python for web development There are many advantages of Python that help you get results fast within the field of web development: Python has a large selection of pre-built libraries for just about anything. Scientific computing, image processing, data processing, machine learning , deep learning—you name it, Python has it. Python code takes less time to write due to its simple and clean syntax. Because of this, code written in Python lends itself very well to creating quick prototypes.

Python accelerates the ROI of commercial projects. The reason behind this is similar to the previous point: you can write and ship your code faster. This is especially important for startups. Python has a built-in framework for unit tests. This helps you ship bug-free code. Top Python web frameworks Django The most widely used Python web framework— at least until recently. Pyramid The maturity of Pyramid stems from the legacy of two previous frameworks: Pylons and repoze.

Python for the Internet of Things. Python fits these criteria very well. The language is supported by a large, helpful community, which has led to the creation of an extensive set of pre-written libraries, making it easier to implement and deploy working solutions.

Python is portable, expandable, and embeddable. This makes Python not system-dependent and allows it to support many of the single-board computers currently available on the market, regardless of the architecture or operating system.

Python works great for managing and organizing complex data. For IoT systems that are particularly data-heavy, this is especially useful. Python is easy to learn without forcing you to get acquainted with many formatting standards and compiling options The most immediate consequence of this are faster results.

Python code is easily readable and compact thanks to its clean syntax. This is helpful on small devices with limited memory and computational power. Python is the language of choice for the Raspberry Pi. It matters a great deal, since the Raspberry Pi is one of the most popular microcontrollers on the market. Python offers tools that streamline the IoT development process, such as webrepl.

This gives you the option to use your browser to run Python code for IoT. Since Python is an interpreted language, you can easily test your solution without compiling the code or flashing the device.

Think of it as the cherry on top of an already delicious cake. What tools are available for Python in IoT? Raspberry Pi Have you ever seen an interesting IoT project around the web? The Raspberry Pi is an incredibly versatile device you can use to build anything : a media center, a retro gaming machine, a time-lapse camera, a robot controller, an FM radio station, a web server, a motion-capture security system, a Twitter bot, a mini-desktop PC.

Home Assistant Home Assistant is an open-source Python project for intelligent home automation. Desktop programming vs. Takeaways Writing in Python is as quick, easy, and painless in IoT as in other fields.

Python for Machine Learning. But why is that? Top Python libraries for machine learning Python is famous for rich selection of libraries, especially for data science. TensorFlow TensorFlow was originally developed by engineers and researchers at Google to meet their needs for a system that can build and train neural networks to find and decipher correlations and patterns.

What machine learning challenges can Python libraries help you solve? Python for supervised learning Supervised machine learning is one of the most widely-applied uses of AI. Python for reinforcement learning Reinforcement learning algorithms learn to modify their behavior to make the right decisions after receiving feedback.

Takeaways Python is the top choice for machine learning because its myriad of pre-prepared, tried-and-true libraries does most of the heavy lifting during the development process.

Python for Startups. Python can give you all of that. Why is Python the best programming language for your startup? Notable startups with Python in their tech stack We understand that theory is one thing and practice is another. Deuce Tennis Deuce Tennis is a startup connecting tennis players with courts and clubs near them. TravelPerk TravelPerk made headlines a while back as one of the hottest Barcelonian startups—and for good reason.

Zappi Like the previous entries, Zappi also enables individuals to get in contact with others. Takeaways Startups are both exciting and terrifying endeavors. Python for Fintech. Advantages of Python for fintech Hedge fund and investment banking industries have long decided that Python is an ideal choice for fintech because the language addresses many of their highly specific needs: creating platforms for risk and trade management; quantitative rate problem solving; simplifying data regulation, compliance, and analytics by leveraging the abundance of Python libraries.

Why should you choose Python for your fintech software product? Fintech belongs with Python for a number of reasons: Clean syntax Python code is easy to understand, because it resembles actual English. Fast time to market Python is a dynamically typed language, making development in it quicker than in statically typed languages such as Java.

Helpful libraries Python boasts an extensive array of libraries for a plethora of purposes; a lot of those are excellent for fintech and finance. Whatever your question, Python has the answer. Top fintechs with Python in their tech stack Many fintech companies have chosen to use the many benefits Python offers to their advantage.

Here are some examples. Venmo Venmo started out as a fintech startup. Newable Business Finance Newable Business Finance is a platform that can be used to apply for business loans. Zopa Zopa was founded on a bold principle: cut out the middleman and let borrowers and lenders deal directly with each other. Vyze Vyze is a leading fintech for manufacturers and retailers.

Takeaways The languages and frameworks you choose for your fintech will to a large extent decide the longevity and ultimate fate of your product. We think the choice should be clear. Python for Data Science. What makes Python the best choice for Data Science? Ease of use Since it was designed with ease of use in mind, Python is a great tool for every data scientist, from a beginner without tech background to a pro with years of professional experience.

Versatility The great thing about Python is that there are plenty of ways it can be applied without compromising on the quality of the final result and without the need to make use of any other languages. Many sectors including the healthcare sector, finance sector, aerospace sector, and banking sector rely heavily on Python.

There are many big names that have either built their applications on Python or have completely shifted their tech stack to Python. Python was founded around 30 years ago and so it has a vast community of efficient developers. These developers are constantly helping out the beginners through their constant support and in-depth journals.

There is plenty of documentation and guides that the newbie programmers could learn and enhance their Python. We have seen that many programming languages do not grow due to the lack of community support.

But Python is lucky in this case. Python is a very versatile language and if you have a good knowledge of Python, there can be various career opportunities in your hand. Some of these opportunities are as follows: You can be a Python developer right after acquiring the Python knowledge.

Python developers are responsible for building websites, optimize data algorithms, or write clean and efficient Python codes. A data analyst has to deal with large sets of data, analyze them and make them visualized. If you are a Python geek and love to play with data then this job is for you.

Project management is in high demand as a project manager is highly responsible for the business and marketing of the companies. Data Science. Data Science All Courses M. Sc in Data Science — University of Arizona. Software Engineering All Courses M. Table of Contents. Why is Python becoming so popular in this decade? What role does the Python developer community play?

What career opportunities does Python provide? Leave a comment. Cancel reply Your email address will not be published. Python is even used in 3D animation software such as Lightwave, Blender, and Cinema 4D, showing just how versatile the language is.

These can help you develop your knowledge and challenge your abilities with the programming language:. That concludes our look at what P ython programming can be used for. As you can see, there are many applications for this popular language, with a wide support network and a diverse range of libraries that can help. There are many reasons why you might want to start learning Python.

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This active community helps ensure that developers of all skills levels — beginner to expert — always have somewhere to find support. And, as any experienced programmer or developer knows, when you run into development issues in the middle of crunch time, support can either make or break you. It helps big time when a programming language has a corporate sponsor. Why does this matter?

Because if companies like Google want their team — and future developers — to work with their systems and apps, they need to provide resources. It contributes a growing list of documentation and support tools and provides free advertising for the language, at least in the development world. The use of big data and cloud computing solutions in the enterprise world has also helped skyrocket Python to success.

It is one of the most popular languages used in data science, second only to R.