What makes python great

Aside from being some of the most popular software services in the world, what else do they have in common? Most of all, Python is easy to learn, clear to read, and simple to write in. This speeds up development without sacrificing reliability or scalability. But why exactly is Python such a good choice? And what areas of technology or business does Python benefit the most? In many cases, the choice of tools will decide your entire experience. Your work may be slower, your competition may outpace you, or your end result may fall below expectations.

Your choice of language at the start of the project will impact it profoundly in the future. For your software project to be a success, we recommend that you choose Python as your tool. Here are the main reasons why. 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 By using a popular language, you have a much higher chance of finding a solution to any problem you may encounter.

Python has a healthy community of enthusiasts that strive every day to make the language better by fixing bugs and opening new possibilities. One of them is Google. They are actively working on guides, tutorials, and other resources to get the most out of Python.

Python is accessible by design, making it one of the fastest languages in terms of speed of development. A user-friendly environment in the hands of your development team means less time wrestling with your building tool and more time spent actually building. Additionally, you can get a headstart with the rich selection of frameworks and libraries. They will save you the hassle of coding features by hand, accelerating your time-to-market.

Check out the most popular Python web frameworks and scientific libraries in the sections below. Because CPU time is rarely the limiting factor. So you need all the help you can get to shorten time-to-market, even if it leads to slower runtime execution. For situations where performance really does matter, Python offers tried and tested solutions to incorporate other, faster languages into the code—like Cython , for example. The language is designed to be readable and close to actual English, making it easy to decipher.

Python also requires fewer lines of code to achieve results compared to languages such as C or Java. Code review goes much faster when you have fewer lines of code to actually review, and the code reads like English.

No one can really predict when your user numbers will start surging and scalability will become a priority. In the current market, a business without a website might as well not exist. Moreover, the trends are pushing for more and more impressive web apps that, among others, include:. There are many advantages of Python that help you get results fast within the field of web development:. With a large selection of well-supported frameworks, you can find the right starting point for any project.

The most widely used Python web framework— at least until recently. Contrary to the all-in-one-package philosophy of Django, Flask works more like the glue that allows you to combine libraries with each other. Bottle is another framework that would rather stay out of the way than overwhelm the user with every single thing they might need.

The framework is lightweight and has no external dependencies other than the Python standard library stdlib. It works great for prototyping, as a learning tool, or for building and running simple personal web apps.

The maturity of Pyramid stems from the legacy of two previous frameworks: Pylons and repoze. Now merged into Pyramid, Pylons used to be one of the top Python frameworks.

Head over to our article for more exotic examples of Python web frameworks. The Internet of Things can be variously understood, depending on your perspective.

IoT often plays a role in projects involving wireless sensor networks, data analytics, cyber-physical systems, big data, and machine learning. Additionally, IoT projects often involve real-time analytics and processes. Ideally, your programming language for an IoT project should already be a strong choice for the aforementioned fields, while also being lightweight and scalable.

Most importantly, it has a Linux distro on board, which means it also uses Python, making coding for the Raspberry Pi simple and straightforward. 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. The Raspberry Pi is an incredibly versatile device you can use to build anything :.

It provides developers with a full ecosystem of tools, including an IDE, a toolchain for development, a multithreaded RTOS real-time operating system , a device manager, and a convenient mobile app to monitor and control Zerynth-powered devices. You can use Zerynth to program the most popular bit microcontrollers, connect them to Cloud infrastructures, and keep your devices running the latest version of your software with Firmware Over-the-Air updates.

Home Assistant is an open-source Python project for intelligent home automation. You can install it on a PC or a Raspberry Pi. Home Assistant drives automation; for example, it can control the lights in your house and measure the temperature in each room. On top of that, Home Assistant is compatible with a variety of drivers and sensors. This trend works in favor of using Python for IoT, because with greater memory and computational power comes greater freedom of choice in terms of picking the right programming language.

Therefore, when developers and project managers are looking to choose a language that brings results fast and makes life easier, they tend to go with Python. Writing in Python is as quick, easy, and painless in IoT as in other fields. In the current IoT environment, you choose your programming language just like you would choose it for any other project. Ease of writing matters more than the choice of language, and Python has that in droves.

Machine learning is the latest craze in the software development world. The very idea that computers can actively learn instead of operating in strict accordance with codified rules is simply exhilarating.

It offers a whole new approach to problem solving. At the forefront of machine learning is Python. Multiple studies unequivocally hail Python as the most popular language for machine learning and data science. There are several reasons why Python is a perfect fit for machine learning:. But there is one more argument to be made for Python here, which in the case of machine learning is greater than all the others combined: extensive open-source library support.

Python is famous for rich selection of libraries, especially for data science. Here are some of the most popular Python libraries for machine learning. Scikit-learn is the best known and arguably most popular Python library for machine learning. Built on SciPy and NumPy—and designed to interoperate with them—scikit-learn is open source, accessible to all, and reusable in a number of contexts.

The library features a wide variety of algorithms for: classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. Yet despite the barrage of options scikit-learn provides, the data mining and data analysis tools it offers are both simple and efficient.

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. The process was designed as analogous to the ways humans reason and learn. The flexible, high-performance architecture of the open-source library makes it easy to deploy numerical computation across multiple platforms, as well as from desktops to server clusters to mobile devices.

This pretty much speaks for itself. Nilearn is a high-level Python library for easy and fast statistical learning on neuroimaging data. The library leverages scikit-learn for a plethora of advanced machine learning techniques, such as pattern recognition or multivariate statistics. The applications of this include predictive modelling and connectivity analysis, among others.

Constructing domain-specific feature engineering is the highest value nilearn holds for machine-learning experts. Python is undoubtedly the hottest cake in the market now.

Many programmers and data science students are using python language for their development projects. Learning python is one of the important section in data science certification courses. In this way, the python language can provide plenty of fantastic career opportunities for students.

Due to the variety of applications of python, one can pursue different career options and will not remain stuck to one. The python language is so flexible that it gives the developer the chance to try something new.

The person who is an expert in python language is not just limited to build similar kinds of things but can also go on to try to make something different than before.

This kind of freedom and flexibility by just learning one language is not available in other programming languages. Now python language is being treated as the core programming language in schools and colleges due to its countless uses in Artificial Intelligence, Deep Learning, Data Science, etc.

It has now become a fundamental part of the development world that schools and colleges cannot afford not to teach python language. In this way, it is increasing more python Developers and Programmers and thus further expanding its growth and popularity.

Python language can help a lot in automation of tasks as there are lots of tools and modules available, which makes things much more comfortable. It is incredible to know that one can reach an advanced level of automation easily by just using necessary python codes. Python is the best performance booster in the automation of software testing also. One will be amazed at how much less time and few numbers of lines are required to write codes for automation tools.

Some of the reasons why Python is growing at a supersonic speed. We hope this article has shed some good light on python language and its importance. Python has a solution for every field.

It is the most versatile language till now and has a bright future ahead. There is a long list of fields where Python is considered to be the most suitable programming language. 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. Python allows newbie programmers to build prototypes and tools quite swiftly allowing one to experience immediate satisfaction.

Because of ease of use, this language is quickly becoming the introductory language taught to beginners. It is easy to understand. In spite of being a high level language, Python is a beginner friendly language because it is easy to understand. It does not stress people with machine like language that is difficult to comprehend.

Instead, it read like the English language by handling the detailed complex and stressful syntax and command, which makes programming unappealing.

You can master the concept of programming more intensely rather than get stuck on learning the language. You get support from a community. The designers placed less of an emphasis on conventional syntax, which makes it easier to work with, even for non-programmers or developers. The language is used for system operations, web development, server and administrative tools, deployment, scientific modeling and much more. Plus, it just so happens that one of the biggest tech companies in the world — Google — uses the language for a number of their applications.

They even have a developer portal devoted to Python , with free classes offered including exercises, lecture videos and more. Python has neither of those problems. Plus, the developer community is incredibly active. That means any time someone needs help or support, they can get it in a timely manner. This active community helps ensure that developers of all skills levels — beginner to expert — always have somewhere to find support.