Python is an interpreted programming language that marked a significant rise in the past decade. Web developers who choose Python as their programming language are enabled to integrate their systems more effectively and work at a faster speed. Moreover, when programmers utilize Python, they opt for an increase in the users’ productivity and a decrease in their maintenance costs. Programmers use Python for the web development of various types of desktop and web applications, mobile apps, websites, and others.
Python was invented in 1989 by Guido Van Rossum, who wanted to reduce the flaws of the ABC programming language, especially its lack of extensibility. His personal experience with error handling and with ABC made him become “aware of the importance of exceptions as a programming language feature”. Therefore, he decided to develop a new programming language, which he named “Python”. Many people think that the inspiration for the name of this programming language comes from the snake python, but instead, its name comes from the BBC show “Monty Python’s Flying Circus”.
Python is an interactive programming language that uses very clear syntax combined with remarkable power. It is extensible in C or C++ and has interfaces to many libraries and system calls. This programming language is created to incorporate different modules, classes, exceptions, as well as high-level dynamic data types. Developers can use Python for big data analytics, but it also has many other advantages, which is why it is considered as the programming language of the new decade. These are only a few essential advantages of using the Python programming language in the new decade:
- Easy-to-Use and Highly-Effective Programming Language
- Adaptive Nature
- Open-Source Programming Language
- Numerous Python Libraries
- Plentiful Python Frameworks
- Strong Online Community
Easy-to-Use and Highly Effective Programming Language
Technology is improving with every passing day, and people try to make their lives less complicated. Python is a programming language that simplifies coding due to its easily readable syntax and easy-to-use features. The simplicity of Python is one of the most important reasons why it is the main programming language used for Machine Learning (ML). Python’s syntax may be easily used by both experienced developers, as well as by beginners or students. Developers who use the Python programming language can focus on solving potential difficulties with ML instead of wasting their time on understanding the technical problems that might happen.
In addition to the ease of using Python as a programming language, developers can say with pride that this language is also highly effective. Other programming languages usually require the writing of countless lines of code. However, Python offers developers the possibility to finish a larger number of tasks with fewer lines of code. In addition, the code written in Python is easily readable and understandable. This is another of the reasons why this programming language is ideal for ML and creating such models.
Python is one of the most eminent programming languages which will continue trending in the new decade, thanks to its adaptive nature. In the past few years, developers have wasted a lot of their time on programming in different languages. With Python, this loss of time will be reduced to a minimum. Why is that? Because Python is a programming language that easily performs cross-language operations. The adaptiveness of Python and its portable nature allow data scientists to train their ML on their machines. Furthermore, Python’s adaptive nature allows integration of the Python libraries with Java, .NET, and C/C++ libraries.
Open-Source Programming Language
One of the main reasons Python is so popular today is because of its distributive nature. Many open-source projects are done in Python because creating Python packages and installing them is easy. Python developers install packages via pip (Pip Installs Packages), which downloads and installs packages from PyPI – an online repository of Python packages. Additionally, most Python projects contain a setup script that is easy to use. According to Nikola Dokoski, our Python expert who works in our company, this makes it easy to write a git project in Python and have other people contribute to it. There are over a million Python projects in Github alone.
Numerous Python Libraries
With the rise of Python’s popularity as one of the most dynamic programming languages, the number of libraries has increased. Nowadays, there are hundreds of Python libraries that developers may use to save their valuable time spent on programming. Some of the Python libraries have been specially created for Artificial Intelligence (AI) and Machine Learning (ML). For instance, Keras is one of the open-source libraries written in Python, which focuses mainly on neural networks. In addition, there are also other libraries written in Python, such as:
- SciPy (Scientific Python)
- NumPy (Numerical Python)
Pandas is the most widely-known open-source library written in Python for data analysis, which handles the basic maintenance and operation of structured data. Moreover, Matplotlib is a Python library that is excellent for data visualization and which enables its users to plot graphs in numerous types (pie charts, histograms, bar graphs). That is the main reason why Matplotlib is considered as the best plotting library for Python programming that any person can easily understand. SciPy is a library that deals with science, engineering, and mathematics. NumPy deals with numerical functionalities mainly, but also with linear algebra and other number capabilities. Scikit-learn is an open-source library for ML, which enables classification, regression, and clustering algorithms and which can be integrated with SciPy and NumPy.
Plentiful Python Frameworks
When it comes to Python frameworks, we asked again our colleague Nikola to share his favorite ones from his personal working experience. According to him, several frameworks make Python a competitive programming language in today’s web development sphere. Some of the more popular frameworks of his choice are Django, Flask, and Tornado WebServer.
Nikola’s first choice is Django – the most popular web development framework for Python. It is an MVC (Model View Controller) framework that standardizes a project’s layout by separating the project into apps but still utilizes Python’s flexible nature by allowing the developer to use third-party packages, or even to write their own. On the other hand, he considers Flask as a much simpler framework which does not limit the developers by having a specific project structure, but still allows many options for organizing their code. This leaves the developers with more freedom of how they will organize their code and what modules they will use. Finally, his third choice is Tornado WebServer – a very bare-bone framework that implements web server functionalities and leaves the business logic to the developer, allowing them a great degree of freedom.
Strong Online Community
One of the main advantages of the Python programming languages lies in its strong online community and the immense public support. The corporate and public support of the Python programming language only enables programmers to increase their knowledge of Machine Learning (ML), regardless of whether they are experienced or inexperienced developers. Moreover, thanks to the enormous online community, both Python and ML get easily promoted. Therefore many tutorials can be found on the internet. Corporate support has also played a great part in the online expansion of Python for ML. For instance, Google is one of the corporate supporters that have created many Python libraries.
If you believe that Python is the future of web development, hire us and get the best Python experts like Nikola to work for you. They will tell you how to implement the advantages of the Python programming language and to transform them into beneficial aspects for your business.