Python programming language is ideal for web development. Websites are constantly changing and, therefore, their contents change over time. For example, the design of a website can be updated or new page elements can be added.
Python is the most popular and widely used computer programming language, especially in the field of Data Science and Machine Learning. Unlike HTML, CSS or JavaScript, its use is therefore not limited to web development. It can be used for any kind of programming and software development.
In particular, it is used for the back end development of web or mobile applications, and for the development of software and applications for PCs. It also allows you to write system scripts, in order to create instructions for a computer system
In addition, Python is the most popular computer language for processing big data, performing mathematical calculations, or machine learning. Overall, this is the language of choice for Data Science.
One of the main use cases of Python is scripting and automation. This language can replace shell scripts, for example, but also automates interactions with web browsers or graphical application interfaces. It also allows system provisioning or configuration through tools like Ansible or Salt. However, these are far from its only applications.
Another use is application programming. It is possible to create all kinds of applications using this language. Although it does not support generating standard binaries from a script, third-party packages like cx Freeze and PyInstaller compensate for this weakness.
In addition, Python is the most widely used language for Data Science and Machine Learning. The vast majority of libraries used for these two data analysis disciplines have Python interfaces. This explains its popularity as a high-level command interface for machine learning libraries and other digital algorithms.
This language is also used for the creation of Web services and RESTful APIs. Its various native libraries and third-party web frameworks allow you to program data-driven websites with just a few lines of code. Another use case is metaprogramming and code generation. Every element of this language is an object, including modules and libraries. This is what makes Python a very efficient code generator. It is possible to write applications that manipulate their own functions, which are much more extensible than with other languages. It can also be used to run code generation systems like LLVM to create code in other languages.
Python is increasingly used in programming for two main reasons. First, as mentioned above, it is one of the most versatile and generalist languages. Additionally, despite its versatility, Python remains one of the easiest programming languages to learn. For good reason, its syntax is similar to everyday English. This is what allows a beginner to understand it and therefore to start learning it very easily.
Despite its simplicity, Python can be used for the most complex projects. It is used for example in the field of AI and Machine Learning. Therefore, this language is used by a wide variety of profiles. Examples include novice programmers, web and mobile application developers, software engineers, but also Data Scientists and other data professionals.
The Python language has many strengths. Due to its minimalism, it requires very little time to start using it. Beginners can learn to master it easily. Thus, developers spend more time trying to solve problems than dwelling on the language complexities.
Another advantage is its popularity. Widely used, this language is supported by most operating systems, and there is a large number of compatible libraries and service APIs. Despite its ease of use, this language can be used for scripting and automation as well as professional quality software development. It is therefore extremely versatile. Additionally, each update to the Python language adds new, very useful features that keep it aligned with modern development practices. In fact, it is not obsolete.
Despite its number of advantages, it is worth noting that Python is not suitable for all tasks. This is a “high level” language. It is therefore not suitable for programming at the system level. It is also not ideal for situations requiring independent cross-platform binaries. An independent application for Windows, macOS, and Linux won’t be easy to code in Python. Finally, it’s best to avoid Python for situations where speed is a top priority for the application. In these cases, it is better to turn to C and C ++ or another language of the same type.
