Programmers, with their skills in coding and problem-solving, have gained immense popularity in today's tech-driven world. Their ability to write efficient and functional code makes them valuable assets in various industries, leading to high demand for their expertise.

Programmers possess analytical thinking and attention to detail, enabling them to break down complex problems and devise effective solutions. They are often self-driven and possess a passion for continuous learning, as the technology field is ever-evolving. Time management is crucial for programmers to handle multiple tasks and meet project deadlines effectively. Many programmers rely on an online calendar planner to organize their schedules, set reminders, and prioritize their work efficiently. Online calendars offer features like sharing schedules with teammates, setting recurring events, and integrating with other productivity tools, enhancing programmers' ability to manage their time effectively.

Python and Golang are some of the most in-demand languages in the DevOps world. And when you had to choose only one of two languages to learn, it can be difficult to do so.

Python

It's pretty easy to dive into Python when you don't know anything about development. At the same time, the language has plenty of libraries and frameworks: DevOps Python Tools in the GitHub repositories, a library for working with GitLab, converters (for example, XML to Yaml), and so on.

Python is an interpreted language that allows you to write scripts. This is useful when you need to have a script in your pocket that does the right thing but isn't used regularly. It’s more convenient than carrying a binary around with you all the time. The language does a great job when you need to automate 2 tasks one after the other, but do it a little trickier than Bash can.

Python also does a great job with orchestration systems. Let's take the same Ansible: some things are more difficult to do in it than to write your own module. Even Kubernetes written in Go can be run in Python. For example, check the status of pods and, in which case, alert in Telegram or Slack.

Simplicity

Python is an understandable language that anyone can understand. No knowledge of OOP principles or complex data structures is required. Let's take Java for comparison. How to print "Hello, World" to the console in Java? You need to create a class in which to declare a public static main method that takes an array of strings as an argument. Next, another class is called in this method, which will finally print the inscription to the console. How is this done in Python? We just write: print('Hello, World') and immediately get the result.

Expandability

A large number of specialized libraries include many ready-made software structures. This allows you not to waste energy on their independent implementation and saves the programmer's time. It is especially worth emphasizing libraries for Data Science: Scikit-learn, Matplotlib, Seaborn, Pandas, and TensorFlow. They include various Machine Learning algorithms, statistical tools, visualization, and data mining techniques.

Openness

Unlike closed and established programming languages such as Java (Oracle), C# (Microsoft), etc., each developer can contribute to the development of the language. For example, if you find a bug or want to expand the functionality of the language, make a pull request to the github repository or just report your ideas in the issues tab. Such openness ensures that Python does not contain potential vulnerabilities, secret tracking functions, or other dangerous aspects.

Readability

The Python community has its own convention, the so-called PEP 8 [2], whose principles they tend to follow in practice. For example, observe an indent of 4 spaces after the definition of a class, function, or condition; import modules to do at the beginning of the file, and then put 2 empty lines; in the case of a large number of arguments for a function, they should be written one below the other, forming a visual table. Linked conditions are not welcome when several operations lie on the same line.

All this saves the developer time and effort when reading someone else's code. Also, excellent readability of Python code is achieved due to the conciseness of the language.

Convenience

Built-in data structures such as lists, dictionaries, tuples, and sets are easy to understand and don't distract from your coding work. And the ways to create them are as simple and memorable as possible. For example, lists are wrapped in square brackets, tuples in round brackets, sets and dictionaries in curly brackets.

Conclusion

Python is a versatile and widely-used language known for its simplicity and readability. It has a large and active community, extensive libraries, and frameworks that make it suitable for a broad range of applications.