In one of our previous articles, we already looked at the powerful tool of functions. We learned how to define a subroutine in code, add arguments, a block of instructions, and a return value to it. We also learned how to call it to solve problems further down the program. Today, we'll look at an interesting tool called recursive functions in Python —an essential knowledge for completing DevOps/DevNet reviews courses in Tashkent.
What is recursion, DevOps courses / DevNet reviews Tashkent
First of all, let's understand what recursion is. This applies, of course, to the topic of today's article—functional programming in Python . In this context, recursion is the addition of a function statement that calls the same function again, but with new data. Typically, this data is the result of the previous iteration of the function call. Of course, our DevOps / DevNet courses—the best Tashkent courses for IT professionals in Uzbekistan —will cover this in more detail.
That is, if we analyze the principle of recursion, it looks like this: a program calls a subroutine, passing it data for processing as an argument. The first-generation subroutine processes them. And then it calls the second generation of the same subroutine, passing it the processed data as an argument for repeated processing. And so on, ideally, ad infinitum.
However, recursion has both advantages and disadvantages. The advantages of recursive functions include:
- ease of mastering the recursive programming method;
- the ability to solve complex problems with small blocks of code;
- high performance in tasks that can be broken down into a finite number of typical subtasks.
While among the disadvantages of this method the following are of the greatest importance:
- counterintuitiveness of the results of the work and increasing complexity of the algorithm analysis;
- an avalanche-like increase in the consumption of computer resources can fill up all available memory and load the CPU in a matter of seconds);
- high demands on the understanding of the process on the part of the programmer.
To sum it up, recursion is easy to learn, but can be difficult to use. And in inexperienced hands, this tool can bring no less headaches than benefits. And also become an ideal source of memory leaks in your project. Therefore, it is very important to learn how to use it correctly, and also to use it exactly where recursion gives the greatest benefit.
Examples of using recursion to solve problems in Python
Recursive programming is certainly essential for those planning to take DevOps/DevNet courses (reviews in Tashkent ) and become IT specialists in Uzbekistan in 2024. Perhaps the simplest example of using recursion is to calculate the sum of numbers from 1 to n . Of course, you can use a loop to solve this problem. However, the recursive solution is slightly shorter and demonstrates the tool's operating principle.
First, declare the function def rec_sum (n) and add a colon. On the next line, indented by 4 spaces, add a conditional statement and a check for equality to one: if n==1 : and, indented by an additional 4 spaces, return 1 . On the next line, on the same level as the if statement , add a line containing the recursive algorithm: return n + rec_sum(n - 1).
As a result, the function will call more and more versions of itself, decrementing the argument by one each time. Until it reaches zero, at which point the algorithm stops. To learn more, we recommend taking the DevOps / DevNet engineer courses in Tashkent on the SEDICOMM platform.
SEDICOMM University Team : Cisco Academy , Linux Professional Institute , Python Institute.