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Python: Determinacy

Functions in every programming language have fundamental properties. These properties help predict the behavior of functions, how to test them, and where to use them. These properties include determinacy.

A deterministic function returns the same result every time if the input parameters are the same. For example, a function that counts the number of characters can be called deterministic:

len('hexlet')  # 6
len('hexlet')  # 6

len('wow')  # 3
len('wow')  # 3

You can call this function and pass the value 'hexlet' as many times as you want, and it will always return 6.

Let's also look at the reverse case: nondeterministic functions. For example, a function that returns a random number belongs to this category: we will always get different results even if we use the same input. If at least one in a million calls to a function returns a different result, it is considered nondeterministic. This applies even if it doesn't take parameters:

# Import syntax will be studied later in Hexlet
from random import random

# A function that returns a random number
random()  # 0.09856613113197676
random()  # 0.8839904367241888

Determinism is an important property of a function, as it affects many aspects. For example, deterministic functions are convenient to work with, as they're easy to optimize and test. If possible, it's better to make the function deterministic.

Instructions

The random() function returns a random number from 0 to 1 with many decimal places. Implement code that displays a random integer between 0 and 10. For this task, you need the random() function and the round(), function, which rounds the value passed to it

round(2.320000789855705) # 2

Try to solve this task using only 1 line

Algorithm

Since random() returns numbers between 0 and 1, we need to multiply by 10 to get numbers between 0 and 10. Then we round the result to get what we need.

Tips

If you've reached a deadlock it's time to ask your question in the «Discussions». How ask a question correctly:

  • Be sure to attach the test output, without it it's almost impossible to figure out what went wrong, even if you show your code. It's complicated for developers to execute code in their heads, but having a mistake before their eyes most probably will be helpful.
Found a bug? Have something to add? Pull requests are welcome!