Set generators allow you to loop through

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Python list comprehensions are considered "syntactic sugar" and are used to reduce the amount of code. Set generators They represent an expression of the form: {expression for item in iterable if condition}. As you can see, it differs from lists only by the presence of curly brackets. Set generators can be used to filter out unnecessary elements in some set. For example, we need to select files with the txt extension: txt = {t for t in files if t.lower().endswith((“.txt))} different iterables with conditionals, create sets of sets, or make a set fixed.

Generators in Python: How to Use Them Generators in Python: How to Use Them 87% of our graduates are already working in IT Leave a request and we will help you choose a new profession Leave a request Generator expressions Declaring generator expressions is syntactically similar to creating dictionaries or lists, but unlike lists, generators do not australia email list store all the values ​​of the executed function in memory, but only the last element of the sequence, the transition condition, or the breakpoint. Let's take as an example a generator expression that cubes numbers from 1 to 5: n = (i**3 for i in range(1, 6)) print(n) > <generator object <genexpr> at 0x7fb6dd886510>

When printing the variable n, the interpreter reports that the created object is a generator. The next() method is used to calculate the next value: print(next(n)) >1 print(next(n)) >8 print(next(n)) >27 print(next(n)) >64 print(next(n)) >125 print(next(n)) > StopIteration Let's do the same thing using a for loop: n = (i**3 for i in range(1, 6)) for i in n: print(i) > 1 8 27 64 125 The next(n) method sequentially calculates and outputs the values: 1, 8, 27, 64, 125. This erases previous values ​​from memory. During the 6th iteration, all values ​​will be deleted, so the interpreter will raise a StopIteration exception.