Python-based iterators and generators

Iterators and generators

Iterators

Iterators are a way to access the elements of a collection. An iterator object is accessed from the first element of the collection, knowing that all of the elements are accessed at the end. Iterators can only move forward without going backwards, but that's fine, because people seldom retreat in the middle of an iteration. In addition, a large part of the iterator is not required to first prepare all the elements of the entire iteration process. An iterator computes an element only when it falls to an element, and before or after that, the element may not exist or be destroyed. This feature makes it particularly well-suited for traversing some large or infinite collections.

Characteristics

• The visitor does not need to care about the structure inside the iterator, but simply continues to fetch the next content through the next () method
• A value in the collection cannot be accessed randomly, and can only be accessed from beginning to end
• You can't go back halfway through the interview.
• Facilitates recycling of large data sets, saving memory

  >>> a = iter ([1,2,3,4,5])>>>a<list_iterator object at 0x101402630>>>> A.__next__()1>>> A.__next__()2>>> A.__next__()3>>> A.__next__()4>>> A.__next__()5>>> A.__next__() Traceback (most recent): File"<stdin>", Line 1,inch<module>stopiteration

  2. Generator

  When a function call returns an iterator, the function is called the Generator (generator), and if the function contains the yield syntax, the function becomes the generator

def func ():     yield 1    yield 2    yield 3    yield 4

In the code above: Func is a function called a generator, and when you execute this function func () you get an iterator.

>>> temp = func ()>>> temp. __next__ ()1>>> temp. __next__ ()2>>> temp. __next__ ()3>>> temp. __next__ ()4>>> temp. __next__ () Traceback (most recent):   " <stdin> "  in <module>stopiteration

Python-based iterators and generators