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This article mainly explains "what are the problems about Python iterator". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "what are the problems about Python iterator"?

The first question: what is an iterator?

Iterator, English Iterator, it is first an object, and secondly, it is a way to access iterable sequences (Iterable). It usually starts with the first element of the sequence and ends until all the elements are accessed.

The iterator is also a special object, especially in that it must implement two methods: _ _ iter__ and _ _ next__.

The second question: why is there an iterator?

One of the most important values of iterators: saving memory, which is insignificant when there is a small amount of data.

However, when the amount of data is large or the performance of the program is high, its value is highlighted.

The third question: how do iterators save memory?

You only know that you can save memory by using iterators, but you don't know how to use them. Here's the answer.

First create a list:

In [1]: a = [1, 3, 5, 9, 10]

Second, each element in the list + 1, create a new list

In [2]: A1 = [item1 for i in a]

Print each element in A1 in turn:

In [8]: for i in A1:...: print (I)

The above operation is equivalent to:

A1 = [] for i in a: a1.append (iTun1) for i in A1: print (I)

The space complexity is O (n), and n is the number of elements in list a.

But what is the space complexity of using an iterator to implement the above element + 1 and print it?

Ait = (iTun1 for i in a) # gets the generator, which is also a special iterator for i in ait: print (I)

The above operation is equivalent to:

For i in a: print (iTun1)

No extra space is needed, so the space complexity of using iterator plus 1 and printing is O (1).

Conclusion: iterators save more space!

The fourth question: how to customize an iterator?

As mentioned above, the iterator object must implement two methods, and to be more specific, we demonstrate how to customize an iterator.

Customize an iterator to implement the Fibonacci sequence:

# Fibonacci sequence class Fabs (): def _ _ init__ (self,max): self.max=max self.n,self.a,self.b=0,0,1 # definition _ _ iter__ method def _ _ iter__ (self): return self # definition _ _ next__ method def _ _ next__ (self): if self.n

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