Iterator object in Python

Iterators are objects that allow us to take each of its elements, this action can be repeated. In this article, Quantrimang will discuss with you how the iterator works in Python and how you can build your own iterator.

Iterators are objects that allow us to take each of its elements, this action can be repeated. In this article, Quantrimang will discuss with you how the iterator works in Python and how you can build your own iterator using __iter__ and __next__ methods.

Iterator object in Python Picture 1

What is an iterator in Python?

Iterator is everywhere in Python, inside loops, comprehension, generator .

It is simply objects that allow us to retrieve each element, whenever you use loops or techniques to get the value of an element group at a given time.

Technically, Python in Python must implement two special methods: __iter __ () and __next __ (), collectively referred to as the iterator protocol (Iterator Protocol).

The __iter__ method returns the iterator object itself. This method is required to install both "iterable" and iterator objects in order to use for and print statements.
The __next__ method returns the next element. If there are no more elements, a StopIteration error will occur.

Iterator object in Python Picture 2

Iterable objects are an object after using methods that will return an iterator, such as String, List, and Tuple.

Iter () is a built-in function in Python that takes the input as an iterable object and returns an iterator.

 # Khai bao mot list 
 my_list = [4, 7, 0, 3] 
  
 # lay mot iterator bang cach su dung iter() 
 my_iter = iter(my_list) 
  
 ## su dung next() 
  
 #prints 4 
 print(next(my_iter)) 
  
 #prints 7 
 print(next(my_iter)) 
  
 ## next(obj) chinh la obj.__next__() 
  
 #prints 0 
 print(my_iter.__next__()) 
  
 #prints 3 
 print(my_iter.__next__()) 
  
 ## Xay ra loi StopIteration vi het gia tri tra ve 
 next(my_iter)

Run the program, the result is:

 4 
 7 
 0 
 3 
  
 Traceback (most recent call last): 
 File "", line 24, in 
 next(my_iter) 
 StopIteration

A similar way to return this result is to use a for loop .

 >>> for element in my_list: 
 . print(element) 
 . 
 4 
 7 
 0 
 3

How the loop works

As we see in the above example, the for loop can be repeated automatically through the use of the list.

In fact, the for loop can be repeated on any iterable. Let's take a closer look at how a for loop is implemented in Python.

 for element in iterable: 
 # do something with element

Made similar to:

 # iter_obj là một iterator object tạo từ iterable 
 iter_obj = iter(iterable) 
  
 # vòng lặp 
 while True: 
  try: 
  # sử dụng next 
  element = next(iter_obj) 
  except StopIteration: 
  # nếu xảy ra lỗi StopIteration thì vòng lặp sẽ được break ra ngoài 
  break

In this example, inside the for loop we create an iterator object called iter_obj by calling iter () on iterable.

And as you can see, the for loop here is an infinite while loop.Next () inside the loop retrieves the elements to execute commands in for loop. When all values are taken, the StopIteration exception will be generated and the loop will end.

Build iterator iterator in Python

We can build the iterator as a class. Building an iterator is easy in Python, we only need to implement __iter __ () and __next __ () methods.

 class PowTwo: 
  
  def __init__(self, max = 0): 
  self.max = max 
  
  def __iter__(self): 
  self.n = 0 
  return self 
  
  def __next__(self): 
  if self.n <= self.max: 
  result = 2 ** self.n 
  self.n += 1 
  return result 
  else: 
 raise StopIteration

The __iter__ method will cause the object to become an iterable object.

The return value of __iter__ is an iterator. It needs a __next__ method and returns StopIteration if there are no more tests.

Create an iterator and run the program as follows:

 >>> a = PowTwo(4) 
 >>> i = iter(a) 
 >>> next(i) 
 1 
 >>> next(i) 
 2 
 >>> next(i) 
 4 
 >>> next(i) 
 8 
 >>> next(i) 
 16 
 >>> next(i) 
 Traceback (most recent call last): 
 . 
 StopIteration

We can also use a for loop to iterator iterators

 >>> for i in PowTwo(5): 
 . print(i) 
 . 
 1 
 2 
 4 
 8 
 16 
 32

Iterator iterates infinitely in Python

Not all iterator objects will be called all elements and end when there are no elements left. There are some iterator instances that will loop infinitely. Examples are as follows:

 >>> int() 
 0 
 
 >>> inf = iter(int,1) 
 >>> next(inf) 
 0 
 >>> next(inf) 
 0

We can see that the int () function always returns 0. Therefore, passing it in iter (int, 1) will return an iterator until the value returns to 1. This is never happens and this is an infinite loop iterator. You need to pay attention when handling in such cases.

Alternatively, you can also build an infinite loop iterator. The following example will loop indefinitely and return odd numbers because there are no stop conditions.

 class InfIter: 
 
  def __iter__(self): 
  self.num = 1 
  return self 
 
  def __next__(self): 
  num = self.num 
  self.num += 2 
  return num

Run the program:

 >>> a = iter(InfIter()) 
 >>> next(a) 
 1 
 >>> next(a) 
 3 
 >>> next(a) 
 5 
 >>> next(a) 
 7

The advantage of using iterator iterators is that they save resources. As shown above, you can get all odd numbers without storing on the entire digital system in memory.

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