{"id":75762,"date":"2020-01-28T10:06:18","date_gmt":"2020-01-28T04:36:18","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=75762"},"modified":"2020-01-28T10:06:18","modified_gmt":"2020-01-28T04:36:18","slug":"python-iterators","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/python-iterators\/","title":{"rendered":"Python Iterators – Learn to create your own iterator in Python"},"content":{"rendered":"

Today we are going to learn about Python iterators<\/strong>. They are used<\/strong> everywhere in Python programming.<\/p>\n

Chances are you might have already used them in loops<\/strong>, list comprehensions<\/strong>, or generators<\/strong>. It is important to study what iterators<\/strong> are and how you can create<\/strong> your own iterators<\/strong>.<\/p>\n

We will cover everything about iterators in this article. So let\u2019s get started.<\/p>\n

What are Python Iterators?<\/h3>\n

In very simple words, Python iterators<\/strong> are objects<\/strong> that we can iterate upon<\/strong>. Iterating means to repeat a process multiple numbers of times<\/strong>. A single process<\/strong> is called an iteration<\/strong>.<\/p>\n

In Python, we use iterators to repeat a process like traversing a sequence<\/strong>.<\/p>\n

For example<\/strong>, a list<\/strong> can be traversed<\/strong> by reading one object<\/strong> at a time.<\/p>\n

Iterators are used a lot in for-loops<\/strong>, lists comprehensions<\/strong>, and generators in Python<\/strong>.<\/p>\n

Creating a Python Iterator<\/h3>\n

The iterator protocol in Python states that an iterable object must implement two methods: __iter__()<\/strong> and __next__()<\/strong>.<\/p>\n

First, we see how to create a Python iterator using Python built-in function iter()<\/strong>, and then, later on, we will create a Python iterator object from scratch<\/strong>.<\/p>\n

The iter() function is a built-in function<\/strong> that is used to create an iterator that we can iterate using the next() function<\/strong>. First, we create a sequence<\/strong> of elements<\/strong> that we want to iterate<\/strong>.<\/p>\n

Code:<\/strong><\/p>\n

nums = [2, 4, 1, 9, 6]<\/pre>\n
Then we use the iter() function<\/strong> to get an iterable object<\/strong>. The iter()<\/strong> function implicitly calls<\/strong> the __iter__()<\/strong> method.<\/p>\n
Code:<\/strong><\/p>\n
nums_iter = iter( nums )\nprint( nums_iter )<\/pre>\n
The iter function<\/strong>, when used on lists<\/strong>, returns the list_iterator<\/strong> object.<\/p>\n
Code:<\/strong><\/p>\n
<list_iterator object at 0x00000258BF9CE5C0><\/pre>\n
The next() function<\/strong> is used<\/strong> to access<\/strong> the elements<\/strong> from the iterator<\/strong> one at a time.<\/p>\n
Code:<\/strong><\/p>\n
print(next(nums_iter))<\/pre>\n
Output:<\/strong><\/p>\n
2<\/div>\n
Now, when we call the next() function<\/strong> again, it will access<\/strong> the next element<\/strong> in the list<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
print(next(nums_iter))<\/pre>\n
Output:<\/strong><\/p>\n
4<\/div>\n
Like this, we can access<\/strong> all the elements<\/strong> of the list<\/strong>. But now, let\u2019s see what will happen when the list<\/strong> comes to an end<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
print(next(nums_iter))\nprint(next(nums_iter))\nprint(next(nums_iter))\nprint(next(nums_iter))<\/pre>\n
Output:<\/strong><\/p>\n
1
\n9
\n6
\nTraceback (most recent call last):
\n\u00a0\u00a0<\/b>File “<stdin>”, line 9, in <module>
\nStopIteration<\/div>\n
As we can see, when we tried to access<\/strong> the next element<\/strong>, which does not exist<\/strong>, so the Python<\/strong> raises a StopIteration error<\/strong>.<\/p>\n
Alternatively, you can also traverse<\/strong> the elements using the __next__()<\/strong> method, and it works the same as the next() function<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
nums_iter = iter({1,2,3,4,5})\n\nprint(nums_iter.__next__())\nprint(nums_iter.__next__())\nprint(nums_iter.__next__())\nprint(nums_iter.__next__())\nprint(nums_iter.__next__())\nprint(nums_iter.__next__())<\/pre>\n
Output:<\/strong><\/p>\n
1
\n2
\n3
\n4
\n5
\nTraceback (most recent call last):
\n\u00a0\u00a0<\/b>File\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 “C:\/Users\/Techvidvan\/AppData\/Local\/Programs\/Python\/Python38-32\/test.py”, line 8, in <module>
\n\u00a0\u00a0\u00a0\u00a0<\/b>print(nums_iter.__next__())
\nStopIteration<\/div>\n
The dir() function<\/strong> can be used<\/strong> to see the list<\/strong> of available<\/strong> methods<\/strong> on the iterable object<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
dir(nums_iter)<\/pre>\n
Output:<\/strong><\/p>\n
[‘__class__’, ‘__delattr__’, ‘__dir__’, ‘__doc__’, ‘__eq__’, ‘__format__’, ‘__ge__’, ‘__getattribute__’, ‘__gt__’, ‘__hash__’, ‘__init__’, ‘__init_subclass__’, ‘__iter__’, ‘__le__’, ‘__length_hint__’, ‘__lt__’, ‘__ne__’, ‘__new__’, ‘__next__’, ‘__reduce__’, ‘__reduce_ex__’, ‘__repr__’, ‘__setattr__’, ‘__setstate__’, ‘__sizeof__’, ‘__str__’, ‘__subclasshook__’]<\/div>\n
For-loop for Iterators<\/h3>\n
You might have already used<\/strong> the for-loop<\/strong> in Python<\/strong>.<\/p>\n
Iterators<\/strong> are working<\/strong> in the background<\/strong> of a for-loop<\/strong>. We can use the for-loop<\/strong> to iterate<\/strong> over<\/strong> the elements<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
for city in (\"Delhi\", \"Punjab\", \"Chennai\", \"Pune\"):\n  print(city)<\/pre>\n
Output:<\/strong><\/p>\n
Delhi
\nPunjab
\nChennai
\nPune<\/div>\n
The for-loop<\/strong> automatically creates<\/strong> the iterator<\/strong> for the tuple<\/strong> and then in each iteration, it stores<\/strong> the current object in the city variable<\/strong>.<\/p>\n
Lists<\/strong>, tuples<\/strong>, sets<\/strong>, strings<\/strong>, etc are all examples of iterable elements<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
for character in \"Hello!\":\n  print(character)<\/pre>\n
Output:<\/strong><\/p>\n
H
\ne
\nl
\nl
\no
\n!<\/div>\n
Create your Own Python Iterator<\/h3>\n
Now we will see how you can create<\/strong> your own iterables<\/strong>.<\/p>\n
To create<\/strong> an iterator<\/strong> object on your own<\/strong> it is necessary to implement the __iter__()<\/strong> and __next__()<\/strong> methods. The __iter__() method will always return the iterator object<\/strong> itself. We can initialize variables<\/strong> in this method. The __next__()<\/strong> method is created<\/strong> to return the next element<\/strong> from the iterator<\/strong>. To reach the end we must raise the StopIteration<\/strong> error<\/strong> in this method.<\/p>\n
Infinite Iterator<\/h4>\n
Let\u2019s see an example:<\/p>\n
Code:<\/strong><\/p>\n
class EvenNumbers:\n  def __iter__(self):\n    self.num = 0\n    return self\n\n  def __next__(self):\n    next_num = self.num\n    self.num += 2\n    return self.num\n\nevens = EvenNumbers()\neven_iter = iter(evens)\n\nprint(next(even_iter))\nprint(next(even_iter))\nprint(next(even_iter))\nprint(next(even_iter))\nprint(next(even_iter))\nprint(next(even_iter))<\/pre>\n
Output:<\/strong><\/p>\n
2
\n4
\n6
\n8
\n10
\n12<\/div>\n
Here, the class EvenNumbers<\/strong> is returning even numbers every time we call the next() function<\/strong>. This will iterate infinitely<\/strong> because we haven\u2019t specified the condition when it needs to stop<\/strong>.<\/p>\n
For creating iterators that we want to stop at certain conditions, we will implement the StopIteration<\/strong> exception in the __next__()<\/strong> method. We can then use a for loop<\/strong> to automatically iterate<\/strong> over all the elements<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
class EvenNumbers:\n  def __iter__(self):\n    self.num = 0\n    return self\n\n  def __next__(self):\n    if(self.num < 10):\n        next_num = self.num\n        self.num += 2\n        return self.num\n    else:\n        raise StopIteration\n\nevens = EvenNumbers()\neven_iter = iter(evens)\n\nfor n in even_iter:\n    print(n)<\/pre>\n
Output:<\/strong><\/p>\n
2
\n4
\n6
\n8
\n10<\/div>\n
Benefits of Using Python Iterators<\/h3>\n
The main advantage of using the iterators is that the program is only holding one object at a time from a sequence<\/strong> or a collection<\/strong>.<\/p>\n
For example<\/strong>, to perform an additional operation on each element of a huge list like [1334, 5534, 5345, 345, 144, \u2026\u2026. ]<\/strong>. We will only hold one value<\/strong> at a time to perform operations on. There is no need to keep all the elements of the list<\/strong> in the memory<\/strong>. This saves the resources<\/strong> of computers<\/strong>.<\/p>\n
Summary<\/h3>\n
In this article, we have observed everything<\/strong> about iterators<\/strong>. We talked about what are Python iterators<\/strong>, how you can iterate<\/strong> the elements<\/strong> with for-loop<\/strong> and how you can create<\/strong> your own iterators<\/strong>.<\/p>\n
Moreover, we understood the benefits<\/strong> of using iterators<\/strong> in your program<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"
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