Python iter Function

What is Python iter Function? How to Use it With Examples

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What is Python iter?

The Python iter() function is used to return iterators from iterable objects such as lists, tuples, dictionaries, or sets).

It simply means that you can convert values to iterator objects from iterable objects.

In addition to that, the iter() function in Python helps you traverse values in different kinds of objects.

Example:

names = ("python", "for", "free")

print(next(iter(names)))
print(next(iter(names)))
print(next(iter(names)))

Output:

python
for
free

iter() syntax

iter() syntax enables the Python program free from unwanted errors.

This syntax enables the program to deliver the exact output that the programmer expects.

iter(object, sentinel)

iter() parameters

The parameters of the iter() method consist of the following:

  • object – an object in form of an iterable which will turn into an iterator object.
  • sentinel – a value that represents the end of the iteration.

These iter() parameters are also known as formal arguments. The parameters deliver information between functions and procedures.

iter() return value

The iter() function returns the iterator value from the collection of iterable objects, whether in the form of a list, strings, tuples, etc.

The argument to the iter() function can be either an iterable or a sequence.

In general, the object argument can be any object that supports an iteration or sequence protocol.

This is how the iter() method works:

Python iter() Example Program

The for loop is the typical approach for traversing a collection (objects).

Example 1:

letters = ['a', 'b', 'c', 'd', 'e']
for a in letters:
    print(a)

Output:

a
b
c
d
e

Explanation:

The for loop in this illustration iterates through a list of objects (letters) and outputs each component one by one.

The iter() method is used implicitly when traversing an iterable object inside a for loop.

Example 2:

letters = ['a', 'b', 'c', 'd', 'e']

print(next(iter(letters)))
print(next(iter(letters)))
print(next(iter(letters)))
print(next(iter(letters)))
print(next(iter(letters)))

Output:

a
b
c
d
e

Explanation:

As a result of the fact that we specified a list collection object in the previous example, the iter() function returns the iterator object.

We are able to obtain each individual element of the collection by utilizing the next() method that is contained within an iterator object.

iter() for Custom Objects Example Program

Python has a built-in function called iter() that makes it easier to turn custom objects into iterators.

An iterator for the specified object is what the iter() function brings back (an array, set, tuple, or custom objects).

It creates an object whose components, when accessed via the next() function, can be viewed and modified one at a time.

When working with loops, this is helpful information to have.

Example:

names = ["Python", "For", "Free"]
iter = iter(names)

try:
    print(iter.__next__())
    print(iter.__next__())
    print(iter.__next__())

except:
    print("\n'StopIterationError': Iteration Done.")

Output:

Python
For
Free
'StopIterationError': Iteration Done.

Explanation:

The __iter__() function generates an iterator object that traverses each component of the object.

This traversing is known as an argument. The __next__() function returns the next element in the sequence.

When working with callable objects and sentinel values, the iteration process continues until the value is found or the maximum number of elements has been exhausted.

In every event, the unaltered version of the object is preserved.

iter() with sentinel parameter example program

The sentinel parameter is what lets you know when the sequence has reached its conclusion.

Having said that, the class needs to be callable, which will cause the __next__() method to invoke internally.

Example:

class DataStore:
    def __init__(self, data):
        self.index = -1
        self.data = data

    def __iter__(self):
        return self

    def __next__(self):
        if (self.index == len(self.data) - 1):
            raise StopIteration
        self.index += 1
        return self.data[self.index]

    _call_ = _next_


ds = DataStore([1, 2, 3])
itr = iter(ds, 3)  # sentinel is 3, so it will stop when encounter 3

for i in itr:
    print(i)

Output:

1
2

Explanation:

By including the line __call__ = __next__ in the DataStore class that is about to be updated, it will be possible to show the use of the sentinel parameter.

What is the difference between an iterator and for loop?

An iterator can be safe over many threads, while a for loop cannot because it directly accesses elements.

When a for loop is executed, the for statement executes the object’s iter() method.

If this call works, the iterator object will give back an iterator object with the __next__() method, which lets you access the object’s elements in order.

Why is an iterator better than for loop?

When used on collections without random access, the iterator method is much better than the for loop approach.

For some reason, the for-each loop, for loop, and iterator all perform similarly in collections that support random access.

Summary

In summary, this tutorial provides the necessary information to understand how the Python iter() function works.

By understanding the iter() function, programmers can now apply it to traverse their Python codes.

This will enable cross-object values among different kinds of objects.

Additionally, knowing another function of Python programming bring you more skills and understanding.

You may also read or visit: Python Exit Program: Easy Ways For Beginners

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