This Python iter() function tutorial gives you additional knowledge in exploring Python programming. It uses examples and demos to let you understand how the Python iter function works.
Python programming is a flexible language and multiple functions that programmers explore. As the language upgrades, you also need to discover more of its functions and built-in data types.
Learn how to know the version of Python programming through How To Check Python Version.
To help deepen your knowledge in Python, this tutorial will walk through one of the language’s functions: Python iter() function with examples.
The iter() function in Python helps you in traversing values in different kinds of objects.
Iteration (iter function) is the process that converts values from iterable objects into iterator objects.
Also read or visit: Python Exit Program: Easy Ways For Beginners
What is python iter?
iter() method is used to return iterators from iterable objects such as lists, tuples, dictionaries, or sets). This means that you can convert values to iterator objects from iterable objects.
names = ("python", "for", "free") print(next(iter(names))) print(next(iter(names))) print(next(iter(names)))
python for free
iter() syntax enables the Python program free from unwanted errors. This syntax enables the program to deliver the exact output that the programmer expects.
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 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).
letters = ['a', 'b', 'c', 'd', 'e'] for a in letters: print(a)
a b c d e
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
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)))
a b c d e
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.
names = ["Python", "For", "Free"] iter = iter(names) try: print(iter.__next__()) print(iter.__next__()) print(iter.__next__()) except: print("\n'StopIterationError': Iteration Done.")
Python For Free 'StopIterationError': Iteration Done.
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.
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)
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 iterator and for loop?
An iterator can be safe over many threads, while a for loop cannot because it directly accesses elements.
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 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.
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 to cross object values among different kinds of objects.
Additionally, knowing another function of Python programming bring you more skills and understanding.