Diary of a Devman: June 2021

Generally, we all iterate through a variety of objects in Python, like:

Tuples

	t = ('apple', 'banana', 'orange')

	for fruit in t:
	print(fruit)

view raw iteration_tuple.py hosted with ❤ by GitHub

Lists

	l = ['apple', 'banana', 'orange']

	for fruit in l:
	print(fruit)

view raw iteration_list.py hosted with ❤ by GitHub

Dictionaries

	d = {'apple': 400, 'banana': 850, 'orange': 660}

	# Without items() method, the iteration over dict 'd', it's on its keys, only.
	for fruit in d:
	print(fruit)

view raw iteration_dictionary.py hosted with ❤ by GitHub

Strings

	s = 'apple'

	for letter in s:
	print(letter)

view raw iteration_string.py hosted with ❤ by GitHub

Sets

	s = {"apple", "banana", "orange", "coconut", "mango"}

	# set data structure is unordered. Therefore, the order in which
	# the data is displayed by the iteration, is different
	# of how it's initially defined.
	#
	# For more information: https://docs.python.org/3/tutorial/datastructures.html#sets
	for fruit in s:
	print(fruit)

view raw iteration_set.py hosted with ❤ by GitHub

But besides theses objects, you can create your own iterable object! Cool huh?

Not that often you might run on this situation, but it's good to know how to build your own iterator and also, you will learn a bit more of Python internals and how the iteration works behind the curtains.

The iter and next methods

Data structure objects like the ones listed above, are all iterable objects. You can get an iterator for any of them, by using the iter() method, and then iterating over it with next() method. If all elements from the iterator were called, then a StopIteration exception will be thrown.

	t = ('apple', 'banana', 'orange')

	# From Python documentation:
	# iter() : Get an iterator from an object.
	t_iter = iter(t)

	print(next(t_iter))
	print(next(t_iter))
	print(next(t_iter))
	print(next(t_iter))


	# [Output]
	#
	# $ python3 iterable.py
	# apple
	# banana
	# orange
	# Traceback (most recent call last):
	# File "iterable.py", line 8, in <module>
	# print(next(t_iter))
	# StopIteration

view raw iteration_iter.py hosted with ❤ by GitHub

Your Iterator

Built as class, your iterator should have __iter__() and __next__() methods implemented: one for initializing your iterator object, and the other for providing the current iterator value, also calculating the next iteration:

	class MyIterator:

	def __iter__(self):
	self.a = 1
	return self

	def __next__(self):
	x = self.a
	self.a += 1
	return x


	obj = MyIterator()
	my_iter = iter(obj)

	print(next(my_iter))
	print(next(my_iter))
	print(next(my_iter))
	print(next(my_iter))
	print(next(my_iter))

view raw iteration_iter_custom.py hosted with ❤ by GitHub

The problem here is that, without a condition, this iteration can go forever:

	class MyIterator:

	def __iter__(self):
	self.a = 1
	return self

	def __next__(self):
	x = self.a
	self.a += 1
	return x


	obj = MyIterator()
	my_iter = iter(obj)

	for i in my_iter:
	print(i)
	if i == 10:
	print("This iteration will go forever if we don't stop it...")
	break

view raw iteration_iter_custom_loop.py hosted with ❤ by GitHub

Depending on your code, you might want to have a condition externally expressed, but most of the cases, the condition of how many interations will be supported by the iterator, are defined on the class which provides the iterator.

Max Number of Iterations

Just as any class, you can define the __init__() method for the iterator class, where you can define the limit of the iterator:

	class MyIterator:

	def __init__(self, limit):
	self.limit = limit

	def __iter__(self):
	self.a = 1
	return self

	def __next__(self):
	if self.a <= self.limit:
	x = self.a
	self.a += 1
	return x
	else:
	raise StopIteration


	obj = MyIterator(10)
	my_iter = iter(obj)

	for x in my_iter:
	print(f"Step: {x}")

view raw iterable_custom_loop_limit.py hosted with ❤ by GitHub

Final Words

Hope you had fun while reviewing this topic and hope that it might help you some day. I decided to write it here, for I went thtough some situation where implementing an iterator was necessary, and here's a record of something that I initially tried, in order to understand how to build one.

From now on, everytime that you iterate through an iterable object, you can have an idea of what's going on with this object, how the data is being processed, stored, and understand that, there might be very specific scenarios where you would like to implement your own iterator.

For more examples and resources, here's a cool document from Python official documentation.

Iterators: brief words about them