Python is known for its elegant syntax and powerful features that make programming intuitive and efficient. One of these features is iterators, which provide a way to access elements of a collection (like lists or tuples) sequentially without exposing the underlying structure. This article delves into what iterators are, how they work, and how you can create your own.
What is an Iterator?
An iterator in Python is an object that implements the iterator protocol, which consists of two methods:
-
__iter__()— Returns the iterator object itself. -
__next__()— Returns the next value from the iterator. RaisesStopIterationwhen there are no more items.
Any object that has these two methods is considered an iterator.
Example:
numbers = [1, 2, 3]
iterator = iter(numbers)
print(next(iterator)) # Output: 1
print(next(iterator)) # Output: 2
print(next(iterator)) # Output: 3
print(next(iterator)) # Raises StopIteration
Iterables vs Iterators
These terms are often used interchangeably but are fundamentally different:
-
Iterable: Any object capable of returning its members one at a time, e.g., lists, strings, tuples. It implements
__iter__()but not necessarily__next__(). -
Iterator: An object that keeps state and produces the next value when you call
next().
lst = [10, 20, 30]
iter_obj = iter(lst)
print(hasattr(lst, '__iter__')) # True (Iterable)
print(hasattr(lst, '__next__')) # False
print(hasattr(iter_obj, '__next__')) # True (Iterator)
How for-Loops Use Iterators
Python's for loop internally uses the iter() and next() functions. Here’s how:
for element in [1, 2, 3]:
print(element)
is internally equivalent to:
iterator = iter([1, 2, 3])
while True:
try:
item = next(iterator)
print(item)
except StopIteration:
break
Creating Your Own Iterator
To create a custom iterator, define a class with __iter__() and __next__() methods.
Example: Countdown Iterator
class Countdown:
def __init__(self, start):
self.current = start
def __iter__(self):
return self
def __next__(self):
if self.current <= 0:
raise StopIteration
else:
self.current -= 1
return self.current + 1
for num in Countdown(5):
print(num)
Output:
5
4
3
2
1
Generator vs Iterator
Generators are a simpler way to create iterators using the yield statement.
Example:
def countdown(n):
while n > 0:
yield n
n -= 1
for number in countdown(5):
print(number)
This generator function automatically creates an iterator and maintains state.
Advantages of Iterators
-
Memory Efficient: Processes items one at a time, especially useful for large datasets.
-
Lazy Evaluation: Items are computed as needed.
-
Composable: Can be easily chained and combined using tools like
itertools.
Common Iterator Tools
Python’s itertools module offers powerful tools for iterators.
Examples:
-
count(start, step): Infinite counter -
cycle(iterable): Infinite cycle through iterable -
chain(iter1, iter2): Combines multiple iterables
import itertools
for i in itertools.islice(itertools.count(10, 2), 5):
print(i) # 10, 12, 14, 16, 18
Handling StopIteration Gracefully
When creating custom iterators, always raise StopIteration when done. However, from Python 3.3+, using return in a generator automatically raises StopIteration.
def numbers():
yield 1
yield 2
return
Conclusion
Iterators are a cornerstone of Python’s elegant design, enabling powerful and memory-efficient programming patterns. Understanding how to use and implement iterators allows you to work more effectively with collections and custom data streams.
Whether you’re working with built-in sequences or designing your own classes, iterators give you fine-grained control over data traversal.
Tips and Tricks
What is pass in Python?
Python | Pass Statement
The pass statement is used as a placeholder for future code. It represents a null operation in Python. It is generally used for the purpose of filling up empty blocks of code which may execute during runtime but has yet to be written.
def myfunction():
pass
How can you generate random numbers?
Python | Generate random numbers
Python provides a module called random using which we can generate random numbers. e.g: print(random.random())
We have to import a random module and call the random() method as shown below:
import random
print(random.random())
The random() method generates float values lying between 0 and 1 randomly.
To generate customized random numbers between specified ranges, we can use the randrange() method
Syntax: randrange(beginning, end, step)
import random
print(random.randrange(5,100,2))
What is lambda in Python?
Python | Lambda function
A lambda function is a small anonymous function. This function can have any number of parameters but, can have just one statement.
Syntex:
lambda arguments : expression
a = lambda x,y : x+y
print(a(5, 6))
It also provides a nice way to write closures. With that power, you can do things like this.
def adder(x):
return lambda y: x + y
add5 = adder(5)
add5(1) #6
As you can see from the snippet of Python, the function adder takes in an argument x and returns an anonymous function, or lambda, that takes another argument y. That anonymous function allows you to create functions from functions. This is a simple example, but it should convey the power lambdas and closures have.
What is swapcase() function in the Python?
Python | swapcase() Function
It is a string's function that converts all uppercase characters into lowercase and vice versa. It automatically ignores all the non-alphabetic characters.
string = "IT IS IN LOWERCASE."
print(string.swapcase())
How to remove whitespaces from a string in Python?
Python | strip() Function | Remove whitespaces from a string
To remove the whitespaces and trailing spaces from the string, Python provides a strip([str]) built-in function. This function returns a copy of the string after removing whitespaces if present. Otherwise returns the original string.
string = " Python "
print(string.strip())
What is the usage of enumerate() function in Python?
Python | enumerate() Function
The enumerate() function is used to iterate through the sequence and retrieve the index position and its corresponding value at the same time.
lst = ["A","B","C"]
print (list(enumerate(lst)))
#[(0, 'A'), (1, 'B'), (2, 'C')]
Can you explain the filter(), map(), and reduce() functions?
Python | filter(), map(), and reduce() Functions
- filter() function accepts two arguments, a function and an iterable, where each element of the iterable is filtered through the function to test if the item is accepted or not.
>>> set(filter(lambda x:x>4, range(7))) # {5, 6}
-
map() function calls the specified function for each item of an iterable and returns a list of result
>>> set(map(lambda x:x**3, range(7))) # {0, 1, 64, 8, 216, 27, 125}
-
reduce() function reduces a sequence pair-wise, repeatedly until we arrive at a single value..
>>> reduce(lambda x,y:y-x, [1,2,3,4,5]) # 3Let’s understand this:
2-1=1
3-1=2
4-2=2
5-2=3Hence, 3.
What is a namedtuple?
Python | namedtuple
A namedtuple will let us access a tuple’s elements using a name/label. We use the function namedtuple() for this, and import it from collections.
>>> from collections import namedtuple
#format
>>> result=namedtuple('result','Physics Chemistry Maths')
#declaring the tuple
>>> Chris=result(Physics=86,Chemistry=92,Maths=80)
>>> Chris.Chemistry
# 92
Write a code to add the values of same keys in two different dictionaries and return a new dictionary.
We can use the Counter method from the collections module
from collections import Counter
dict1 = {'a': 5, 'b': 3, 'c': 2}
dict2 = {'a': 2, 'b': 4, 'c': 3}
new_dict = Counter(dict1) + Counter(dict2)
print(new_dict)
# Print: Counter({'a': 7, 'b': 7, 'c': 5})
Python In-place swapping of two numbers
Python | In-place swapping of two numbers
>>> a, b = 10, 20
>>> print(a, b)
10 20
>>> a, b = b, a
>>> print(a, b)
20 10
Reversing a String in Python
Python | Reversing a String
>>> x = 'PythonWorld'
>>> print(x[: : -1])
dlroWnohtyP
Python join all items of a list to convert into a single string
Python | Join all items of a list to convert into a single string
>>> x = ["Python", "Online", "Training"]
>>> print(" ".join(x))
Python Online Training
python return multiple values from functions
Python | Return multiple values from functions
>>> def A():
return 2, 3, 4
>>> a, b, c = A()
>>> print(a, b, c)
2 3 4
Python Print String N times
Python | Print String N times
>>> s = 'Python'
>>> n = 5
>>> print(s * n)
PythonPythonPythonPythonPython
Python check the memory usage of an object
Python | Check the memory usage of an object
>>> import sys
>>> x = 100
>>> print(sys.getsizeof(x))
28
