An iterable is any Python object that can return an iterator. These objects implement the __iter__() method, which returns an iterator when called.
__iter__().for loop.iter(iterable) will return an iterator for that iterable.# A list is an iterable
my_list = [1, 2, 3]
for item in my_list: # Iterating over the iterable
print(item)In this example, my_list is an iterable because it can return an iterator that can be used in a for loop.
An iterator is an object that represents a stream of data. It implements the __iter__() and __next__() methods:
__iter__(): Returns the iterator object itself.__next__(): Returns the next value from the iterator. When there are no more items, it raises the StopIteration exception.An iterator remembers its state during iteration, meaning once a value has been accessed, it cannot be revisited without creating a new iterator.
# Getting an iterator from an iterable
my_list = [1, 2, 3]
my_iter = iter(my_list) # my_iter is an iterator
# Manually iterate using next()
print(next(my_iter)) # Output: 1
print(next(my_iter)) # Output: 2
print(next(my_iter)) # Output: 3
# The following will raise StopIteration
# print(next(my_iter))1
2
3In this example, my_iter is an iterator that returns one element of the list at a time when next() is called.
A generator is a special type of iterator that is defined using a function with the yield keyword. Generators allow you to generate values lazily, meaning values are produced only when requested, not all at once.
Generators are a type of iterator because they also implement the __iter__() and __next__() methods, but they are written in a simpler way, using yield.
yield instead of managing __iter__() and __next__() methods manually.# A generator function
def my_generator():
yield 1
yield 2
yield 3
gen = my_generator() # gen is a generator
# Iterate over the generator
for value in gen:
print(value)1
2
3In this example, the my_generator() function is a generator. It “yields” values one at a time and can be used like an iterator.
You can also create a generator using a generator expression, which is similar to a list comprehension but with parentheses:
# Generator expression
gen_exp = (x * x for x in range(3))
# Iterate over the generator expression
for value in gen_exp:
print(value) # Output: 0, 1, 4| Concept | Characteristics | Methods | Example Usage |
|---|---|---|---|
| Iterable | Any object you can iterate over (e.g., lists, strings, etc.). Produces an iterator when iter() is called. |
__iter__() |
Lists, sets, strings, dictionaries, etc. |
| Iterator | Object that represents a stream of data. Iterates once and keeps its state. | __iter__(), __next__() |
Result of calling iter() on an iterable. |
| Generator | A type of iterator created using a function with yield. Lazily produces values on demand. |
__iter__(), __next__() |
Generator functions or generator expressions. |
yield and is more memory-efficient because it generates values on the fly.In short: