Using the Python zip() Function for Parallel Iteration

Using the Python zip() Function for Parallel Iteration

by Leodanis Pozo Ramos basics python
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Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Parallel Iteration With Python's zip() Function

Python’s zip() function creates an iterator that will aggregate elements from two or more iterables. You can use the resulting iterator to quickly and consistently solve common programming problems, like creating dictionaries. In this tutorial, you’ll discover the logic behind the Python zip() function and how you can use it to solve real-world problems.

By the end of this tutorial, you’ll learn:

  • How zip() works in both Python 3 and Python 2
  • How to use the Python zip() function for parallel iteration
  • How to create dictionaries on the fly using zip()

Understanding the Python zip() Function

zip() is available in the built-in namespace. If you use dir() to inspect __builtins__, then you’ll see zip() at the end of the list:

Python 
>>> dir(__builtins__)
['ArithmeticError', 'AssertionError', 'AttributeError', ..., 'zip']

You can see that 'zip' is the last entry in the list of available objects.

According to the official documentation, Python’s zip() function behaves as follows:

Returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The iterator stops when the shortest input iterable is exhausted. With a single iterable argument, it returns an iterator of 1-tuples. With no arguments, it returns an empty iterator. (Source)

You’ll unpack this definition throughout the rest of the tutorial. As you work through the code examples, you’ll see that Python zip operations work just like the physical zipper on a bag or pair of jeans. Interlocking pairs of teeth on both sides of the zipper are pulled together to close an opening. In fact, this visual analogy is perfect for understanding zip(), since the function was named after physical zippers!

Using zip() in Python

Python’s zip() function is defined as zip(*iterables). The function takes in iterables as arguments and returns an iterator. This iterator generates a series of tuples containing elements from each iterable. zip() can accept any type of iterable, such as files, lists, tuples, dictionaries, sets, and so on.

Passing n Arguments

If you use zip() with n arguments, then the function will return an iterator that generates tuples of length n. To see this in action, take a look at the following code block:

Python 
>>> numbers = [1, 2, 3]
>>> letters = ['a', 'b', 'c']
>>> zipped = zip(numbers, letters)
>>> zipped  # Holds an iterator object
<zip object at 0x7fa4831153c8>
>>> type(zipped)
<class 'zip'>
>>> list(zipped)
[(1, 'a'), (2, 'b'), (3, 'c')]

Here, you use zip(numbers, letters) to create an iterator that produces tuples of the form (x, y). In this case, the x values are taken from numbers and the y values are taken from letters. Notice how the Python zip() function returns an iterator. To retrieve the final list object, you need to use list() to consume the iterator.

If you’re working with sequences like lists, tuples, or strings, then your iterables are guaranteed to be evaluated from left to right. This means that the resulting list of tuples will take the form [(numbers[0], letters[0]), (numbers[1], letters[1]),..., (numbers[n], letters[n])]. However, for other types of iterables (like sets), you might see some weird results:

Python 
>>> s1 = {2, 3, 1}
>>> s2 = {'b', 'a', 'c'}
>>> list(zip(s1, s2))
[(1, 'a'), (2, 'c'), (3, 'b')]

In this example, s1 and s2 are set objects, which don’t keep their elements in any particular order. This means that the tuples returned by zip() will have elements that are paired up randomly. If you’re going to use the Python zip() function with unordered iterables like sets, then this is something to keep in mind.

Passing No Arguments

You can call zip() with no arguments as well. In this case, you’ll simply get an empty iterator:

Python 
>>> zipped = zip()
>>> zipped
<zip object at 0x7f196294a488>
>>> list(zipped)
[]

Here, you call zip() with no arguments, so your zipped variable holds an empty iterator. If you consume the iterator with list(), then you’ll see an empty list as well.

You could also try to force the empty iterator to yield an element directly. In this case, you’ll get a StopIteration exception:

Python 
>>> zipped = zip()
>>> next(zipped)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

When you call next() on zipped, Python tries to retrieve the next item. However, since zipped holds an empty iterator, there’s nothing to pull out, so Python raises a StopIteration exception.

Passing One Argument

Python’s zip() function can take just one argument as well. The result will be an iterator that yields a series of 1-item tuples:

Python 
>>> a = [1, 2, 3]
>>> zipped = zip(a)
>>> list(zipped)
[(1,), (2,), (3,)]

This may not be that useful, but it still works. Perhaps you can find some use cases for this behavior of zip()!

As you can see, you can call the Python zip() function with as many input iterables as you need. The length of the resulting tuples will always equal the number of iterables you pass as arguments. Here’s an example with three iterables:

Python 
>>> integers = [1, 2, 3]
>>> letters = ['a', 'b', 'c']
>>>