The following illustration helps us understand how the zip() function works by creating an iterator of tuples from two input lists, L1 and L2. – Python Docs How the zip() Function Creates an Iterator of Tuples With no arguments, it returns an empty iterator. With a single iterable argument, it returns an iterator of 1-tuples.Ĥ. The iterator stops when the shortest input iterable is exhausted.ģ. Returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables.Ģ. Make an iterator that aggregates elements from each of the iterables.ġ. Syntax: zip(*iterables) – the zip() function takes in one or more iterables as arguments. Let's start by looking up the documentation for zip() and parse it in the subsequent sections.
Let's now see how Python's zip() function can help us iterate through multiple lists in parallel. You may not be accessing newly added items at all as they are at indices not currently in the range of accessed indices.You may run into Inde圎rrors as you're accessing items at indices that are no longer valid because the item at the index has been removed, or.# do something on list_1,list_2,list_3.,list_NĪs you might have guessed by now, this works as expected only when all the iterables contain the same number of items.Ĭonsider the case where one or more of the lists are updated – say, one list may have an item removed from it, and another may have an item added to it. And you create a range() object as shown below and use the index i to access the item at position i in each of the iterables. You know that all the lists – list_1, list_2., list_N – contain the same number of items. "If I know that all lists have the same number of items, can I not just use the index to tap into each of those lists, and pull out the item at the specified index?" You may think of using the range() object with the for loop. Why Using Python's range() Object is Not an Optimal Choice Always This is precisely what is called parallel iteration. We need to be able to access items at a particular index from both the lists. does this until it traverses the whole of list_1Ĭlearly, this isn't what we want.and loops through the whole of list_2 again, and.then accesses the second item in list_1,.then loops through list_2 accessing each item in list_2,.first taps into the first item in list_1,.Things may seem a bit difficult now, and the following approach won't work: # Example - 2 lists, list_1 and list_2 What if we had more than one list (or any iterable) ? Say, N lists – you may insert your favorite number in place of N. In simple terms, we tell the Python interpreter: " Hey there! Please loop through list_1 to access each item and do some operation on each item." The snippet below shows the general syntax: for item in list_1:
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How to Use the 'in' Operator in Python to Traverse Iterablesīefore we go ahead and learn about the zip() function, let's quickly revisit how we use the in operator with a for loop to access items in an iterable (lists, tuples, dictionaries, strings etc.). How to Use the zip_longest() Function in Python.What Happens When You Pass in One or No Iterable to the zip() Function?.What Happens When the Iterables are of Different Lengths?.How to Use Python's zip() Function - Try it Yourself!.How the zip() Function Creates an Iterator of Tuples.
Why Using Python's range() Object is Not an Optimal Choice Always.How to Use the 'in' Operator in Python to Traverse Iterables.In this tutorial, we'll use Python's zip() function to efficiently perform parallel iteration over multiple iterables. Have you ever needed to loop through multiple iterables in parallel when coding in Python?
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