Python list comprehension counter

Iterating With for Loops in Python

A for loop in Python uses collection-based iteration. This means that Python assigns the next item from an iterable to the loop variable on every iteration, like in this example:

In this example, values is a list with three strings, "a", "b", and "c". In Python, lists are one type of iterable object. In the for loop, the loop variable is value. On each iteration of the loop, value is set to the next item from values.

Next, you print value onto the screen. The advantage of collection-based iteration is that it helps avoid the off-by-one error that is common in other programming languages.

Now imagine that, in addition to the value itself, you want to print the index of the item in the list to the screen on every iteration. One way to approach this task is to create a variable to store the index and update it on each iteration:

In this example, index is an integer that keeps track of how far into the list you are. On each iteration of the loop, you print index as well as value. The last step in the loop is to update the number stored in index by one. A common bug occurs when you forget to update index on each iteration:

In this example, index stays at 0 on every iteration because theres no code to update its value at the end of the loop. Particularly for long or complicated loops, this kind of bug is notoriously hard to track down.

Another common way to approach this problem is to use range() combined with len() to create an index automatically. This way, you dont need to remember to update the index:

In this example, len(values) returns the length of values, which is 3. Then range() creates an iterator running from the default starting value of 0 until it reaches len(values) minus one. In this case, index becomes your loop variable. In the loop, you set value equal to the item in values at the current value of index. Finally, you print index and value.

With this example, one common bug that can occur is when you forget to update value at the beginning of each iteration. This is similar to the previous bug of forgetting to update the index. This is one reason that this loop isnt considered Pythonic.

This example is also somewhat restricted because values has to allow access to its items using integer indices. Iterables that allow this kind of access are called sequences in Python.

Fortunately, Pythons enumerate() lets you avoid all these problems. Its a built-in function, which means that its been available in every version of Python since it was added in Python 2.3, way back in 2003.

Using Pythons enumerate()

You can use enumerate() in a loop in almost the same way that you use the original iterable object. Instead of putting the iterable directly after in in the for loop, you put it inside the parentheses of enumerate(). You also have to change the loop variable a little bit, as shown in this example:

When you use enumerate(), the function gives you back two loop variables:

1. The count of the current iteration
2. The value of the item at the current iteration

Just like with a normal for loop, the loop variables can be named whatever you want them to be named. You use count and value in this example, but they could be named i and v or any other valid Python names.

With enumerate(), you dont need to remember to access the item from the iterable, and you dont need to remember to advance the index at the end of the loop. Everything is automatically handled for you by the magic of Python!

Pythons enumerate() has one additional argument that you can use to control the starting value of the count. By default, the starting value is 0 because Python sequence types are indexed starting with zero. In other words, when you want to retrieve the first element of a list, you use index 0:

You can see in this example that accessing values with the index 0 gives the first element, a. However, there are many times when you might not want the count from enumerate() to start at 0. For instance, you might want to print a natural counting number as an output for the user. In this case, you can use the start argument for enumerate() to change the starting count:

In this example, you pass start=1, which starts count with the value 1 on the first loop iteration. Compare this with the previous examples, in which start had the default value of 0, and see whether you can spot the difference.

Practicing With Python enumerate()

You should use enumerate() anytime you need to use the count and an item in a loop. Keep in mind that enumerate() increments the count by one on every iteration. However, this only slightly limits your flexibility. Since the count is a standard Python integer, you can use it in many ways. In the next few sections, youll see some uses of enumerate().

Understanding Python enumerate()

In the last few sections, you saw examples of when and how to use enumerate() to your advantage. Now that youve got a handle on the practical aspects of enumerate(), you can learn more about how the function works internally.

To get a better sense of how enumerate() works, you can implement your own version with Python. Your version of enumerate() has two requirements. It should:

1. Accept an iterable and a starting count value as arguments
2. Send back a tuple with the current count value and the associated item from the iterable

One way to write a function meeting these specifications is given in the Python documentation:

my_enumerate() takes two arguments, sequence and start. The default value of start is 0. Inside the function definition, you initialize n to be the value of start and run a for loop over the sequence.

For each elem in sequence, you yield control back to the calling location and send back the current values of n and elem. Finally, you increment n to get ready for the next iteration. You can see my_enumerate() in action here:

First, you create a list of the four seasons to work with. Next, you show that calling my_enumerate() with seasons as the sequence creates a generator object. This is because you use the yield keyword to send values back to the caller.

Finally, you create two lists from my_enumerate(), one in which the start value is left as the default, 0, and one in which start is changed to 1. In both cases, you end up with a list of tuples in which the first element of each tuple is the count and the second element is the value from seasons.

Although you can implement an equivalent function for enumerate() in only a few lines of Python code, the actual code for enumerate() is written in C. This means that its super fast and efficient.

Unpacking Arguments With enumerate()

When you use enumerate() in a for loop, you tell Python to use two variables, one for the count and one for the value itself. Youre able to do this by using a Python concept called argument unpacking.

Argument unpacking is the idea that a tuple can be split into several variables depending on the length of the sequence. For instance, you can unpack a tuple of two elements into two variables:

First, you create a tuple with two elements, 10 and "a". Then you unpack that tuple into first_elem and second_elem, which are each assigned one of the values from the tuple.

When you call enumerate() and pass a sequence of values, Python returns an iterator. When you ask the iterator for its next value, it yields a tuple with two elements. The first element of the tuple is the count, and the second element is the value from the sequence that you passed:

In this example, you create a list called values with two elements, "a" and "b". Then you pass values to enumerate() and assign the return value to enum_instance. When you print enum_instance, you can see that its an instance of enumerate() with a particular memory address.

Then you use Pythons built-in next() to get the next value from enum_instance. The first value that enum_instance returns is a tuple with the count 0 and the first element from values, which is "a".

Calling next() again on enum_instance yields another tuple, this time with the count 1 and the second element from values, "b". Finally, calling next() one more time raises StopIteration since there are no more values to be returned from enum_instance.

When an iterable is used in a for loop, Python automatically calls next() at the start of every iteration until StopIteration is raised. Python assigns the value it retrieves from the iterable to the loop variable.

If an iterable returns a tuple, then you can use argument unpacking to assign the elements of the tuple to multiple variables. This is what you did earlier in this tutorial by using two loop variables.

Another time you might have seen argument unpacking with a for loop is with the built-in zip(), which allows you to iterate through two or more sequences at the same time. On each iteration, zip() returns a tuple that collects the elements from all the sequences that were passed:

By using zip(), you can iterate through first, second, and third at the same time. In the for loop, you assign the element from first to one, from second to two, and from third to three. Then you print the three values.

You can combine zip() and enumerate() by using nested argument unpacking:

In the for loop in this example, you nest zip() inside enumerate(). This means that each time the for loop iterates, enumerate() yields a tuple with the first value as the count and the second value as another tuple containing the elements from the arguments to zip(). To unpack the nested structure, you need to add parentheses to capture the elements from the nested tuple of elements from zip().

There are other ways to emulate the behavior of enumerate() combined with zip(). One method uses itertools.count(), which returns consecutive integers by default, starting at zero. You can change the previous example to use itertools.count():

Using itertools.count() in this example allows you to use a single zip() call to generate the count as well as the loop variables without nested argument unpacking.

Conclusion

Pythons enumerate() lets you write Pythonic for loops when you need a count and the value from an iterable. The big advantage of enumerate() is that it returns a tuple with the counter and value, so you dont have to increment the counter yourself. It also gives you the option to change the starting value for the counter.

In this tutorial, you learned how to:

• Use Pythons enumerate() in your for loops
• Apply enumerate() in a few real-world examples
• Get values from enumerate() using argument unpacking
• Implement your own equivalent function to enumerate()

You also saw enumerate() used in some real-world code, including within the CPython code repository. You now have the superpower of simplifying your loops and making your Python code stylish!