list basics in python

Lists in Python are similar to arrays, though there are some idiosyncrasies to how the methods work in Python (at least relative to Javascript).

Manipulating List Contents

Python replaces the push method with append, and though pop is still present, it can take a positional argument.

There’s also a remove method in Python which takes an element’s value and removes the first instance found (and an error otherwise).

>>> my_list = []
>>> my_list.append('bear')
>>> my_list.append('lion')
>>> my_list.append('cat')
>>> my_list.append('elephant')
>>> my_list
['bear', 'lion', 'cat', 'elephant']
>>> my_list.pop(3)
'elephant'
>>> my_list
['bear', 'lion', 'cat']
>>> my_list.remove('lion')
>>> my_list
['bear', 'cat']

Sorting Lists

In Python, there’s both a list.sort() method as well as a sorted(). The latter can take any iterable (lists, dictionaries, etc.).

The biggest difference between list.sort() and sorted() is that the former is in place and slightly more efficient - though being in place means you will lose the original list.

Sorting in Python is stable and leverages the Timsort algorithm, “a hybrid stable sorting algorithm, derived from merge sort and insertion sort.”¹

The Python documentation covers several interesting sorting examples - beyond the basics. Included are:

1. multi / complex sorts
2. use of lambdas
3. item and attribute getters

Counting A List

To find the number of elements in a list, we have len and the occurrences of an item, we have list.count().

For example:

>>> my_list = ['cat','bear','dog','dog','elephant']
>>> my_list
['cat', 'bear', 'dog', 'dog', 'elephant']
>>> len(my_list)
5
>>> my_list.count('dog')
2

Slicing Lists

Slicing can be used to retrieve portions of an existing list or mutate a list.

For example:

>>> a = [1,2,3,4,5,6,7,8,9]
>>> a[4:7] # starts at the 4th index and continues to the 7th, though the end is not included
[5, 6, 7]
>>> a[3:] # the end index is not included, so we continue to the end
[4, 5, 6, 7, 8, 9]
>>> a[:3] # the start index is not included, so we start at 0.
[1, 2, 3]
>>> a[-4:-2] # negatives also work, here we're starting at the fourth to the end and continuing ot the second to the end
[6, 7]
>>> a[2:5] = [103, 104, 105] # we can also replace values with slices
>>> a
[1, 2, 103, 104, 105, 6, 7, 8, 9]
>>> a[2:5] = [1002] # the replacements can be of different sizes
>>> a
[1, 2, 1002, 6, 7, 8, 9]
>>> a[3] = [67, 78] # though going the other way will create a nested list
>>> a
[1, 2, 1002, [67, 78], 7, 8, 9]

Combining Two Lists

Combining two lists is as easy as using the .extend method:

>>> a = [1,2,3,4,5]
>>> b = [6,7,8,9,10]
>>> a.extend(b)
>>> a
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> b
[2, 3, 4, 5]

This is similar to using the spread parameter in Javascript, e.g., a = [...a, ...b], that is, it mutates the original list a (though not b).

Wrap Up

Python lists are very interesting, and this is only a smattering of the use cases. There are other methods that are useful like clear, reverse, and copy. See the docs for more on those and other useful tips - like list comprehension!

It’s worth noting that the Python community seems to be much comfortable with mutating in place than what I grew accustomed to within the React community where reducers were an important concept for managing state transformations.

Footnotes

• ¹ For more on the Timsort algorithm, see Wikipedia.