3 Python list comprehension tricks you might not know yet

List comprehensions aren’t just for lists

If you’ve used Python you’re probably familiar with the list comprehension syntax.

If you start with a list like this one:

>>> words = ['goodbye', 'cruel', 'world']

You can create a new list like this:

>>> lengths = [len(x) for x in words]
[7, 5, 5]

Compare that to appending items to an empty list.

# Not the pythonic way!
lengths = []
for word in words:
    lengths.append(len(word))

Creating lists using list comprehension is more pythonic and easier to read.

But did you know that you can create other types of objects with the same technique?

List comprehensions aren’t just for lists.

We’ll show you 3 tricks that you might not be using yet. They’ll help make your code easier to read, and easier to write.

1. Dictionary comprehension

You can also create dictionaries using the same list comprehension syntax.

>>> data = {word: len(word) for word in words}
{"goodbye": 7, "cruel": 5, "world": 5}

Notice that the key word and its value len(word) are separated with a colon :.

That means you need to use word: len(word) and not word, len(word), which would be a syntax error.

Bonus: another useful trick for creating dictionaries is to zip two lists together.

>>> words = ["hello", "old", "friend"]
>>> lengths = [len(word) for word in words]
>>> data = dict(zip(words, lengths))
{"hello": 5, "old": 3, "friend": 6}

2. Filtering

You can filter the items that are included.

>>> words = ['deified', 'radar', 'guns']
>>> palindromes = [word for word in words if word == word[::-1]]
['deified', 'radar']

Filtering works for dictionaries comprehensions, too.

>>> words = ["not", "on", "my", "watch"]
>>> data = {w: w[::-1] for w in words if len(w) < 5}
{'not': 'ton', 'on': 'no', 'my': 'ym'}