Item 8: Avoid More Than Two Expressions in List Comprehensions
Beyond basic usage (see Item 7: “Use List Comprehensions Instead of map and filter”), list comprehensions also support multiple levels of looping. For example, say you want to simplify a matrix (a list containing other lists) into one flat list of all cells. Here, I do this with a list comprehension by including two for expressions. These expressions run in the order provided from left to right.
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] flat = [x for row in matrix for x in row] print(flat) >>> [1, 2, 3, 4, 5, 6, 7, 8, 9]
The example above is simple, readable, and a reasonable usage of multiple loops. Another reasonable usage of multiple loops is replicating the two-level deep layout of the input list. For example, say you want to square the value in each cell of a two-dimensional matrix. This expression is noisier because of the extra  characters, but it’s still easy to read.
squared = [[x**2 for x in row] for row in matrix] print(squared) >>> [[1, 4, 9], [16, 25, 36], [49, 64, 81]]
If this expression included another loop, the list comprehension would get so long that you’d have to split it over multiple lines.
my_lists = [ [[1, 2, 3], [4, 5, 6]], # … ] flat = [x for sublist1 in my_lists for sublist2 in sublist1 for x in sublist2]
At this point, the multiline comprehension isn’t much shorter than the alternative. Here, I produce the same result using normal loop statements. The indentation of this version makes the looping clearer than the list comprehension.
flat =  for sublist1 in my_lists: for sublist2 in sublist1: flat.extend(sublist2)
List comprehensions also support multiple if conditions. Multiple conditions at the same loop level are an implicit and expression. For example, say you want to filter a list of numbers to only even values greater than four. These two list comprehensions are equivalent.
a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] b = [x for x in a if x > 4 if x % 2 == 0] c = [x for x in a if x > 4 and x % 2 == 0]
Conditions can be specified at each level of looping after the for expression. For example, say you want to filter a matrix so the only cells remaining are those divisible by 3 in rows that sum to 10 or higher. Expressing this with list comprehensions is short, but extremely difficult to read.
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] filtered = [[x for x in row if x % 3 == 0] for row in matrix if sum(row) >= 10] print(filtered) >>> [, ]
Though this example is a bit convoluted, in practice you’ll see situations arise where such expressions seem like a good fit. I strongly encourage you to avoid using list comprehensions that look like this. The resulting code is very difficult for others to comprehend. What you save in the number of lines doesn’t outweigh the difficulties it could cause later.
The rule of thumb is to avoid using more than two expressions in a list comprehension. This could be two conditions, two loops, or one condition and one loop. As soon as it gets more complicated than that, you should use normal if and for statements and write a helper function (see Item 16: “Consider Generators Instead of Returning Lists”).
Things to Remember
List comprehensions support multiple levels of loops and multiple conditions per loop level.
List comprehensions with more than two expressions are very difficult to read and should be avoided.