Lambda, map, filter, reduce

Tiny anonymous functions and the functional trio for reshaping data

Big idea: A lambda is a small, unnamed function you write in a single line. map, filter and reduce are higher-order functions — they take another function and apply it across a whole sequence to transform it, select from it, or fold it into one value.

By the end you will be able to:

write a lambda and know when it is (and is not) worth it,
transform every item of a sequence with map,
keep only the items you want with filter,
fold a sequence into a single value with functools.reduce,
weigh the readability trade-off against a comprehension or a plain loop.

1. What is a lambda?

A lambda is an anonymous function: a function with no name, defined inline where you need it. The syntax is the keyword lambda, then parameters, a colon, and one expression whose value is returned automatically.

double = lambda x: x * 2
print(double(5))     # 10

That lambda is exactly equivalent to this named function:

def double(x):
    return x * 2

A lambda may take several parameters, separated by commas:

add = lambda a, b: a + b
print(add(3, 4))     # 7

A lambda holds exactly one expression. There is no return keyword (the result is returned for you), and you cannot put assignments, loops, or multiple statements inside. When you need those, use def.

2. map: transform every item

map(function, iterable) applies function to each item and yields the results. In Python 3 it returns a lazy iterator (a map object), so you usually wrap it in list() to see the values.

nums = [1, 2, 3, 4]
squares = list(map(lambda n: n * n, nums))
print(squares)       # [1, 4, 9, 16]

The function does not have to be a lambda — any callable works, including built-ins:

prices = ["10", "25", "7"]
as_int = list(map(int, prices))
print(as_int)        # [10, 25, 7]

map can walk several iterables at once; the function then receives one argument from each:

a = [1, 2, 3]
b = [10, 20, 30]
sums = list(map(lambda x, y: x + y, a, b))
print(sums)          # [11, 22, 33]

Lambda, map, filter, reduce