Python lambda functions and when to use them

Lambda Functions

A lambda is a single-expression anonymous function. It returns the expression's value implicitly. Use it for short, throwaway functions — not for anything requiring multiple lines or a docstring.

square = lambda x: x ** 2
print(square(5))  # 25

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

With sort, map, filter

people = [("Alice", 30), ("Bob", 25), ("Charlie", 35)]

# sort by age
people.sort(key=lambda p: p[1])
print(people)  # [('Bob', 25), ('Alice', 30), ('Charlie', 35)]

# map: apply function to every element
nums = [1, 2, 3, 4]
doubled = list(map(lambda x: x * 2, nums))
# [2, 4, 6, 8]

# filter: keep elements where function is True
evens = list(filter(lambda x: x % 2 == 0, nums))
# [2, 4]

When NOT to Use Lambda

If you find yourself writing a complex lambda or assigning it to a variable and reusing it, write a named function instead. PEP 8 explicitly discourages assigning lambdas to names. Prefer list comprehensions over map/filter with lambdas for clarity.

Lambdas are most appropriate as inline one-off callbacks — the key= argument in sorting, the default= argument in certain APIs, or simple transformations passed to map and filter. If you need the logic more than once, give it a name. The functools.reduce function takes a binary function and folds a sequence into a single value — useful occasionally, but explicit loops are usually clearer. Python emphasises readability over cleverness; a three-line function with a descriptive name beats a one-liner nobody can parse on first read.