Python Lambda Functions
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What is a Lambda Function?
A lambda defines a small, unnamed function inline using the lambda keyword instead of def — it can take any number of arguments but is limited to a single expression, with no statements or multiple lines allowed.
Example: What is a Lambda Function?
square = lambda x: x * x
print(square(5))Lambdas with filter()
filter() keeps only the items from an iterable for which a given function returns True, and a lambda is the typical way to supply that test condition inline without defining a separate named function just for one use.
Example: Lambdas with filter()
numbers = [1, 2, 3, 4, 5, 6]
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)Lambdas with map()
map() applies a function to every item in an iterable and returns the transformed results; pairing it with a lambda lets you write a quick, throwaway conversion — like doubling every number in a list — without a full function definition.
Example: Lambdas with map()
numbers = [1, 2, 3]
doubled = list(map(lambda x: x * 2, numbers))
print(doubled)Lambdas with sorted()
Passing key=lambda x: x[1] to sorted() tells it to sort by a computed value rather than the item itself, which is essential when sorting tuples, dictionaries, or objects by something other than their natural order.
Example: Lambdas with sorted()
pairs = [(1, "b"), (2, "a")]
sorted_pairs = sorted(pairs, key=lambda x: x[1])
print(sorted_pairs)Lambdas vs Regular Functions
Lambdas are meant for short, single-expression logic; the moment you need a loop, error handling, or more than one statement, a regular def function is clearer and should be preferred over forcing that logic into a lambda.
Example: Lambdas vs Regular Functions
# Lambda: short, single expression
square = lambda x: x * x
# Regular function: clearer for multi-step logic
def square_verbose(x):
result = x * x
return result
print(square(4), square_verbose(4))Chapter Quiz — Complete all 9 topics to unlock
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