Lambda Functions in Python

A lambda is a small, one-line function with no name. It's handy when you need a quick function to pass to another function. Compare these two — they do exactly the same thing:

# A normal function
def double(x):
    return x * 2

# The same thing as a lambda
double = lambda x: x * 2

print(double(5))     # 10 either way

The lambda syntax is lambda arguments: expression. There's no return — the expression's value is returned automatically.

When are lambdas useful?

You rarely assign a lambda to a variable like above (a normal def is clearer for that). Lambdas shine when you pass a tiny function into another function. The most common case is the key argument of sorted():

students = [
    ("Asha", 85),
    ("Ravi", 72),
    ("Meena", 91),
]

# Sort by the second item (the score), highest first
ranked = sorted(students, key=lambda student: student[1], reverse=True)
print(ranked)
# [('Meena', 91), ('Asha', 85), ('Ravi', 72)]

Here the lambda tells sorted() what to sort by. Writing a separate named function for such a small job would be overkill.

Lambdas with map() and filter()

map() applies a function to every item; filter() keeps only items where the function returns True:

numbers = [1, 2, 3, 4, 5, 6]

# map: square every number
squares = list(map(lambda n: n ** 2, numbers))
print(squares)        # [1, 4, 9, 16, 25, 36]

# filter: keep only even numbers
evens = list(filter(lambda n: n % 2 == 0, numbers))
print(evens)          # [2, 4, 6]

Note that map() and filter() return special iterator objects, so we wrap them in list() to see the result.

Lambda with multiple arguments

A lambda can take more than one argument, separated by commas:

# A lambda that adds two numbers
add = lambda a, b: a + b
print(add(3, 4))      # 7

# Useful inside functions like sorted with a tuple key
words = ["banana", "apple", "fig", "cherry"]
# Sort by length, then alphabetically
words.sort(key=lambda w: (len(w), w))
print(words)          # ['fig', 'apple', 'banana', 'cherry']

A practical example

# Find the product with the lowest price

products = [
    {"name": "Pen", "price": 20},
    {"name": "Notebook", "price": 60},
    {"name": "Eraser", "price": 10},
]

# min() uses the lambda to compare by price
cheapest = min(products, key=lambda item: item["price"])
print(f"Cheapest: {cheapest['name']} at {cheapest['price']}")
# Cheapest: Eraser at 10

Common mistakes

• Trying to put statements in a lambda: A lambda can only hold a single expression — no if/else blocks, no loops, no assignments. If you need those, use a regular def.
• Overusing lambdas: Assigning a complex lambda to a variable hurts readability. If it's more than a trivial line, a named function is clearer and shows up better in error messages.
• Forgetting that map/filter need list(): print(map(...)) shows a map object, not the values. Wrap it in list().
• Confusing the syntax: It's lambda x: x + 1, with a colon and no parentheses around the parameter. No return keyword inside.
• Late binding in loops: Creating lambdas inside a loop that reference the loop variable can capture the wrong value. This is an advanced gotcha — use a default argument (lambda x, n=n: ...) if you hit it.

FAQ

What does "anonymous function" mean? A function without a name. A lambda is anonymous because you usually use it on the spot without giving it a permanent name.

Is a lambda faster than a normal function? No. Performance is the same. Lambdas are about convenience and conciseness, not speed.

Can I use an if-else in a lambda? Only the expression form: lambda x: "even" if x % 2 == 0 else "odd". You cannot use block statements.

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Lambdas build on what you learned in Functions in Python. They also pair beautifully with List Comprehensions in Python for transforming data. Explore more on the Python learning hub.

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