Python Lambda Functions Syntax, Usage, Examples
What is a Lambda Function?
A lambda function is a small, anonymous function defined using the lambda keyword instead of def. Unlike regular functions, lambda functions don’t have a name and are generally used for short, throwaway operations.
Basic Syntax
The basic syntax of a lambda function in Python is:
lambda arguments: expression
A lambda function can take any number of arguments, but it must contain only a single expression. It returns the result of that expression automatically — no need to use the return keyword.
Example: Add Two Numbers
add = lambda x, y: x + y
print(add(5, 3))8Explanation:
lambda x, y:defines an anonymous function that takes two parameters:xandy.- The expression
x + yis evaluated and returned as the result of the function. - This lambda function is assigned to the variable
add, so you can call it like a regular function usingadd(5, 3). - When called with arguments 5 and 3, it returns
8, which is printed to the output.
Sorting with Lambda
Lambda functions are particularly useful when passed as arguments to higher-order functions. Consider the example below where we sort a list of tuples by the second element:
data = [(1, 4), (2, 1), (3, 9)]
sorted_data = sorted(data, key=lambda x: x[1])
print(sorted_data)[(2, 1), (1, 4), (3, 9)]Filtering with Lambda
Use lambda with filter() to select only even numbers from a list:
numbers = [1, 2, 3, 4, 5, 6]
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)[2, 4, 6]Mapping with Lambda
Apply a function to every element using map():
nums = [1, 2, 3, 4]
squares = list(map(lambda x: x**2, nums))
print(squares)[1, 4, 9, 16]When Should You Use Lambda?
- When the function is short and simple.
- When the function will not be reused elsewhere.
- When you need a function as an argument (e.g., in
map,filter,sorted).
When NOT to Use Lambda
Lambda functions come with limitations. Avoid them when:
- The logic inside is too complex.
- You want to reuse or debug the function later.
- You need statements (lambda only allows expressions).
Common Mistakes and Checks
- Only one expression is allowed. Statements like
if/else,try/except, andprint()inside lambda are not allowed unless used as expressions. - Readability matters. Just because you can use a lambda doesn’t mean you should. Avoid sacrificing clarity.
- Debugging is hard. Anonymous nature makes it difficult to trace errors.
Example: Conditional Expression in Lambda
max_func = lambda a, b: a if a > b else b
print(max_func(10, 20))20Lambda vs Regular Function
def add_def(x, y):
return x + y
add_lambda = lambda x, y: x + y
print(add_def(2, 3)) # Output: 5
print(add_lambda(2, 3)) # Output: 55
5How to Test and Verify
- Always start with small examples. Try printing the output after defining a lambda.
- Use
type()to confirm it's a function:print(type(lambda x: x)) - Compare behavior side-by-side with a regular function to understand what’s happening.
What is a Lambda Function?
A lambda function is a small, anonymous function defined using the lambda keyword instead of def. Unlike regular functions, lambda functions don’t have a name and are generally used for short, throwaway operations.
Basic Syntax
The basic syntax of a lambda function in Python is:
lambda arguments: expression
A lambda function can take any number of arguments, but it must contain only a single expression. It returns the result of that expression automatically — no need to use the return keyword.
Example: Add Two Numbers
add = lambda x, y: x + y
print(add(5, 3))8Explanation:
lambda x, y:defines an anonymous function that takes two parameters:xandy.- The expression
x + yis evaluated and returned as the result of the function. - This lambda function is assigned to the variable
add, so you can call it like a regular function usingadd(5, 3). - When called with arguments 5 and 3, it returns
8, which is printed to the output.
Sorting with Lambda
Lambda functions are particularly useful when passed as arguments to higher-order functions. Consider the example below where we sort a list of tuples by the second element:
data = [(1, 4), (2, 1), (3, 9)]
sorted_data = sorted(data, key=lambda x: x[1])
print(sorted_data)[(2, 1), (1, 4), (3, 9)]Filtering with Lambda
Use lambda with filter() to select only even numbers from a list:
numbers = [1, 2, 3, 4, 5, 6]
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(evens)[2, 4, 6]Mapping with Lambda
Apply a function to every element using map():
nums = [1, 2, 3, 4]
squares = list(map(lambda x: x**2, nums))
print(squares)[1, 4, 9, 16]When Should You Use Lambda?
- When the function is short and simple.
- When the function will not be reused elsewhere.
- When you need a function as an argument (e.g., in
map,filter,sorted).
When NOT to Use Lambda
Lambda functions come with limitations. Avoid them when:
- The logic inside is too complex.
- You want to reuse or debug the function later.
- You need statements (lambda only allows expressions).
Common Mistakes and Checks
- Only one expression is allowed. Statements like
if/else,try/except, andprint()inside lambda are not allowed unless used as expressions. - Readability matters. Just because you can use a lambda doesn’t mean you should. Avoid sacrificing clarity.
- Debugging is hard. Anonymous nature makes it difficult to trace errors.
Example: Conditional Expression in Lambda
max_func = lambda a, b: a if a > b else b
print(max_func(10, 20))20Lambda vs Regular Function
def add_def(x, y):
return x + y
add_lambda = lambda x, y: x + y
print(add_def(2, 3)) # Output: 5
print(add_lambda(2, 3)) # Output: 55
5How to Test and Verify
- Always start with small examples. Try printing the output after defining a lambda.
- Use
type()to confirm it's a function:print(type(lambda x: x)) - Compare behavior side-by-side with a regular function to understand what’s happening.
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