Python में Lambda Function: Syntax, Examples और कब Use करें
Lambda एक one-line anonymous function है: lambda arguments: expression. map(), filter(), sorted() के practical examples और lambda कब NOT use करें.
What is a lambda function?
A lambda is a small anonymous (nameless) function written in one line:
lambda arguments: expressionsquare = lambda x: x * x
print(square(5))
# exactly the same as:
def square(x):
return x * x25
Lambda with multiple arguments
add = lambda a, b: a + b
maximum = lambda a, b: a if a > b else b
fullname = lambda first, last: first + " " + last
print(add(10, 20))
print(maximum(45, 72))
print(fullname("Gagan", "Sharma"))30
72
Gagan Sharma
Where lambda actually shines: map(), filter(), sorted()
map() — apply to every item:
marks = [45, 60, 75, 90]
percent = list(map(lambda m: m / 100 * 100, marks))
doubled = list(map(lambda m: m * 2, marks))
print(doubled)[90, 120, 150, 180]
filter() — keep items that pass a test:
marks = [25, 60, 33, 90, 18]
passed = list(filter(lambda m: m >= 33, marks))
print(passed)[60, 33, 90]
sorted() with key — the most common real-world use:
students = [("Aman", 92), ("Priya", 88), ("Rahul", 95)]
by_marks = sorted(students, key=lambda s: s[1], reverse=True)
print(by_marks)[('Rahul', 95), ('Aman', 92), ('Priya', 88)]
When NOT to use lambda
- No multiple statements: lambda cannot contain if-blocks, loops, or several lines — only one expression.
- Complex logic: if you need to think twice to read it, write a normal
deffunction with a name. - Reuse: if the same logic is needed in 3 places, a named function is cleaner. PEP 8 even recommends not assigning lambdas to variables in real projects.
Interview summary
| Point | lambda | def function |
|---|---|---|
| Name | Anonymous | Named |
| Body | One expression only | Any number of statements |
| return | Automatic | Written explicitly |
| Best for | Short throwaway logic in map/filter/sorted | Everything else |
Lambda function क्या है?
Lambda एक छोटा anonymous (बिना नाम का) one-line function है:
lambda arguments: expressionsquare = lambda x: x * x
print(square(5))
# बिल्कुल यही:
def square(x):
return x * x25
Multiple arguments के साथ Lambda
add = lambda a, b: a + b
maximum = lambda a, b: a if a > b else b
fullname = lambda first, last: first + " " + last
print(add(10, 20))
print(maximum(45, 72))
print(fullname("Gagan", "Sharma"))30
72
Gagan Sharma
Lambda जहां असली काम आता है: map(), filter(), sorted()
map() — हर item पर apply:
marks = [45, 60, 75, 90]
doubled = list(map(lambda m: m * 2, marks))
print(doubled)[90, 120, 150, 180]
filter() — test pass करने वाले items रखें:
marks = [25, 60, 33, 90, 18]
passed = list(filter(lambda m: m >= 33, marks))
print(passed)[60, 33, 90]
sorted() with key — सबसे common real-world use:
students = [("Aman", 92), ("Priya", 88), ("Rahul", 95)]
by_marks = sorted(students, key=lambda s: s[1], reverse=True)
print(by_marks)[('Rahul', 95), ('Aman', 92), ('Priya', 88)]
Lambda कब NOT use करें
- Multiple statements नहीं: lambda में if-blocks, loops या कई lines नहीं आ सकतीं — सिर्फ एक expression.
- Complex logic: अगर पढ़ने के लिए दो बार सोचना पड़े, तो नाम वाला normal
deffunction लिखें. - Reuse: same logic 3 जगह चाहिए तो named function cleaner है. PEP 8 भी real projects में lambda को variable में assign न करने की सलाह देता है.
Interview summary
| Point | lambda | def function |
|---|---|---|
| Name | Anonymous | Named |
| Body | सिर्फ एक expression | कितने भी statements |
| return | Automatic | Explicitly लिखना होता है |
| Best for | map/filter/sorted में short logic | बाकी सब कुछ |
Frequently Asked Questions
Python में lambda function क्या है?
Lambda एक anonymous one-line function है जिसका syntax है lambda arguments: expression, जहां expression का result automatically return होता है.
क्या lambda में multiple statements हो सकते हैं?
नहीं. Lambda की body एक single expression होनी चाहिए — न loops, न कई lines. उससे ज़्यादा के लिए normal def function use करें.
Real code में lambda सबसे ज़्यादा कहां use होता है?
sorted(), min() और max() के key argument के रूप में, और map() व filter() के अंदर short one-time transformations के लिए.