Python Lambda ExpressionsUse lambda expressions. Pass a lambda expressions to another method.
Lambda.Think of a tree. Each branch and leaf grows in a pattern. Suppose a tiny function (and many similar functions) constructed this tree.
In Pythonwe have higher-order procedures and the lambda keyword. We pass lambdas to other functions. Much like a tree grows we build a program in little parts.
In this program,two lambdas are created. The first is called "square" and it receives one argument "n" and returns "n * n". The second is called "cube".
Square: This method receives one value. It returns the value multiplied by itself.
Cube: This method too receives one value. It returns the value cubed (with an exponent of 3).
Syntax: Lambda expression syntax uses the lambda keyword. The arguments are specified after.
|Python program that uses lambda argument def apply(f, n): print(f(n)) # Create two lambdas. square = lambda n: n * n cube = lambda n: n * n * n # Pass lambdas to apply method. apply(square, 4) apply(cube, 3) Output 16 27|
Lambda usage.Here we define a lambda that receives no arguments. It simply returns an expression. Here it returns the sum of the numbers 1, 2 and 3 (which is 6).
Variable: We can assign a variable to a lambda expression and then invoke the lambda with parentheses. We call it like any other function.
Here: To get the value 6 in this program, we invoke x. We then print the value it returns (stored in y).
So: Lambdas can be passed to other methods. They can be stored in variables. And those variables can be called like methods.
|Python program that uses lambda, no arguments # Assign variable to lambda expression. x = lambda: sum(range(1, 4)) # Invoke lambda expression. y = x() print(y) Output 6|
None.Many statements, like print(), return None. This is a valid return value for a lambda. We can specify a lambda with side effects, and a None return value.NonePrint
|Python program that uses None, lambda # This lambda has a side effect. # ... Print returns None. p = lambda x: print(x) p("Hello") p("World") Output Hello World|
Nested.A lambda can call another. This can simplify complex computations—we assign names to parts of a computation. The order the lambdas appear in the file does not matter.
With nested lambdas: Recursion can occur. This may result in a RuntimeError: maximum recursion depth exceeded error.
|Python program that uses lambda in lambda add_two = lambda n: n + 2 multiply_add_two = lambda n: add_two(n * 2) # Call lambda in lambda. print(multiply_add_two(3)) print(multiply_add_two(5)) Output 8 12|
Limitations.The lambda syntax in Python has serious limitations. But these limitations make sense. You cannot have multiple statements in a lambda expression.
Tip: If you want many statements, please instead use a def. For complex or involved methods, def is a better option.Def
Concepts.A lambda is an expression of behavior. It is a small function meant to do a well-defined task. We have no need to write an entire program in lambda syntax.
And: Lambda supplements, but does not replace, the def method syntax. It should be used when it improves clarity.
Greek letter: The word "lambda" is simply the name of a letter in the Greek alphabet. It is similar to the letter "L."
Performance research.In some languages lambdas cause performance loss. In the Python documentation I found that lambdas should not cause this problem. They behave just like def methods.
Quote: The expression lambda yields a function object. The unnamed object behaves like a function object defined with [def].Expressions: python.org
Performance.Here we test lambda performance. The square() method above is rewritten in the def method syntax. We then benchmark the methods against each other.
First: The program tests the performance of the def method call. We call it ten million times.
Second: The program times the lambda expression method call. We also call it ten million times.
Note: The results show that methods written with the def keyword and with the lambda keyword are close in performance.
|Python program that times lambda expressions import time # Method. def square1(n): return n ** 2 # Lambda method. square2 = lambda n: n ** 2 print(time.time()) # Use def method. i = 0 while i < 10000000: square1(1) i += 1 print(time.time()) # Use lambda method. i = 0 while i < 10000000: square2(1) i += 1 print(time.time()) Output 1346613154.399 1346613158.919 (Def = 4.52 s) 1346613163.397 (Lambda = 4.48 s)|
Macros.In older languages like C a macro is an easy way to combine code statements. It reduces repetitive typing. A lambda can be used in this way.
Here: We use a lambda X to combine two string method calls. This is like a macro for those invocations. Typing is reduced.
|Python program that uses lambda as macro line1 = "A cat, a dog " line2 = " a bird, a mountain" # Use X as an alias for two methods. x = lambda s: s.strip().upper() # Call the lambda to shorten the program's source. line1b = x(line1) line2b = x(line2) print(line1b) print(line2b) Output A CAT, A DOG A BIRD, A MOUNTAIN|
Avoiding lambda.Sometimes developers use a lambda with one argument and one result, but the lambda is not needed. Here we can use a function name (like math.sqrt) instead of a lambda.
And: When we avoid the lambda, the code becomes clearer and shorter. The lambda does not add much in this case.
Note: Sometimes a program can benefit from lambda when the lambda increases the "symmetry" of the program—other places also use lambda.
|Python program that avoids lambda when possible import math values = [10, 20, 30] # Apply sqrt to all elements in the list with map. result1 = map(math.sqrt, values) # We can use a lambda, but it is not needed. result2 = map(lambda x: math.sqrt(x), values) print("values:", values) print("math.sqrt:", list(result1)) print("lambda:", list(result2)) Output values: [10, 20, 30] math.sqrt: [3.1622776601683795, 4.47213595499958, 5.477225575051661] lambda: [3.1622776601683795, 4.47213595499958, 5.477225575051661]|
A summary.Function objects provide many possibilities. We specify these objects with the lambda syntax form. And when we pass them to other functions, we develop higher-order procedures.
In functional programming,we construct functions that act on other functions. We emphasize less the order of statements and loops. We focus on the input, and output, of functions.
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