Python lambda functions

last modified January 29, 2024

In this article we shows how to create anonymous functions in Python. Anonymous functions in Python are created with lambda keyword.

Python lambda function

Python lambda functions, also known as anonymous functions, are inline functions that do not have a name. They are created with the lambda keyword. This is part of the functional paradigm built-in Python.

Python lambda functions are restricted to a single expression. They can be used wherever normal functions can be used.

Python lambda syntax

Python lambda has the following syntax:

z = lambda x: x * y

The statement creates an anonymous function with the lambda keyword. The function multiplies two values. The x is a parameter that is passed to the lambda function. The parameter is followed by a colon character. The code next to the colon is the expression that is executed when the lambda function is called. The lambda function is assigned to the z variable.

Python lambda function example

The following is a simple example demonstrating Python lambda function.


def square(x):

    return x * x

sqr_fun = lambda x: x * x


In the example, we have two functions that square a value.

def square(x):

    return x * x

This is a Python function defined with the def keyword. The function's name is square.

sqr_fun = lambda x: x * x

Here we define an anonymous, inline function with lambda. Note that the function does not have a name. The sqr_fun is a name of the variable that holds the created lambda function.

$ ./lambda_fun_simple.py

Python lambda function with map

Python lambda functions are useful with the map function. We can create more concise code. Python map is a built-in function which applies the given function on every item of iterable(s) and returns an iterator object.


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

nums_squared = map(lambda x: x * x, nums)

for num in nums_squared:

The example creates a little inline function for the map as a parameter. With the map function we apply the lambda function on each element of the list.

$ ./lambda_fun_map.py

Python lambda function with filter

Python lambda functions can be used with the filter function. The filter function constructs a list from those elements of the iterable for which the function returns true.


nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]

nums_filtered = list(filter(lambda x: x % 2, nums))


In the example, we filter the list of integers. The new list contains only odd integers.

nums_filtered = list(filter(lambda x: x % 2, nums))

The first parameter of the filter is the function which processes the list elements. The lambda function has the x % 2 expression, which returns true for odd values.

$ ./lambda_fun_filter.py
[1, 3, 5, 7, 9, 11]

Python lambda function with sort

Python lists have a built-in list.sort method that modifies the list in-place. The method has a key parameter to specify a function to be called on each list element prior to making comparisons. There we can use a lambda function.


users = [
  {'name': 'John Doe', 'date_of_birth': 1987},
  {'name': 'Jane Doe', 'date_of_birth': 1996},
  {'name': 'Robert Brown', 'date_of_birth': 1977},
  {'name': 'Lucia Smith', 'date_of_birth': 2002},
  {'name': 'Patrick Dempsey', 'date_of_birth': 1994}

users.sort(reverse=True, key=lambda e: e['date_of_birth'])

for user in users:

We have a list of user dictionaries. With the lambda function, we sort the users by their date of birth in the reverse order.

$ ./lambda_fun_sort.py
{'name': 'Lucia Smith', 'date_of_birth': 2002}
{'name': 'Jane Doe', 'date_of_birth': 1996}
{'name': 'Patrick Dempsey', 'date_of_birth': 1994}
{'name': 'John Doe', 'date_of_birth': 1987}
{'name': 'Robert Brown', 'date_of_birth': 1977}

Python lambda function with min and max

The next example uses the built-in min and max functions with lambda.


from dataclasses import dataclass

class Car:
    name: str
    price: int

cars = [
    Car("Audi", 52642), Car("Mercedes", 57127), Car("Skoda", 9000),
    Car("Volvo", 29000), Car("Bentley", 350000), Car("Citroen", 21000),
    Car("Hummer", 41400), Car("Volkswagen", 21601)

n = min(cars, key=lambda c: c.price)

n = max(cars, key=lambda c: c.price)

In the example, we have a list of car objects. We find out the cheapest and the most expensive cars.

n = min(cars, key=lambda c: c.price)

n = max(cars, key=lambda c: c.price)

The functions take the lambda function as the second parameter. The lambdas return the attribute of the object on which the min, max functions operate.

$ ./mmfun.py
Car(name='Skoda', price=9000)
Car(name='Bentley', price=350000)

Python lambda with Tkinter

Python lambda function can be used in GUI programming with Tkinter. It allows to create small, inline functions for the command parameter.


from tkinter import Tk, BOTH, messagebox
from tkinter.ttk import Frame, Button

class Example(Frame):

    def __init__(self, parent):
        Frame.__init__(self, parent)

        self.parent = parent


    def initUI(self):


        self.pack(fill=BOTH, expand=1)

        btn1 = Button(self, text="Button 1",
            command=lambda: self.onClick("Button 1"))
        btn1.pack(padx=5, pady=5)

        btn2 = Button(self, text="Button 2",
            command=lambda: self.onClick("Button 2"))
        btn2.pack(padx=5, pady=5)

        btn2 = Button(self, text="Button 3",
            command=lambda: self.onClick("Button 3"))
        btn2.pack(padx=5, pady=5)

    def onClick(self, text):

        messagebox.showinfo("Button label", text);

def main():

    root = Tk()
    app = Example(root)

if __name__ == '__main__':

We have three buttons that share one callback. The lambda function allows us to send specific data to the callback function. Each button displays its label in a message box.

btn1 = Button(self, text="Button 1",
    command=lambda: self.onClick("Button 1"))

We pass an anonymous function to the command parameter. We send the label of the button to the onClick callback.


Python lambdas - language reference

In this article we have worked with the Python lambda functions.


My name is Jan Bodnar and I am a passionate programmer with many years of programming experience. I have been writing programming articles since 2007. So far, I have written over 1400 articles and 8 e-books. I have over eight years of experience in teaching programming.

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