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.
#!/usr/bin/python
def square(x):
return x * x
sqr_fun = lambda x: x * x
print(square(3))
print(sqr_fun(4))
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 9 16
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.
#!/usr/bin/python
nums = [1, 2, 3, 4, 5, 6]
nums_squared = map(lambda x: x * x, nums)
for num in nums_squared:
print(num)
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 1 4 9 16 25 36
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.
#!/usr/bin/python nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] nums_filtered = list(filter(lambda x: x % 2, nums)) print(nums_filtered)
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.
#!/usr/bin/python
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:
print(user)
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.
#!/usr/bin/python
from dataclasses import dataclass
@dataclass(frozen=True)
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)
print(n)
n = max(cars, key=lambda c: c.price)
print(n)
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) print(n) n = max(cars, key=lambda c: c.price) print(n)
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.
#!/usr/bin/python
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
self.initUI()
def initUI(self):
self.parent.title("Buttons")
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()
root.geometry("250x150+300+300")
app = Example(root)
root.mainloop()
if __name__ == '__main__':
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.
Source
Python lambdas - language reference
In this article we have worked with the Python lambda functions.
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