Python Features: Lambda function - Simple one-time function
Today I am gonna show you lambda function, also know as anonymous function. When we need to build some simple, one-time function, it is the show time of lambda function.
Through this article, you will learn how to create and use lambda functions and see how useful they can be.
Let’s go ahead!
How to construct a lambda function
This is a function, to add 2 numbers.
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def add(x, y):
return x + y
Although this is a very simple function, we need 2 lines of code. But what about lambda function?
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add = lambda x, y: x + y
Just 1 line.
Let’s take a look at the construction of this lambda function. The add at the beginning of the statement represents the function name. The lambda keyword indicates that this is a lambda function, a and b are the parameters of the function. And then a colon, followed by the colon is what the lambda function returns. If the lambda function does not require parameters, just add a colon after lambda.
Easy to understand, right? Now Let’s see how to use the lambda function in practical code.
How to use lambda function
Basic usage
The method of using lambda function is same as ordinary functions, function name and arguments.
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add = lambda a,b: a+b
print(add(1,2))
Use lambda function as a parameter
An important use of lambda functions is to use them as parameters of other functions, such as map and sorted functions that require functions as parameters.
Here is an example that use lambda in map.
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my_lst = [1,2,3,4,5]
print(list(map(lambda x: x**2, my_lst)))
I am giving a brief explanation of map function here. It takes a function an iterable object as parameters, then applied the function to each element in the iterable object, returning a new iterator.
In this example, we passed in lambda function could square numbers. So what we get is the square of each value in my_lst.
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[1, 4, 9, 16, 25]
Use with dictionary
I want to share my favorite way to use lambda function, as dictionary value. When we need to write multiple conditional branches, we need to write multiple else if, which is not Pythonic. But using lambda function as dictionary value could solve this problem very well.
For example, now we need a function that, based on the user’s level, adds corresponding credits to the user each time they log in.
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def user_logging(user):
if user.level == 1:
user.credits += 2
elif user.level == 2:
user.credits += 5
elif user.level == 3:
user.credits += 10
elif user.level == 4:
user.credits += 20
If there were more user levels, this function would be longer.
Now I’m going to use dictionary.
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def user_logging(user):
level_credit_map = {
1: lambda x: x+2,
2: lambda x: x+5,
3: lambda x: x+10,
4: lambda x: x+20
}
user.credit = level_credit_map[user.level](user.credit)
It is more concise than the previous one, and is also more readable.
level_credit_map[user.level] will return the corresponding lambda function according to user.level , and the following user.credit would be argument passed into the lambda function.
At last
After reading this blog, you may now be able to take advantages of lambda function in practical code, you can check your previous code to see if there are any areas that can be optimized.
If you have any questions, feel free to ask in the comment section below, I will do my best to answer. If you think the article is helpful, you can like and share it with anyone who you think would find it useful. You can also subscribed my channel for future posts. Thanks for reading.