One of my favourite aphorisms I often use when teaching is the following:

Everything is hard when you don't know it. Everything is easy when you know it.

This feels like it ought to be a quote from someone important, but GPT couldn't find any references. So, I think I may have made this up myself. If you like it, I'll take credit. If you think it's silly, it's probably someone else's!

Python's lambda functions are a perfect example of this idea. Almost everyone finds them puzzling and impenetrable the first time they encounter them. And the second. And third. But I recall the moment I finally understood them, and I remember clearly the thought that streamed through my head:

Is that it? What's all the fuss, then?

They're useful. But they're not magical, even if you may get that impression from how some talk about them.

In this spirit, I'm writing a concise, matter-of-fact article about lambda functions. The article style mirrors their functionality without glorifying them excessively.

If you're new to my articles, this is not how I usually write my articles!

Lambda functions are functions. So far, this looks easy, right?

It says it in the REPL/Console output above. So it must be true.

Let's compare a lambda function with a standard function. And we'll do this with the most boring function you can imagine. The remaining examples are shown in a script rather than the REPL/Console:

Here's a brief animation highlighting the similarities and differences between the two:

And here's the comparison in a table:

You can call a function, whether it's a standard function or a lambda function. You won't call the function directly in many use cases for lambda functions. You'll see why later. But it's a function, so you can call it:

With standard functions, you use the function name followed by parentheses to call the function. But lambda functions don't have a name! Instead, you enclose the expression in parentheses, and you can treat it just like you would treat a standard function name: add (10) to call the function with 10 as the argument.

You could name a lambda function if you really wanted to. But if you feel the need to name a lambda function, you probably should use a standard function instead. Anyway, here's how you would name a lambda function if you're stubborn enough to do so:

And that's all there is, really. Python's lambda functions are just functions with no name. You can define them with one or more parameters (or none). However, you can only have a single expression that evaluates to a value. This is the value returned by the lambda function. Therefore, you can't have complex algorithms in a lambda function, just whatever you can fit in a single expression!

Here are a few more examples of lambda functions. There's one with no parameters, one with two parameters, and another with three:

So, when do you need to use a lambda function? Well, you never need to use one. You can always use a standard function if you wish. But there are cases when it's convenient to use an inline anonymous function rather than define a standard function, think of a good name to give it, and then use it once.

Functions can be used as arguments for other functions. This is especially common in the functional programming style. Here's one example using the built-in map() function. I'll demonstrate both scenarios: using a standard function and using a lambda function.

I'll use this dictionary in the following examples:

These are the scores these students got in a test. Let's figure out who passed the test. The pass mark is 5 out of 10.

First, let's use a standard function definition:

Each key in the dictionary scores is passed to check_pass(), and the function's return value is used as the output.

Why are the dictionary keys passed to the function and not the key-value pairs? Iteration over dictionaries in Python uses the keys. This is also the case if you use a dictionary in a for loop, say.

Next, using a lambda function:

You get the same result. It's more convenient to use lambda functions in these scenarios.

I can't conclude this section without pointing out that there's another way to obtain the same result, which many would consider preferable and more Pythonic:

Use lambda functions if you want. Don't if you don't! And this brings us to the end of this short article. Python's lambda functions are functions with no name and which have a single expression. They're "disposable" functions. You create them as and when you need them, and then they're gone.

And at under 1,000 words, this is one of the shortest articles I ever wrote!

Code in this article uses Python 3.12

For more Python resources, you can also visit Real Python—you may even stumble on one of my own articles or courses there!

Also, are you interested in technical writing? You’d like to make your own writing more narrative, more engaging, more memorable? Have a look at Breaking the Rules.

And you can find out more about me at stephengruppetta.com

Stop Stack

#42

• I'm getting closer to the official launch of The Python Coding Place (15 January 2024). There are already many who joined as lifetime members, and I hope many more will join over the coming weeks and months to grow this new community into a thriving learning platform for beginners and intermediate Python programmers. There are video courses, weekly videos, members' forum, live workshops, and even cohort-based courses…all included in the lifetime membership.

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• Recently published articles on The Python Coding Stack:

  • In Conversation: Pawel and Stephen Discuss Matplotlib's New-ish subplot_mosaic() In recent years, Matplotlib introduced a new function for plotting several plots in one figure. We had a chat about subplot_mosaic()

  • In Conversation: Rodrigo and Stephen Discuss Analogies When Learning To Code A conversation between Rodrigo Girão Serrão and Stephen Gruppetta on analogies in programming

  • A Touch of Randomness Makes The Magic Sparkle • A Python turtle Animation Let's build this sparkly turtle animation step by step

  • NumPy for Numpties Introducing an infrequent, loose series of articles on NumPy

  • The Curious Little Shop at The End of My Street • Python's f-strings Many people's favourite Python feature: f-strings

• Recently published articles on Breaking the Rules, my other substack about narrative technical writing:

  • I Haven't Been Abducted by Aliens (Ep. --) Why this long lull since the last Breaking The Rules post?

  • The Selfish Reason (Ep. 13) Another reason for authors to innovate • Enjoying the writing process

  • The Consequential Detail (Ep. 12). Can a single letter or one blank line make a difference? (Spoiler Alert: Yes)

  • The Unexpected Audience (Ep. 11). What I'm learning from listening to Feynman's physics lectures

  • The Story So Far (Mid-Season* Review). Are you back from your holidays? Catch up with what you've missed

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