Codetown ::: a software developer's community

ResourcesLast week, we went over higher order functions in Kotlin. We learned how higher order functions can accept functions as parameters and are also able to return functions. This week, we will take a look at lambdas. Lambdas are another type of function and they are very popular in the functional programming world.
Computer programs are made up of two parts: logic and data. Usually, logic is described in functions and data is passed to those functions. The functions do things with the data, and return a result. When we write a function we would typically create a named function. As we saw last week, this is a typical named function:
fun hello(name: String): String {
return "Hello, $name"
}
Then you can call this function:
fun main() {
println(hello("Matt"))
}
Which gives us the result:
Hello, Matt
Functions as DataThere is a concept in the functional programming world where functions are treated as data. Lambdas (functions as data) can do the same thing as named functions, but with lambdas, the content of a given function can be passed directly into other functions. A lambda can also be assigned to a variable as though it were just a value.
Lambda SyntaxLambdas are similar to named functions but lambdas do not have a name and the lambda syntax looks a little different. Whereas a function in Kotlin would look like this:
fun hello() {
return "Hello World"
}
The lambda expression would look like this:
{ "Hello World" }
Here is an example with a parameter:
fun(name: String) {
return "Hello, ${name}"
}
The lambda version:
{ name: String -> "Hello, $name" }
You can call the lambda by passing the parameter to it in parentheses after the last curly brace:
{ name: String -> "Hello, $name" }("Matt")
It’s also possible to assign a lambda to a variable:
val hello = { name: String -> "Hello, $name" }
You can then call the variable the lambda has been assigned to, just as if it was a named function:
hello("Matt")
Lambdas provide us with a convenient way to pass logic into other functions without having to define that logic in a named function. This is very useful when processing lists or arrays of data. We’ll take a look at processing lists with lambdas in the next post!
Tags:
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
Check out the Codetown Jobs group.
AI coding assistants promise speed, but what do they mean for quality, trust, and the architect’s craft? In this inaugural episode of Next Gen Architecture Playbook, Shweta Vohra and Grady Booch explore a principled view of how architecture must evolve when machines begin writing code alongside humans. They unpack the third golden age of software engineering, where productivity gains are real.
By Grady Booch
Amazon CloudFront now supports mutual TLS authentication for origin servers, completing end-to-end zero-trust authentication from viewers to backends. The feature replaces IP allowlists and shared secrets with cryptographic verification, proving particularly valuable for multi-cloud deployments, where origins can verify that traffic originated from CloudFront without VPN tunnels.
By Steef-Jan Wiggers
In this article, author Abhishek Goswami shares a practitioner's playbook with development practices, that describes building agentic AI applications and scaling them in production. He also presents core architecture patterns for agentic application development.
By Abhishek Goswami
The pandas team has released pandas 3.0.0, a major update that changes core behaviors around string handling, memory semantics, and datetime resolution, while removing a substantial amount of deprecated functionality. The release introduces several changes to core behaviors in the library’s API.
By Robert Krzaczyński
A new CNCF report identifies Kubernetes as the primary engine for AI growth, with 82% production adoption. However, technical maturity has outpaced organisational change. Human factors, such as siloed team structures and a lack of cross-functional collaboration, now serve as the leading barriers to successful deployment, making cultural transformation the decisive factor for AI scaling.
By Mark Silvester
© 2026 Created by Michael Levin.
Powered by