Resources

Introduction

Last 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.



Logic & Data

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 Data

There 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 Syntax

Lambdas 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!

Views: 146

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

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.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

KubeCon NA 2025 - Robert Nishihara on Open Source AI Compute with Kubernetes, Ray, PyTorch, and vLLM

AI workloads are growing more complex in terms of compute and data, and technologies like Kubernetes and PyTorch can help build production-ready AI systems to support them. Robert Nishihara from Anyscale recently spoke at KubeCon + CloudNativeCon North America 2025 Conference about how an AI compute stack comprising Kubernetes, PyTorch, VLLM and Ray technologies can support these new AI workloads.

By Srini Penchikala

Reddit Migrates Comment Backend from Python to Go Microservice to Halve Latency

Reddit has rebuilt its core backend, migrating Comments, Accounts, Posts, and Subreddits from a legacy Python monolith to Go microservices. The migration improves performance, halves critical write latency, and modernizes the platform for future scalability while preserving correctness across multiple datastores.

By Leela Kumili

Amazon Adds A2A Protocol to Bedrock AgentCore for Interoperable Multi-Agent Workflows

Amazon announced support for the Agent-to-Agent (A2A) protocol in Amazon Bedrock AgentCore Runtime, enabling communication between agents built on different frameworks. The protocol allows agents developed with Strands Agents, OpenAI Agents SDK, LangGraph, Google ADK, or Claude Agents SDK to "share context, capabilities, and reasoning in a common, verifiable format."

By Vinod Goje

Podcast: Authenticity Over Convention: Lessons from 16 Years of Solo Game Development

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Joe Cassavaugh about building a sustainable solopreneur game development business, the importance of authenticity over conventional wisdom, and learning from both successes and failures in the digital content marketplace.

By Joe Cassavaugh

Microsoft's Azure Cobalt 200 ARM Chip Delivers 50% Performance Boost

At the Ignite conference, Microsoft unveiled the Cobalt 200 ARM processors, boasting a remarkable 50% performance boost. Engineered with advanced AI simulations and robust security features, it supports high-density workloads with 132 cores. As the next-gen solution for Azure, Cobalt 200 sets a new standard in efficiency and power, enhancing cloud capabilities for diverse applications.

By Steef-Jan Wiggers

© 2025   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service