Teach Yourself some Functional Programming with Scala

Feb 22, 20171 like275 views

This document provides an introduction to functional programming concepts using Scala. It defines functional programming as a programming paradigm focused on pure functions without side effects. It contrasts imperative programming which can contain side effects. Key functional programming concepts discussed include referential transparency, where expressions will always evaluate to the same result given the same inputs; avoiding mutable state; and using functions as first-class citizens that can be assigned to variables or passed as arguments. Benefits highlighted are improved composability, testability, parallelization and optimization of functional code. The document provides examples of functional programming in Scala including using high-order functions and anonymous functions.

Teach Yourself some
Functional Programming
with Scala
@DamianJureczko

Agenda
What is Functional Programming?
Key concepts of Functional Programming

Functional Programming?
Programming Paradigm
Style

There are others
Imperative
Object-oriented
...

Functional Programming is about
pure functions
no side effects

Imperative example ✗
List<User> users = new ArrayList<>();
users.add(new User("John", 35));
users.add(new User("Michael", 27));
int count = 0;
for (User user : users)
{
if (user.getAge() > 30)
{
count += 1;
}
}

Functional example ✓
val users = List(User("John", 35), User("Michael", 27))
val count = users.count(user => user.age > 30)

Referential transparency
“An expression is said to be referentially
transparent if it can be replaced with its
corresponding value without changing
the program's behavior.“

Referentially transparent function
returns the same value for same arguments
has no side effects

The same result for same arguments ✓
def inc(x: Int): Int = x + 1
val two = inc(1)

Result can be different for same arguments ✗
def crazyInc(x: Int): Int = x + Random.nextInt()
val whoKnows = crazyInc(1)

Result depends on some global, mutable state ✗
var userCount = ???
def getUserCount: Int = userCount

Function without side effects
Result: x = 8
def add(x: Int, y: Int): Int = x + y
val x = add(1, 1) * add(2, 2)

We can change it to ✓
Result: x = 8
val x = add(1, 1) * 4

We can change it to ✓
Result: x = 8
val x = 2 * 4

Function with side effects
Result: x = 8, totalSum = 6
var totalSum = 0
def weirdAdd(x: Int, y: Int): Int = {
val sum = x + y
totalSum += sum
sum
}
val x = weirdAdd(1, 1) * weirdAdd(2, 2)

We cannot change it to ✗
Result: x = 8, totalSum = 2
val x = weirdAdd(1, 1) * 4

We cannot change it to ✗
Result: x = 8, totalSum = 0
val x = 2 * 4

Pure functions are referentially
transparent

Functional Programming
What are the beneﬁts?
compositionality
(divide & conquer, generalize, reuse)
code easier to reason about
code easier to parallelize
code easier to optimize (memoization)
code easier to test

First-class functions
We can use functions like we use other types
assign to variable
pass to function (as argument)
return from function

Function type
Int => Int
type Transformation = Int => Int

Function object
Anonymous function
x => x + 1

Assigning function to variable
val inc: Int => Int = x => x + 1
val inc: Transformation = x => x + 1
val two = inc(1)

High-order functions
take other functions as argument
return functions as result

Passing function to high-order function
val count = users.count(user => user.age > 30)
def count(p: User ⇒ Boolean): Int

Returning function from high-order function
def makeUserFilterByAge(threshold: Int): User => Boolean =
user => user.age > threshold
val userOlderThen30: User => Boolean = makeUserFilterByAge(30)
val count = users.count(userOlderThen30)

Summary
Functional programming is here
It simpliﬁes your life
It makes you a better developer
Scala is a good way to start

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Microsoft Azure is a cloud platform that empowers businesses with scalable computing, data analytics, artificial intelligence, and cybersecurity capabilities. Arguably the biggest hurdle for most organizations is understanding how to get started. Microsoft Azure is a consumption-based cloud service. This means you pay for what you use. Unlike traditional software, Azure resources (e.g., VMs, databases, storage) are billed based on usage time, storage size, data transfer, or resource configurations. There are three primary Azure purchasing models: • Pay-As-You-Go (PAYG): Ideal for flexibility. Billed monthly based on actual usage. • Azure Reserved Instances (RI): Commit to 1- or 3-year terms for predictable workloads. This model offers up to 72% cost savings. • Enterprise Agreements (EA): Best suited for large organizations needing comprehensive Azure solutions and custom pricing. Licensing Azure: What You Need to Know Azure doesn’t follow the traditional “per seat” licensing model. Instead, you pay for: • Compute Hours (e.g., Virtual Machines) • Storage Used (e.g., Blob, File, Disk) • Database Transactions • Data Transfer (Outbound) Purchasing and subscribing to Microsoft Azure is more than a transactional step, it’s a strategic move. Get in touch with our team of licensing experts via [email protected] to further understand the purchasing paths, licensing options, and cost management tools, to optimize your investment.

How Insurance Policy Management Software Streamlines OperationsInsurance Tech Services

Maintaining + Optimizing Database Health: Vendors, Orchestrations, Enrichment...BradBedford3

Join the Denver Marketo User Group, Captello and Integrate as we dive into the best practices, tools, and strategies for maintaining robust, high-performing databases. From managing vendors and automating orchestrations to enriching data for better insights, this session will unpack the key elements that keep your data ecosystem running smoothly—and smartly. We will hear from Steve Armenti, Twelfth, and Aaron Karpaty, Captello, and Frannie Danzinger, Integrate.

Online Queue Management System for Public Service Offices [Focused on Municip...Rishab Acharya

This report documents the design and development of an Online Queue Management System tailored specifically for municipal offices in Nepal. Municipal offices, as critical providers of essential public services, face challenges including overcrowded queues, long waiting times, and inefficient service delivery, causing inconvenience to citizens and pressure on municipal staff. The proposed digital platform allows citizens to book queue tokens online for various physical services, facilitating efficient queue management and real-time wait time updates. Beyond queue management, the system includes modules to oversee non-physical developmental programs, such as educational and social welfare initiatives, enabling better participation and progress monitoring. Furthermore, it incorporates a module for monitoring infrastructure development projects, promoting transparency and allowing citizens to report issues and track progress. The system development follows established software engineering methodologies, including requirement analysis, UML-based system design, and iterative testing. Emphasis has been placed on user-friendliness, security, and scalability to meet the diverse needs of municipal offices across Nepal. Implementation of this integrated digital platform will enhance service efficiency, increase transparency, and improve citizen satisfaction, thereby supporting the modernization and digital transformation of public service delivery in Nepal.

Build enterprise-ready applications using skills you already have!PhilMeredith3

Process Tempo is a rapid application development (RAD) environment that empowers data teams to create enterprise-ready applications using skills they already have. With Process Tempo, data teams can craft beautiful, pixel-perfect applications the business will love. Process Tempo combines features found in business intelligence tools, graphic design tools and workflow solutions - all in a single platform. Process Tempo works with all major databases such as Databricks, Snowflake, Postgres and MySQL. It also works with leading graph database technologies such as Neo4j, Puppy Graph and Memgraph. It is the perfect platform to accelerate the delivery of data-driven solutions. For more information, you can find us at www.processtempo.com

Software Engineering Process, Notation & Tools Introduction - Part 4Gaurav Sharma

Micro-Metrics Every Performance Engineer Should Validate Before Sign-OffTier1 app

When it comes to performance testing, most engineers instinctively gravitate toward the big-picture indicators—response time, memory usage, throughput. But what about the smaller, more subtle indicators that quietly shape your application’s performance and stability? we explored the hidden layer of performance diagnostics that too often gets overlooked: micro-metrics. These small but mighty data points can reveal early signs of trouble long before they manifest as outages or degradation in production. From garbage collection behavior and object creation rates to thread state transitions and blocked thread patterns, we unpacked the critical micro-metrics every performance engineer should assess before giving the green light to any release. This session went beyond the basics, offering hands-on demonstrations and JVM-level diagnostics that help identify performance blind spots traditional tests tend to miss. We showed how early detection of these subtle anomalies can drastically reduce post-deployment issues and production firefighting. Whether you're a performance testing veteran or new to JVM tuning, this session helped shift your validation strategies left—empowering you to detect and resolve risks earlier in the lifecycle.

Automating Map Production With FME and PythonSafe Software

People still love a good paper map, but every time a request lands on a GIS team’s desk, it takes time to create that perfect, individual map—even when you're ready and have projects prepped. Then come the inevitable changes and iterations that add even more time to the process. This presentation explores a solution for automating map production using FME and Python. FME handles the setup of variables, leveraging GIS reference layers and parameters to manage details like map orientation, label sizes, and layout elements. Python takes over to export PDF maps for each location and template size, uploading them monthly to ArcGIS Online. The result? Fresh, regularly updated maps, ready for anyone to grab anytime—saving you time, effort, and endless revisions while keeping users happy with up-to-date, accessible maps.

How to Generate Financial Statements in QuickBooks Like a Pro (1).pdfQuickBooks Training

Are you preparing your budget for the next year, applying for a business credit card or loan, or opening a company bank account? If so, you may find QuickBooks financial statements to be a very useful tool. These statements offer a brief, well-structured overview of your company’s finances, facilitating goal-setting and money management. Don’t worry if you’re not knowledgeable about QuickBooks financial statements. These statements are complete reports from QuickBooks that provide an overview of your company’s financial procedures. They thoroughly view your financial situation by including important features: income, expenses, investments, and disadvantages. QuickBooks financial statements facilitate your financial management and assist you in making wise determinations, regardless of your experience as a business owner.

14 Years of Developing nCine - An Open Source 2D Game FrameworkAngelo Theodorou

DevOps for AI: running LLMs in production with Kubernetes and KubeFlowAarno Aukia

Eliminate the complexities of Event-Driven Architecture with Domain-Driven De...SheenBrisals

The distributed nature of modern applications and their architectures brings a great level of complexity to engineering teams. Though API contracts, asynchronous communication patterns, and event-driven architecture offer assistance, not all enterprise teams fully utilize them. While adopting cloud and modern technologies, teams are often hurried to produce outcomes without spending time in upfront thinking. This leads to building tangled applications and distributed monoliths. For those organizations, it is hard to recover from such costly mistakes. In this talk, Sheen will explain how enterprises should decompose by starting at the organizational level, applying Domain-Driven Design, and distilling to a level where teams can operate within a boundary, ownership, and autonomy. He will provide organizational, team, and design patterns and practices to make the best use of event-driven architecture by understanding the types of events, event structure, and design choices to keep the domain model pure by guarding against corruption and complexity.

From Chaos to Clarity - Designing (AI-Ready) APIs with APIOps CyclesMarjukka Niinioja

Teams delivering API are challenges with: - Connecting APIs to business strategy - Measuring API success (audit & lifecycle metrics) - Partner/Ecosystem onboarding - Consistent documentation, security, and publishing 🧠 The big takeaway? Many teams can build APIs. But few connect them to value, visibility, and long-term improvement. That’s why the APIOps Cycles method helps teams: 📍 Start where the pain is (one “metro station” at a time) 📈 Scale success across strategy, platform, and operations 🛠 Use collaborative canvases to get buy-in and visibility Want to try it and learn more? - Follow APIOps Cycles in LinkedIn - Visit the www.apiopscycles.com site - Subscribe to email list -

Software Engineering Process, Notation & Tools Introduction - Part 3Gaurav Sharma