Coding principles 1: Favour functional code

Introduction to the principles

When I started working at 67 Bricks in 2017, in a small Oxford office already slightly struggling to contain about 15 developers, I found a strong and positive coding culture here. I learnt very quickly over my first few weeks what kind of code and practices the company valued. Some of that learning came via formal routes like on-boarding meetings and code review comments, but a lot of it came just by being in the office among many excellent developers and chatting or overhearing chats about opinions and preferences.

While there’s something very nice about this organic, osmosis-like way of ingesting a company’s values, practices and principles, it has been forced to evolve by a few factors over the last year. First we switched to home-working during the Covid lockdowns of 2020 and 2021 and then settled into a hybrid working model in which home-working is the default for most of us and the office is used somewhat less routinely. Secondly, we’ve increasing our technical team quite significantly over the last several years. Thirdly, that growth has partly involved a focus on bringing in and developing more junior developers. Each of these changes has made the “osmosis” model for new starters to pick up the company’s values a bit less tenable.

So over recent months, the tech leads have undertaken a project to distil those unwritten values and principles into a set of slightly more formal statements that new starters and old hands alike can refer to to help guide our high level thinking.

We came up with 9 of these principles. This and the following 8 posts in this series will go through each principle describing it and explaining why we think it is important in our ultimate goal of producing good, well-functioning products that run robustly, meet customer needs and are easy to maintain. 67 Bricks’s semi-joking unofficial motto is “do sensible things competently”; these principles aim to formalise a little what we mean by “sensible” and “competent”.

Generally I’ve used Typescript to write any code examples. The commonality of Typescript and Javascript should mean that examples are understandable to a good number of people.

About the principles

Before diving into the first principle, it’s worth briefly describing what these principles are and what they’re not.

These are high-level, general principles that aim to guide approaches to writing code in a way that is language/framework/technology agnostic. They should be seen more as rules of thumb or guidelines with plenty of room for exceptions and caveats depending on the situation. A good comparison might Effective Java by Joshua Bloch where a statement like “Favor composition over inheritance” doesn’t rule out ever using inheritance, but aims to guide the reader to understand why – in some cases – inheritance can cause problems and composition may provide a more robust and flexible solution.

These principles are not a style guide – our individual project teams are self organising and perfectly capable of enforcing their own code style preferences as they see fit – nor a dogmatic, stone-carved attempt at absolute truth. They’re also not strongly opinionated hot takes that are likely to provoke flame wars. They are simply what we see as sensible guidelines towards good, easy-to-write, easy-to-maintain code, and therefore robust software.

That was a lot of ado, so without any further let’s get on with the first principle.

The principle

Favour functional, immutable code over imperative, mutable code

Functional code emphasises side effect free, pure, composable functions that deal with immutable objects and avoid mutable state. We believe this approach leads to more concise, more testable, more readable, less error-prone software and we advise that all code be written in this way unless there is a good reason not to.

Code written in this way is easier to reason about because it avoids side effects and state mutations; functions are pure, deterministic and predictable. This approach promotes writing small, modular functions that are easy to compose together and easy to test.

67 Bricks has a history of favouring Scala as a development language – which may be clear from browsing back through the history of this blog. While these days C# has become a more common language for the products we deliver, the functional-first spirit of Scala is still woven into the fabric of 67 Bricks development. I believe Martin Odersky’s Coursera course: Functional Programming Principles in Scala is an excellent starting point for anyone wanting to understand the functional programming mindset regardless of your interest in Scala as a language.

As an interesting aside, the implementations of many of the Scala collections library classes – such as ListMap and HashMap – use mutable data structures internally in some methods, presumably for purposes of optimisation. This illustrates the caveat mentioned above that there may be sensible, situation-specific reasons to override this principle and others. It’s worth noting however that while the internals of some functions may be implemented in an imperative way, those are implementation details that are entirely encapsulated and irrelevant to users of the API.

I think “functional programming” is better seen as a continuum than a black and white dichotomy. While certain languages – like Haskell and F# – may be strictly functional, most languages – including C#, Javascript/Typescript, Python and (increasingly) Java – have many features that allow you to write in a more functional way if you choose to use them.


There are many books describing and teaching functional programming and the various principles that make it up, so I don’t intend to go into too much detail, but I think a couple of examples may help illustrate what functional code is and why it’s useful.

The following is an example of some code that does not follow this principle:

let onOffer = false;

function applyOffersToPrices(prices: number[]) {
  onOffer = isOfferDate(new Date());
  if (onOffer) {
    for (let i = 0; i < prices.length; i++) {
      prices[i] /= 2;
  return onOffer;

const prices: number[] = await retrievePricesFromSomewhere();
const onOffer = applyOffersToPrices(prices)
if (onOffer) {
  // ... what values does `prices` contain here?
} else {
  // ... how about here?

This code is hard to reason about because applyOffersToPrices mutates one of its arguments in some instances. This makes it very hard to be sure what state the values in the prices array are in after that function is called.

The following is an example that attempts to follow the principle:

function discountedPrices(prices: number[], date: Date) {
  if (!isOfferDate(date)) {
    return prices;
  return => price / 2)

const prices: number[] = await retrievePricesFromSomewhere();
const todayPrices = discountedPrices(prices, new Date());

In this example, applyOffersToPrices is a pure function that does not mutate its input, but returns a new array containing the updated prices. It is unambiguous that prices still contains the original prices while todayPrices contains the prices that apply on the current date with the offer applied as necessary.

Note also that discountedPrices has everything it needs – the original prices and the current date – passed into it as arguments. This makes it very easy to test with different values.


Functional Programming Principles in Scala – Martin Odersky on Coursera

Why Functional Programming