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How To Lose Functional Programming At Work

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SummaryTips on how to unsuccessfully introduce and keep functional programming styles and principles in your workplace.
Shared2023-01-30
Revised2023-01-30 @ 23:00 UTC

Hi! If you’re looking to lose functional programming at work, here are a bunch of mistakes I’ve made on JS-heavy web teams over the years that can help you do the same.

Enjoy!

Note: if sarcasm and self-deprecation aren’t your thing, you can skip to the real-talk takeaways.

PDF version

Here is the much prettier PDF version that is also useful for sending to your teammates or using in your own lunch-n-learn tech talk.

Thanks to KronisLV on the orange site for helping me fix an issue where the PDF was accidentally auto-downloading in Firefox.

Your browser doesn’t support PDF, but you can download the file here: How to Lose Functional Programming at Work - PDF

How to Lose Functional Programming at Work - PDF

Don’t have static type checking

const processData = composeP(syncWithBackend, cleansePII, validateData)

// * What arguments and their types are expected here?
//
// * If each function is written like this, how can
//   one suss out what data are flowing where?
//
// * How hard is this going to be to debug?
//   Use this everywhere: `(x) => (console.log(x), x)`

Oh, so point-free style programming is the problem? Not so fast:

async function processData(data) {
  await validateData(data)
  const cleansedData = cleansePII(data)
  await syncWithBackend(cleansedData)
  return data
}

// or for the Promise-chainers


const processData = data =>
  validateData(data)
    .then(cleansePII)
    .then(syncWithBackend)
    .then(() => data)

Do keep telling yourself that any of these 3, on their own, are easy for your teammates to work with after 3 months.

Don’t use well-known code documentation tools

Deprive your team of this clarity and helpful auto-completion:

// NOTE: this is an untested, small example

/**
 * @typedef {Object} ReportingInfo
 * @property {("light"|"dark")} userTheme - Current user's preferred theme
 * @property {string} userName - Current user's name
 * @property {UUID} postId - The current post's ID
 */

/**
 * Validates that the reporting data (current user site prefences and post info)
 * is OK, removes personally identifiable information, syncs this info with the
 * backend, and gives us back the original data.
 *
 * @param {ReportingInfo} data - The current user's site preferences and post info
 * @returns {Promise<ReportingInfo>} - The original reporting data
 */
const processData = data => // 


Don’t properly train new and existing colleagues

Truly believe, in your heart, that you can write a pile of blog posts, collect a bunch of other great learning resources, hand them all to a new FP learner, recommend they read as much as they can then come back with questions, and expect them to come out the other side at all.

Conversely, spend all your time and energy on a couple of individuals, neglect the others, fail to write any useful learnings down, and forget to encourage these initiates to turn around and help teach their other colleagues, in turn.

Don’t bother getting the other engineering teams on board and rowing in the same direction

Instead, if you keep it to yourself, other teams won’t get to contribute and probably improve the state of things.

Do live by the creed, “Point-free or die”

Watch the video, “Point-Free or Die: Tacit Programming in Haskell and Beyond”, by Amar Shah

Contrived example:

import { __, any, lt } from 'ramda'
const anyLt0 = any(lt(0, __)) // hint: this has a bug in it
anyLt0([1, 2, 3]) // true — ugh


// vs. the probably pretty simple


const anyLt0 = numbers => numbers.some(n => n < 0)
anyLt0([0, 1, 2, 3]) // false
anyLt0([0, 1, 2, -1, 3]) // true — looks good

// 👆 should we resist eta-converting this?!
// 

// NOT ON MY WATCH

const any = fn => array => array.some(fn)
const isLtN = x => n => x < n
const isLt0 = isLtN(0)
const anyLt0 = any(isLt0)
anyLt0([1, 2, 3]) // true — ugh; the bug is back

Real, but altered, example:

const finishItems = compose(
  flip(merge)({ isDone: true, amtComplete: 100 }),
  over(
    lensProp('indexedObjects'),
    mapVals(
      compose(
        over(lensProp('indexedObjects'), mapVals(assoc('isDone', true))),
        assoc('isDone', true)
      )
    )
  )
)

Do prefer the wrong abstraction over the right duplication

I was at Sandi Metz’ RailsConf 2014 Chicago talk, All the Little Things, where she blew my mind with the simplicity of “preferring duplication over the wrong abstraction”. Two years later, she followed it up with some great blog commentary, The Wrong Abstraction.

But in this case, dilute your core business logic to broad generalizations that can be extracted and abstracted over and over, fail to understand category theory enough for this to be useful, and be the only one who knows how these abstractions work.

You’ll know you’ve lost people when normally thorough PR reviews now look like, “👍”.

Don’t refactor old patterns that clearly don’t work for the team

Make sure that people coming into the project have your old code patterns to emulate that you cringe looking at years later but never made the time to update.

While you could allocate investment time to this or reading up on how to improve your technical leadership skills, spend that time making new features, instead.

Do force functional patterns into a language that wasn’t built for them (bonus: cryptic stack traces)

Do opaquely compose and sequence the entirety of your API endpoints and make them hard to debug

On the surface, this isn’t so difficult to read


// handler for POST /posts

import { createPost } from 'app/db/posts'
import { authenticateUser, authorizeUser } from 'app/lib/auth'
import { trackEvent } from 'app/lib/tracking'

const validateRequestSchema = payload => { /* 
 */ }

export const handleCreatePost = curry(metadata =>
  pipeP(
    authenticateUser(metadata),
    authorizeUser(metadata),
    validateRequestSchema,
    createPost(metadata),
    tapP(trackEvent('post:create', metadata)),
    pick([ 'id', 'authorId', 'title' ])
  )
)

Did you catch that this expects 2 arguments? Did you also know that authenticateUser ignores the 2nd argument sent to it? How would you? And what about trackEvent? Does it receive the payload, or does createPost() return post-related data?

Let’s write this another way:

export async function handleCreatePost(metadata, payload) {
  await authenticateUser(metadata)
  await authorizeUser(metadata, payload)
  await validateRequestSchema(payload)

  const post = await createPost(metadata, payload)

  await trackEvent('post:create', metadata, payload)

  return {
    id: post.id,
    authorId: post.authorId,
    title: post.title,
  }
}

I’m not saying that option #2 is an awesome handler, but if you want to make it trickier for people, go with option #1.

Do recreate imperative, procedural programming while calling it “declarative”

const setBookReadPercentByType = (contentType, statusObject) =>
  assoc(
    'readPercent',
    pipe(
      prop('subItems'),
      values,
      filter(propEq(contentType, 'chapter')),
      length,
      flip(divide)(compose(length, keys, prop('subItems'))(statusObject)),
      multiply(100),
      Math.round
    )(statusObject),
    statusObject
  )

Do have 8+-ish different patterns for function composition

// 👇 These 4, plus Promisified versions of them,
//    plus combinations of them all used at once;
//    doesn't include ramda's pipeWith and composeWith

// compose
const getHighScorers =
  compose(
    mapProp('name'),
    takeN(3),
    descBy('score')
  )

// pipe
const getHighScorers =
  pipe(
    descBy('score'),
    takeN(3),
    mapProp('name')
  )

// composeWithValue
const getHighScorers = players =>
  composeWithValue(
    mapProp('name'),
    takeN(3),
    descBy('score'),
    players
  )

// pipeWithValue
const getHighScorers = players =>
  pipeWithValue(
    players,
    descBy('score'),
    takeN(3),
    mapProp('name')
  )

// 
but then now mix and match them with actual,
// real-life business logic.

Do make yourself one of the few who can debug algebraic data types during midnight incidents

Ensure your team is surprised by all of the following words when debugging or altering your code in the pursuit of their own work tasks:

Don’t have SQL (a declarative language) do data transformations for you — DIWHY??? it yourself

Instead, and in the name of immutability, use data pipelines in your app to apply changes to your data, one transformation at a time, and accidentally do as many key/value iterations and memory allocations as possible. 😬

Do suggest, on PRs, that colleagues completely refactor what they’ve done to fit your functional style

What you have here works great, but what could this look like if we flipped all the function arguments around, removed all these intermediate variables, and mapped these operations over an Either?

or

I noticed you’re explicitly constructing these objects in their functions. If you were to use <UTILITY-FUNCTION>, you could declare the shape of your outputted object and use functions as the values to look up or compute each value given some data.

And for some quick final ones


Real-talk takeaways

Much of the backwards recommendations here can be, on the surface, written off as symptoms of inexperience, a lack of technical leadership from me, and obviously not the right paths.

But I think it’s something deeper than those easy explanations.

Most things in life need to be tended to in order for them to go the ways that we’d like them to; our relationships, our physical & mental health, our gardens. With most of these things in life, we strive to purposefully sculpt our futures.

However, there are many things that we accidentally sculpt. For example, if the fastest way from your back door to your garden is through your grassy yard, the simplest thing is to walk over the grass to get there. It makes sense for a while, but over time, your stepping on the grass carves a path that you never intended to create — it was an unintended consequence of your gardening.

This same thing happens with our minds and in our work. If we’re not paying attention to the big picture, the path of least resistance can carve canyons.

In my case, here, not taking responsibility of a path I helped create, coupled with persistent imposter syndrome and a feeling I needed to ship features and just look out for myself, instead of making time for re-evaluation, helped lead to the difficulties above for others and a loss of “higher” functional programming in a pretty good workplace that gives teams the freedom to choose their own tools.

But all is not lost! The core tenets of FP seem to remain:

It seems a happy balance has been collectively decided on, and I’m excited to see where it goes. Perhaps, this time around, I’ll be better.

Thanks for reading,
Robert