lotus.dev — clean architecture, blooming

The philosophy

In Japanese tradition, the lotus blooms unblemished from muddy water — a quiet reminder that elegance is not the absence of complexity, but its careful resolution.

lotus.dev is a developer framework for transforming raw, tangled data into clean, composable structures. Each function is a petal: small, deliberate, opening at its appointed angle. Together they form something whole.

Three principles

The library is built on three quiet ideas, each one ma — the space between things — as much as the things themselves.

Stillness Pure functions. No hidden state. The pond is undisturbed until you choose to disturb it.
Emergence Compose small petals. Shape arrives without being forced.
Transparency Every transformation is observable. Nothing is hidden in the mud.

A small bloom

From muddy input — a list of mixed records — a single ordered structure emerges. Read it the way one reads a haiku.

import { bloom, petal, pond } from 'lotus'

const garden = pond(rawEntries)
  .filter(petal.isValid)
  .map(petal.normalize)
  .reduce(bloom.byCategory, {})

// → { quiet: [...], deep: [...], still: [...] }

Three lines. One transformation. The mud settles below.

To begin

Install the library with a single line. There is no scaffolding, no configuration ceremony.

$ npm install lotus

Then sit, breathe, and write your first pond().

Five petals

The library is divided into five small modules, arranged like the petals of a single flower.

pond the source — a quiet, immutable starting point

petal small, pure transformations on a single value

stem composition — the line connecting petal to root

bloom aggregation — the moment shape arrives

ripple observation — gentle feedback for what just happened

A note on slowness

This page is intentionally unhurried. The spacing is wide. The lines are long. The animations are slow. We believe coding, at its best, is a contemplative act.

If you have arrived here looking for benchmarks and badges, you may find the rest of the internet better suited. If you have arrived looking for a quiet place to think about data, return to the pond.