crosslink
A spreadsheet cell microlibrary inspired by arrowized Functional Reactive Programming
Last updated 3 years ago by plotly .
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crosslink.js

A compact and fast data propagation core for use with higher level libraries or reactive programming directly. Under development, the API is still evolving.

Install:

npm install crosslink

or clone, npm install and npm build this package, then use the bundle as a script (see the examples directory).

Goals:

  • suitable for linking input, calculation and rendering components
  • small footprint (around 1kB minified and gzipped)
  • small API, focusing on the lift operation
  • fast, with lots of headroom
  • predictable
  • glitch free
  • also suitable for asynchronous updates
  • reasonably safe and debuggable
  • covered with test cases

The library implements the spreadsheet model. Cells can be created explicitly, and values can be put in source cells directly. But the real power comes from the spreadsheet formulas, technically, the lift operator, which takes a plain function eg. (a, b) => a + b and yields a lifted function, in this case, a function that makes a cell whose value is the sum of the values of two referenced cells. A lifted function can be used to make one or more cells in the spreadsheet. Unneeded cells can also be removed. The spreadsheet model is temporal: certain API functions rely on past values of the cell (scan), impact future values (delay) or mirror values from multiple cells (merge).

Example:

import _ from 'crosslink'

const cellA = _.cell('our cell A')
const cellB = _.cell('our cell B')

const adder = (a, b) => a + b
const logger = x => { console.log('The cell value is', x) }

const liftedAdder = _.lift(adder)
const liftedLogger = _.lift(logger)

const c = liftedAdder(cellA, cellB)
liftedLogger(c)

_.put(cellA, 3)
    // nothing happens

_.put(cellB, 6)
    // The cell value is 9

_.put(cellA, 2)
    // The cell value is 8

The cells need to be managed as resources: if they're generated continuously or upon incoming data, they need to be removed to avoid memory leaks. Even if the cells are established once on an initial execution and there is no subsequent cell creation, the cells remain operational even after they are not actually used, for example, if the DOM elements they influence had been removed from the document DOM - potentially expensive calculations continue to run on each input update, which may be left in by accident, and the DOM nodes may be prevented from garbage collection by the cell function continuing to hold a reference to them.

The dependency links among cells form a directed acyclic graph. Following the spreadsheet model - which is, at its core, a directed acyclic graph -, it uses topological sorting to propagate updates to dependencies (cells downstream in the DAG), as commonly done in the case of spreadsheets.

It is possible for a DAG to have a node that depend on some upstream node through different paths. For example, B and C both depend on A, and D depends on both of B and C, therefore an update to A will reach D in two 'waves'. This is prone to cause glitches as D will be inconsistent for a brief moment, before the second update. These glitches are avoided by invalidating all direct and indirect dependencies first; in the second step, values are propagated, and D will only be recomputed once it got sufficient input i.e. when it also got even the last piece input stemming from updating A.

It is possible for a cell update function to put a value in any cell, but if the data propagation from that cell causes a recalculation of the initiating cell, a circularity error will be signaled.

The speed and predictable updates are due to synchronous operations. Data are propagated in the DAG synchronously. By consequence, to avoid UI lock-up, long-running cell operations are best done asynchronously, e.g. in a setTimeout, Web Worker, or some method of incremental recalculation. Currently, the output of the asynchronously scheduled operation needs to update a cell different from the one doing the scheduling, but this restricion might be lifted in the future.

Compact size is achieved by relying on no dependencies and trying to capture a minimal set of functions, from which useful functionality can be composed. The primary method of composition is the use of lift, which is currently suitable for stateless calculations. Currently, few other operators are supported: scan, merge and delay. New functionality will be added as needed.

Note to users of observables libraries: The cells are analogous to hot observables in that creating a cell will not cause the reexecution of code upstream in the DAG. For example, a new cell that has the result of AJAX calls as an upstream will not cause a new AJAX request. Features analogous to cold observables can currently only be emulated, for example, by using factory functions or retaining the history of the downstream cells for replay.

More mature libraries with generally broader scope, a diversity of objectives and various overlaps with crosslink functionality (and one another):

  • flyd which, being closest in goals, was also an inspiration
  • xstream has a carefully crafted API and commented source
  • most focuses on async operations and fast at that
  • RxJS where it started in JS land
  • MobX a more magical take on data propagation
  • Redux predictable state container, and scan on steroids

Links:

  • The Essence and Origins of Functional Reactive Programming is the vision relative to which this library and other JavaScript libraries are overly operational, less declarative, and leave the continuity of time as an exercise to the user. It is possible to sample, integrate and differentiate variables that are considered continuous, for example, by implementing a backward looking five point stencil to numerically differentiate values, for example, for modeling pointer speed. Modeling with continuous time might be a future abstraction.
  • RxMarbles by André Staltz is a wonderful resource for visualizing events and data propagation across time. Several current and future crosslink operations are covered.

The library name is a nod to crossfilter.js, linked brushing and crosstalk as crosslink will be a basis for related functionality.

API

Generally, all kinds of values can be propagated except, currently, undefined, which now represents an invalid status. In the future, the notion of an invalid state - e.g. due to not having received all input yet - might be separated from the concept ofundefined although it arguably represents the concept of not having been defined.

Prefer the use of named functions, for example, defined as function myFun() {} or const myFun = () => {} so that the function name is available when debugging cell-based code.

# _.cell([alias])

Creates an input cell. Use:

const age = _.cell('age')

The result is a cell. The input cell can be depended on by calculated cells. The optional alias must be a string and helps debug cells, which inevitably arises.

# _.put(cell, value)

Puts a value in an input cell. Dependent cells will be synchronously updated. It is commonly done inside event handlers, for example, to put mouse position continuously in a cell, or to update a cell from streaming data from WebSockets. Use:

_.put(age, 5)

# _(function)

Shorthand for the _.lift(function) - it's encouraged to use it as a lightweight notation for constructing function cells.

A spreadsheet cell that contains a formula. Lifts the supplied function to operate on cells. The function must have a fixed arity (curried functions are fine). If the function takes n arguments, then the result, the lifted function, will also take n arguments. Each of those arguments can be, but does not have to be, a cell.


const bmiFormulaSI = (w, h) => w / (h * h)
const bmiLogger = d => console.log('The BMI value is', d)

const weightKilograms = _.cell()
const heightMeters = _.cell()

const bmi = _(bmiFormulaSI)(weightKilograms, heightMeters)

_(bmiLogger)(bmi)

_.put(heightMeters, 1.83)
_.put(weightKilograms, 80)
/* The BMI value is 23.888 */

// ... dinner happens ...

_.put(weightKilograms, 81)
/* The BMI value is 24.187 */

This syntax is closer to the clutter-free mathematical notation than e.g. using crosslink.lift(function).

While it's good practice to lift pure functions, they may also cause side effects, for example, changing some attribute of a DOM element. The side effecting cells are best done as leaf (or sink) nodes in the DAG. There may be good reasons for making other nodes have side effect, e.g. for logging data that flows through for debugging, for caching an expensive calculation or for initiating a calculation asynchronously, e.g. in a Web Worker. As this is a low level library, a future higher level API layer may have dedicated primitives or plugins for capturing DOM events, making changes, scheduling work, LRU caching etc.

# _.lift(function)

See the previous entry.

# _.reduce(function)

Analogous to Array.prototype.reduce in that it acts as a reducer, and the first argument of the supplied function carries the previous value. Unlike Array.prototype.reduce however it supports an arbitrary number of subsequent arguments. If any of these input values change, the function will be rerun with its previous value (if any) and the current arguments. An initial value for previous can be supplied via the ES2015 default value. Example:

const numbers = _.cell('numbers streamed in')
const runningTotal = _.reduce((previousSum = 0, newValue) => previousSum + newValue)(numbers)
_.lift(sum => console.log(sum))(runningTotal)
_.put(numbers, 24)
_.put(numbers, 72)

# _.scan(function, initialValue, cell)

Accumulates values based on cell, similar to JavaScript reduce. The supplied function must have two arguments prev and next (can be named differently) such that the accumulating value - which is initially set to initialValue - will be prev, and the new input from the cell cell is the value next. Example:

const click = _.cell('mouseClick')
const clickCount = _.scan((prev, next) => prev + next, 0, click)
_.put(click, true)

# _.merge(cell1, cell2)

Results a cell that merges the values from two cells. Example:

const click = _.cell('mouse click')
const tap = _.cell('finger tap')
const activate = _.merge(click, tap)

# _.delay(delayInMs, cell)

Results a cell that is a delayed version of the supplied cell by delayInMs milliseconds. Example:

const finishSignal = _.delay(300, startSignal)

# _.remove(cell)

Removes a cell from the DAG. Its lifted function will not be called again even if its former upstream cells change. Not only the cell is removed, but also, the DAG is pruned:

  • all downstream cells are recursively removed as they can no longer receive updates
  • all upstream cells are recursively removed that only served this cell being removed
    • by extension, the downstream of removed upstream cells are also removed, and
    • the upstreams of downstream cells are also pruned

Naturally, only those upstreams are removed which don't have, or no longer have other uses (direct sinks) downstream.

As a consequence, ensure that a permanent cell that may have removed downstream cells is _.retained. Such cells are typically part of a data model or view model that need to be present even if there is no data point to render at the moment.

# _.retain(cell)

Retains a cell which would otherwise be subject to pruning (recursive cell removal) in case a downstream cell is removed.

For example:

  • there is some model or view model cell carrying aggregate data, config etc. i.e. that need to be there, whether there is some number of data points currently rendered or not
  • a downstream (sink, leaf) cell is responsible for updating a DOM element that corresponds to a data point - let's assume it's the only data point
  • removing that data point, and freeing up the DOM element modifier cell with a remove will cause upstream cells to also be removed
  • if the model / view model cell is protected with a _.retain(viewModelCell) then it will not be pruned, and newly arriving data points can render (which needs the model / view model cell to function)

Manual resource management, i.e. calling remove on a retained cell (or one of its direct or indirect sources) is necessary even if its usages are removed, as there's no automatic pruning from the downstream. A problematic memory leak may occur if retained cells are not removed eventually. Consequently, ensure that _.retain is used only as needed and such cells are freed up once they're of no use.

Calling _.retain does not affect terminal sinks, as those nodes have no downstreams, i.e. pruning can not propagate to them in an upwards direction. Such cells can be removed either directly, or by removing one of their direct or indirect sources, in which case retain is not going to block pruning (removal) anyway. Wrapping is still advised with such cells as it's easy to search the source code for places where memory may leak, and such terminal sinks are the riskiest cells because they typically effect HTML nodes etc. which can get created prolifically but eventually get removed from the DOM. As it's crucial to free up such terminal sinks (in part, to release the reference to removed HTML elements ec.) and prune their upstreams after disuse (e.g. DOM element removal), using retain is an easy to search warning sign for untied loose ends. Library abstractions over crosslink don't need to do this wrapping if they automatically manage removal (eg. doing it together with the DOM element removal).

Not using retain is not going to prevent memory leaks. Pruning only happens when a cell is removed, and only impacts the cells that can be reached downstream (all of them) and upstream (those not protected with retain), and their downstreams and unprotected upstreams recursively. Therefore, the only purpose of pruning is to make resource management easier, as typically, only terminal sinks and retained cells will need to be explicitly deleted.

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