Sunday, 27 February 2022

Org Documentor - (Some of) The Order of Execution


It's been a while since I made any changes to the Org Documentor, partly because I've been focused in other areas, and partly because I didn't need anything else documented. This changed with the Spring 22 release of Salesforce and the Flow Trigger Explorer

I really liked the idea of the explorer, but was disappointed that it showed inactive flows and didn't reflect the new ordering capabilities. Why didn't they add that, I wondered. How hard could it be? Then it occurred to me that I could handle this myself through the Org Documentor. It turns out I couldn't handle all aspects, but still enough to be useful. More on that later.

Flow Support

Up until now I hadn't got around to including flows in the generated documentation, and this clearly needed to change if I wanted to output the order they were executed in. 

As long as API version 54 is used, the execution order information comes back as expected, and getting these in the right order and handling collisions based on names is straightforward with a custom comparator function. Sadly I can't figure out the order when there is no execution information defined, as CreatedDate isn't available in the metadata. Two out of three ain't bad.

Order of Execution

As there are multiple steps in the order of execution, and most of those steps require different metadata, I couldn't handle it like I do other metadata. Simply processing the contents of a directory might help for one or two steps, but I wanted the consolidated view. To deal with this I create an order of execution data structure for each object that appears in the metadata, and gradually flesh this out as I process the various other types of metadata. So the objects add the validation rule information, triggers populate the before and after steps, as do flows. 

As everyone knows, there's a lot of steps in the order of execution, and I'm not attempting to support all of them right now. Especially as some of them (write to database but don't commit) don't have anything that metadata influences! Rather than trying to detail this in a blog post that I'd have to update every time I change anything, the order of execution page contains all the steps and adds badges to show which are possible to support, and which are supported:

As you can see, at the time of writing it's triggers and flows plus validation rules and roll up summaries. 

Steps where there is metadata that influences the behaviour appear in bold with a badge to indicate how many items there are. Clicking on the step takes you to the section that details the metadata:

You can see an example of the order of execution generated from the sample metadata at the Heroku site.

Updated Plug-in

Version 4.0.1 of the plug-in has this new functionality and can be found on NPM

If you already have the plug-in installed, just run sfdx plugins:update to upgrade to 4.0.1 - run sfdx plugins once you have done that to check the version.

The source code for the plug-in can be found in the Github repository.

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Saturday, 19 February 2022

Lightning Web Component Getters


When Lightning Web Components were released, one feature gap to Aura components I was pleased to see was the lack of support for expressions in the HTML template. 

Aura followed the trail blazed by Visualforce in allowing this, but if not used cautiously the expressions end up polluting the HTML making it difficult to understand. Especially for those that only write HTML, or even worse are learning it. Here's a somewhat redacted version from one of my personal projects from a few years ago:

Even leaving aside the use of i and j for iterator variables, it isn't enormously clear what name and lastrow will evaluate to.

Handling Expressions in LWC

One way to handle expressions is to enhance the properties that are being used in the HTML. In the example above, I'd process the ccs elements returned from the server and wrap them in an object that provides the name and lastrow properties, then change the HTML to iterate the wrappers and bind directly to those properties. All the logic sits where it belongs, server side. 

This technique also works for non-collection properties, but I tend to avoid that where possible. As components get more complex you end up with a bunch of properties whose sole purpose is to surface some information in the HTML and a fair bit of code to manage them, blurring the actual state of the component. 

The Power of the Getter

For single property values, getters are a better solution in many cases. With a getter you don't store a value, but calculate it on demand when a method is invoked, much like properties in Apex. The template can bind to a getter in the same way it can to a property, so there's no additional connecting up required.

The real magic with getters in LWC is they react to changes in the properties that they use to calculate their value. Rather than your code having to detect a change to a genuine state property and update avalue that is bound from the HTML, when a property that is used inside a getter changes, the getter is automatically re-run and the new value calculated and used in the template.

Here's a simple example of this - I have three inputs for title, firstname and lastname, and I calculate the fullname based on those values. My JavaScript maintains the three state properties and provides a getter that creates the fullname by concatenating the values:

export default class GetterExample extends LightningElement {

    titleChanged(event) {

    firstnameChanged(event) {

    lastnameChanged(event) {
    get fullname() {
        return this.title + ' ' + this.firstname + ' ' + this.lastname;

and this is used in my HTML as follows:

    <lightning-card title="Getter - Concatenate Values">
        <div class="slds-var-p-around_small">
                <lightning-input label="Title" type="text" value={title} onchange={titleChanged}></lightning-input>
                <lightning-input label="First Name" type="text" value={firstname} onchange={firstnameChanged}></lightning-input>
                <lightning-input label="Last Name" type="text" value={lastname} onchange={lastnameChanged}></lightning-input>
            <div class="slds-var-p-top_small">
                Full name : {fullname}

Note that I don't have to do anything to cause the fullname to rerender when the user supplies a title, firstname or lastname. The platform detects that those properties are used in my getter and automatically calls it when they change. This saves me loads of code compared to aura.

You can also have getters that rely on each other and the whole chain gets re-evaluated when a referenced property changes. Extending my example above to use the fullname in a sentence:

get sentence() {
    return this.fullname + ' built a lightning component';

and binding directly to the setter:

<div class="slds-var-p-top_small">
    Use it in a sentence : {sentence}

and as I complete the full name, the sentence is automatically calculated and rendered, even though I'm only referencing another getter that was re-evaluated:

You can find the component in my lwc-blogs repository at :

Another area that Lightning Web Components score in is they are built on top of web standards, so if I want to change values that impact getters outside of the user interactions, I can use a regular setinterval  rather than having to wrap it inside a $A.getCallback function call, as my next sample shows:

In this case there is a countdown property that is calculated based on the timer having been started and not expiring, and an interval timer that counts down to zero and then cancels itself:


startCountdown() {
    this.interval=setInterval(() => {
        if (this.timer==0) {
    }, 1000);

get countdown() {
    let result='Timer expired';
    if (null==this.interval) {
        result='Timer not started';
    else if (this.timer>0) {
        result=this.timer + ' seconds to go!';

    return result;
and once again, I can just bind directly to the getter in the certainty that if the interval is populated or the timer changes, the UI will change with no further involvement from me.
<div class="slds-var-p-top_medium">
    <div class={countdownClass}>{countdown}</div>

Note that I'm also using a getter to determine the colour that the countdown information should be displayed in, removing more logic that would probably be in the view if using Aura:

You can also find this sample in the lwc-blogs repo at :

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Sunday, 6 February 2022

Flow Collection Filter Element in Spring 22


One of the many new flow features introduced in Spring 22 is the Collection Filter - this processes a collection applying filter conditions and creates a new collection containing only those elements that match the filter, similar to a reducer from JavaScript. This seemed like something that would save a considerable amount of effort compared to manually iterating the collection myself and applying a decision to each element. But how much effort I wondered? As Peter Drucker may have famously said, "If you can't measure it, you can't manage it", or in this case, if you can't measure it you don't know whether it is any better.

Working with Salesforce at Enterprise scale often turns into a battle of Man V CPU, so I decided to measure the impact of switching to this approach in flow, and how carrying out the same processing in Apex performed. 

The Challenge

The scenario was very (unrealistically) simple - query the Id and Forecast Category field for all opportunities from the database, create a new collection with just those in the Best Case forecast category. I used a random number generator to pick the stage for each opportunity created, and each of manual iteration, Collection Filter and Apex ran on the same set of opportunities. 

Each method of processing was run three times in no particular order to try to mitigate the impact of caching, but as usual with this kind of testing, your mileage may vary enormously depending on what else is going on.

The Results

The results were as follows:

Opportunity Count Manual Iteration Collection Filter Apex
500 480 90 20
1000 N/A 90 20
2000 N/A 116 36
3000 N/A 279 44
4000 N/A 397 65
5000 N/A 500 80
10000 N/A 850 151

One clear benefit of using the Collection Filter is the manual iteration tops out somewhere between 500 and 1000 records, breaching the number of executed elements of 2000, whereas the Collection Filter keeps going to the 10000 record limit that I imposed.

The filter approach is also about 5x more efficient in terms of CPU usage, although Apex is in turn 5x as efficient as the filter, but in all honesty if you are trying to wring every last millisecond of CPU out of a transaction involving thousands of records, flow won't be your first choice tool.

It's also good to see that the filter approach scales fairly linearly - somewhere between 80-100 msec per 1000 records, versus the 15-20 msec per 1000 records for Apex.

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