Peterbe.com

React Hooks isn't here yet but when it comes I'll be all over that, replacing many of my classes with functions.

However, as of React 16.6 there's this awesome new React.memo() thing which is such a neat solution. Why didn't I think of that, myself, sooner?!

Anyway, one of the subtle benefits of it is that writing functions minify a lot better than classes when Babel'ifying your ES6 code.

To test that, I took one of my project's classes, which needed to be "PureComponent":

class ShowAutocompleteSuggestionSong extends React.PureComponent {
  render() {
    const { song } = this.props;
    return (
      <div className="media autocomplete-suggestion-song">
        <div className="media-left">
          <img
            className={
              song.image && song.image.preview
                ? 'img-rounded lazyload preview'
                : 'img-rounded lazyload'
            }
            src={
              song.image && song.image.preview
                ? song.image.preview
                : placeholderImage
            }
            data-src={
              song.image ? absolutifyUrl(song.image.url) : placeholderImage
            }
            alt={song.name}
          />
        </div>
        <div className="media-body">
          <h5 className="artist-name">
            <b>{song.name}</b>
            {' by '}
            <span>{song.artist.name}</span>
          </h5>
          {song.fragments.map((fragment, i) => {
            return <p key={i} dangerouslySetInnerHTML={{ __html: fragment }} />;
          })}
        </div>
      </div>
    );
  }
}

Minified it weights 1,893 bytes and looks like this:

Minified PureComponent class

When re-written with React.memo it looks like this:

const ShowAutocompleteSuggestionSong = React.memo(({ song }) => {
  return (
    <div className="media autocomplete-suggestion-song">
      <div className="media-left">
        <img
          className={
            song.image && song.image.preview
              ? 'img-rounded lazyload preview'
              : 'img-rounded lazyload'
          }
          src={
            song.image && song.image.preview
              ? song.image.preview
              : placeholderImage
          }
          data-src={
            song.image ? absolutifyUrl(song.image.url) : placeholderImage
          }
          alt={song.name}
        />
      </div>
      <div className="media-body">
        <h5 className="artist-name">
          <b>{song.name}</b>
          {' by '}
          <span>{song.artist.name}</span>
        </h5>
        {song.fragments.map((fragment, i) => {
          return <p key={i} dangerouslySetInnerHTML={{ __html: fragment }} />;
        })}
      </div>
    </div>
  );
});

Minified it weights 783 bytes and looks like this:

Minified React.memo function

Highly scientific measurement. Yeah, I know. (Joking)
Perhaps it's stating the obvious but part of the ES5 code that it generates, from classes can be reused for other classes.

Anyway, it's neat and worth considering to squeeze some bytes out. And the bonus is that it gets you prepared for Hooks in React 16.7.

If you're reading this, you might have thought one of two thoughts about this blog post title (or both); "Cool buzzwords!" or "Yuck! So much hyped buzzwords!"

Either way, React v16.6 came out a couple of days ago and it brings with it React.lazy: Code-Splitting with Suspense.

React.lazy is React's built-in way of lazy loading components. With Suspense you can make that lazy loading be smart and know to render a fallback component (or JSX element) whilst waiting for that slowly loading chunk for the lazy component.

The sample code in the announcement was deliciously simple but I was curious; how does that work with react-router-dom??

Without furher ado, here's a complete demo/example. The gist is an app that has two sub-components loaded with react-router-dom:

<Router>
  <div className="App">
    <Switch>
      <Route path="/" exact component={Home} />
      <Route path="/:id" component={Post} />
    </Switch>
  </div>
</Router>

The idea is that the Home component will list all the blog posts and the Post component will display the full details of that blog post. In my demo, the Post component never bothers to actually do the fetching of the full details to display. It just displays the passed in ID from the react-router-dom match prop. You get the idea.

That's standard React with react-router-dom stuff. Next up, lazy loading. Basically, instead of importing the Post component, you make it lazy:

-import Post from "./post";
+const Post = React.lazy(() => import("./post"));

And here comes the magic sauce. Instead of referencing component={Post} in the <Route/> you use this badboy:

function WaitingComponent(Component) {
  return props => (
    <Suspense fallback={<div>Loading...</div>}>
      <Component {...props} />
    </Suspense>
  );
}

Complete prototype

The final thing looks like this:

import React, { lazy, Suspense } from "react";
import ReactDOM from "react-dom";
import { MemoryRouter as Router, Route, Switch } from "react-router-dom";

import Home from "./home";
const Post = lazy(() => import("./post"));

function App() {
  return (
    <Router>
      <div className="App">
        <Switch>
          <Route path="/" exact component={Home} />
          <Route path="/:id" component={WaitingComponent(Post)} />
        </Switch>
      </div>
    </Router>
  );
}

function WaitingComponent(Component) {
  return props => (
    <Suspense fallback={<div>Loading...</div>}>
      <Component {...props} />
    </Suspense>
  );
}

const rootElement = document.getElementById("root");
ReactDOM.render(<App />, rootElement);

(sorry about the weird syntax highlighting with the red boxes.)

And it totally works! It's hard to show this with the demo but if you don't believe me, you can download the whole codesandbox as a .zip, run yarn && yarn run build && serve -s build and then you can see it doing its magic as if this was the complete foundation of a fully working client-side app.

1. Loading the "Home" page, then click one of the links

2. Lazy loading the Post component

3. Post component lazily loaded once and for all

Bonus

One thing that can happen is that you might load the app when the Wifi is honky dory but when you eventually make a click that causes a lazy loading to actually need to go out on the Internet and download that .js file it might fail. For example, because the file has been removed from the server or your network just fails for some reason. To deal with that, simply wrap the whole <Suspense> component in an error boundary component.

See this demo which is a fork of the main demo but with error boundaries added.

In conclusion

No surprise that it works. React is pretty awesome. I just wasn't sure how it would look like with react-router-dom.

A word of warning, from the v16.6 announcement: "This feature is not yet available for server-side rendering. Suspense support will be added in a later release."

I think lazy loading isn't actually that big of a deal. It's nice that it works but how likely is it really that you have a sub-tree of components that is so big and slow that you can't just pay for it up front as part of one big fat build. If you really care about a really great web performance for those people who reach your app rarely and sporadically, the true ticket to success is server-side rendering and shipping a gzipped HTML document with all the React client-side code non-blocking rendering so that the user can download the HTML, start reading/consuming it immediately and then whilst the user is doing that you download the rest of the .js that is going to be needed once the user clicks around. Start there.

I'm in the midst of rewriting a big app that currently uses AWS S3 and will soon be switched over to Google Cloud Storage. This blog post is a rough attempt to log various activities in both Python libraries:

Disclaimer: I'm manually copying these snippets from a real project and I have to manually scrub the code clean of unimportant quirks, hacks, and other unrelated things that would just add noise.

Install

boto3

$ pip install boto3
$ emacs ~/.aws/credentials

google-cloud-storage

$ pip install google-cloud-storage
$ cat ./google_service_account.json

Note: You need to create a service account and then that gives you a .json file which you download and make sure you pass its path when you create a client.

I suspect there are more/other ways to do this with environment variables alone but I haven't got there yet.

Making a "client"

boto3

Note, there are easier shortcuts for this but with this pattern you can have full control over things like like read_timeout, connect_timeout, etc. with that confi_params keyword.

import boto3
from botocore.config import Config


def get_s3_client(region_name=None, **config_params):
    options = {"config": Config(**config_params)}
    if region_name:
        options["region_name"] = region_name
    session = boto3.session.Session()
    return session.client("s3", **options)

google-cloud-storage

from google.cloud import storage


def get_gcs_client():
    return storage.Client.from_service_account_json(
        settings.GOOGLE_APPLICATION_CREDENTIALS_PATH
    )

Checking if a bucket exists and if you have access to it

boto3 (for s3_client here, see above)

from botocore.exceptions import ClientError, EndpointConnectionError


try:

    s3_client.head_bucket(Bucket=bucket_name)
except ClientError as exception:
    if exception.response["Error"]["Code"] in ("403", "404"):
        raise BucketHardError(
            f"Unable to connect to bucket={bucket_name!r} "
            f"ClientError ({exception.response!r})"
        )
    else:
        raise
except EndpointConnectionError:
    raise BucketSoftError(
        f"Unable to connect to bucket={bucket.name!r} "
        f"EndpointConnectionError"
    )
else:
    print("It exists and we have access to it.")

google-cloud-storage

from google.api_core.exceptions import BadRequest


try:
    gcs_client.get_bucket(bucket_name)
except BadRequest as exception:
    raise BucketHardError(
        f"Unable to connect to bucket={bucket_name!r}, "
        f"because bucket not found due to {exception}"
    )
else:
    print("It exists and we have access to it.")

Checking if an object exists

boto3

from botocore.exceptions import ClientError


def key_existing(client, bucket_name, key):
    """return a tuple of (
        key's size if it exists or 0,
        S3 key metadata
    )
    If the object doesn't exist, return None for the metadata.
    """
    try:
        response = client.head_object(Bucket=bucket_name, Key=key)
        return response["ContentLength"], response.get("Metadata")
    except ClientError as exception:
        if exception.response["Error"]["Code"] == "404":
            return 0, None
        raise

Note, if you do this a lot and often find that the object doesn't exist the using list_objects_v2 is probably faster.

google-cloud-storage

def key_existing(client, bucket_name, key):
    """return a tuple of (
        key's size if it exists or 0,
        S3 key metadata
    )
    If the object doesn't exist, return None for the metadata.
    """
    bucket = client.get_bucket(bucket_name)
    blob = bucket.get_blob(key)
    if blob:
        return blob.size, blob.metadata
    return 0, None

Uploading a file with a special Content-Encoding

Note: You have to use your imagination with regards to the source. In this example, I'm assuming that the source is a file on disk and that it might have already been compressed with gzip.

boto3

def upload(file_path, bucket_name, key_name, metadata=None, compressed=False):
    content_type = get_key_content_type(key_name)

    metadata = metadata or {}

    # boto3 will raise a botocore.exceptions.ParamValidationError
    # error if you try to do something like:
    #
    #  s3.put_object(Bucket=..., Key=..., Body=..., ContentEncoding=None)
    #
    # ...because apparently 'NoneType' is not a valid type.
    # We /could/ set it to something like '' but that feels like an
    # actual value/opinion. Better just avoid if it's not something
    # really real.
    extras = {}
    if content_type:
        extras["ContentType"] = content_type
    if compressed:
        extras["ContentEncoding"] = "gzip"
    if metadata:
        extras["Metadata"] = metadata

     with open(file_path, "rb") as f:
         s3_client.put_object(Bucket=bucket_name, Key=key_name, Body=f, **extras)

google-cloud-storage

def upload(file_path, bucket_name, key_name, metadata=None, compressed=False):
    content_type = get_key_content_type(key_name)

    metadata = metadata or {}
    bucket = gcs_client.get_bucket(bucket_name)
    blob = bucket.blob(key_name)

    if content_type:
        blob.content_type = content_type
    if compressed:
        blob.content_encoding = "gzip"
    blob.metadata = metadata
    blob.upload_from_file(f)

Downloading and uncompressing a gzipped object

boto3

from io import BytesIO
from gzip import GzipFile
from botocore.exceptions import ClientError

from .utils import iter_lines


def get_stream(bucket_name, key_name):
    try:
        response = source.s3_client.get_object(
            Bucket=bucket_name, Key=key
        )
    except ClientError as exception:
        if exception.response["Error"]["Code"] == "NoSuchKey":
            raise KeyHardError("key not in bucket")
        raise

    stream = response["Body"]
    # But if the content encoding is gzip we have re-wrap the stream.
    if response.get("ContentEncoding") == "gzip":
        body = response["Body"].read()
        bytestream = BytesIO(body)
        stream = GzipFile(None, "rb", fileobj=bytestream)

    for line in iter_lines(stream):
        yield line.decode("utf-8")

google-cloud-storage

from io import BytesIO
from gzip import GzipFile
from botocore.exceptions import ClientError

from .utils import iter_lines


def get_stream(bucket_name, key_name):
    bucket = gcs_client.get_bucket(bucket_name)
    blob = bucket.get_blob(key)
    if blob is None:
        raise KeyHardError("key not in bucket")

    bytestream = BytesIO()
    blob.download_to_file(bytestream)
    bytestream.seek(0)

    for line in iter_lines(bytestream):
        yield line.decode("utf-8")

Note! That here blob.download_to_file works a bit like requests.get() in that it automatically notices the Content-Encoding metadata and does the gunzip on the fly.

Conclusion

It's not fair to compare them on style because I think boto3 came out of boto which probably started back in the day when Google was just web search and web emails.

I wanted to include a section about how to unit test against these, especially how to mock them. But what I had for a draft was getting ugly. Yes, it works for the testing needs I have in my app but it's very personal taste (aka. appropriate for the context) and admittedly quite messy.

Bleach is awesome. Thank you for it @willkg! It's a Python library for sanitizing text as well as "linkifying" text for HTML use. For example, consider this:

>>> import bleach
>>> bleach.linkify("Here is some text with a url.com.")
'Here is some text with a <a href="http://url.com" rel="nofollow">url.com</a>.'

Note that sanitizing is separate thing, but if you're curious, consider this example:

>>> bleach.linkify(bleach.clean("Here is <script> some text with a url.com."))
'Here is &lt;script&gt; some text with a <a href="http://url.com" rel="nofollow">url.com</a>.'

With that output you can confidently template interpolate that string straight into your HTML.

Getting fancy

That's a great start but I wanted a more. For one, I don't always want the rel="nofollow" attribute on all links. In particular for links that are within the site. Secondly, a lot of things look like a domain but isn't. For example This is a text.at the start which would naively become...:

>>> bleach.linkify("This is a text.at the start")
'This is a <a href="http://text.at" rel="nofollow">text.at</a> the start'

...because text.at looks like a domain.

So here is how I use it here on www.peterbe.com to linkify blog comments:

def custom_nofollow_maker(attrs, new=False):
    href_key = (None, u"href")

    if href_key not in attrs:
        return attrs

    if attrs[href_key].startswith(u"mailto:"):
        return attrs

    p = urlparse(attrs[href_key])
    if p.netloc not in settings.NOFOLLOW_EXCEPTIONS:
        # Before we add the `rel="nofollow"` let's first check that this is a
        # valid domain at all.
        root_url = p.scheme + "://" + p.netloc
        try:
            response = requests.head(root_url)
            if response.status_code == 301:
                redirect_p = urlparse(response.headers["location"])
                # If the only difference is that it redirects to https instead
                # of http, then amend the href.
                if (
                    redirect_p.scheme == "https"
                    and p.scheme == "http"
                    and p.netloc == redirect_p.netloc
                ):
                    attrs[href_key] = attrs[href_key].replace("http://", "https://")

        except ConnectionError:
            return None

        rel_key = (None, u"rel")
        rel_values = [val for val in attrs.get(rel_key, "").split(" ") if val]
        if "nofollow" not in [rel_val.lower() for rel_val in rel_values]:
            rel_values.append("nofollow")
        attrs[rel_key] = " ".join(rel_values)

    return attrs

html = bleach.linkify(text, callbacks=[custom_nofollow_maker])

This basically taking the default nofollow callback and extending it a bit.

By the way, here is the complete code I use for sanitizing and linkifying blog comments here on this site: render_comment_text.

Caveats

This is slow because it requires network IO every time a piece of text needs to be linkified (if it has domain looking things in it) but that's best alleviated by only doing it once and either caching it or persistently storing the cleaned and rendered output.

Also, the check uses try: requests.head() except requests.exceptions.ConnectionError: as the method to see if the domain works. I considered doing a whois lookup or something but that felt a little wrong because just because a domain exists doesn't mean there's a website there. Either way, it could be that the domain/URL is perfectly fine but in that very unlucky instant you checked your own server's internet or some other DNS lookup thing is busted. Perhaps wrapping it in a retry and doing try: requests.head() except requests.exceptions.RetryError: instead.

Lastly, the business logic I chose was to rewrite all http:// to https:// only if the URL http://domain does a 301 redirect to https://domain. So if the original link was http://bit.ly/redirect-slug it leaves it as is. Perhaps a fancier version would be to look at the domain name ending. For example HEAD http://google.com 301 redirects to https://www.google.com so you could use the fact that "www.google.com".endswith("google.com").

UPDATE Oct 10 2018

Moments after publishing this, I discovered a bug where it would fail badly if the text contained a URL with an ampersand in it. Turns out, it was a known bug in Bleach. It only happens when you try to pass a filter to the bleach.Cleaner() class.

So I simplified my code and now things work. Apparently, using bleach.Cleaner(filters=[...]) is faster so I'm losing that. But, for now, that's OK in my context.

Also, in another later fix, I improved the function some more by avoiding non-HTTP links (with the exception of mailto: and tel:). Otherwise it would attempt to run requests.head('ssh://server.example.com') which doesn't make sense.

tl;dr; Use --runInBand when running jest in CI and use --maxWorkers=3 on your laptop.

We have a test suite that covers 236 tests across 68 suites and runs mainly a bunch of enzyme rendering of React component but also some plain old JavaScript function tests. We hit a problem where tests utterly failed in CircleCI due to running out of memory. Several individual tests, before it gave up or failed, reported to take up to 45 seconds.
Turns out, jest tried to use 36 workers because the Docker OS it was running was reporting 36 CPUs.

> circleci@9e4c489cf76b:~/repo$ node
> var os = require('os')
undefined
> os.cpus().length
36

After forcibly setting --maxWorkers=2 to the jest command, the tests passed and it took 20 seconds. Yay!

But that got me thinking, what is the ideal number of workers when I'm running the suite here on my laptop? To find out, I wrote a Python script that would wrap the call CI=true yarn run test --maxWorkers=%(WORKERS) repeatedly and report which number is ideal for my laptop.

After leaving it running for a while it spits out this result:

SORTED BY BEST TIME:
3 8.47s
4 8.59s
6 9.12s
5 9.18s
2 9.51s
7 10.14s
8 10.59s
1 13.80s

The conclusion is vague. There is some benefit to using some small number greater than 1. If you attempt a bigger number it might backfire and take longer than necessary and if you do do that your laptop is likely to crawl and cough.

Notes and conclusions

• Doing --runInBand is the same as --maxWorkers=1 apparently.
• @thymikee, a core jest contributor suggests to use --runInBand in CI.
• The times might not matter much because on your laptop you probably use --watch with a filter anyway.
• If someone feels productive, please copy my Python script and run it inside a Docker container in CircleCI and report their findings.

UPDATE (1)

My understanding of how to generate the CSP nonces was wrong. What I initially posted was a confusion between nonces and hashes. Sorry. The blog post has been updated to use hashing.

UPDATE (2)

Shortly after publishing this I changed my mind entirely. I decided I don't want any inline scripts no matter how small. Reasons are: 1) with HTTP2 it's cheap to send another file and thus that critical precious first HTML document becomes smaller and 2) when you load it as an external you have the power to load it async if it's applicable.

Check out this new script, it's hackish but works: uninline_scripts.js

UPDATE (Oct 18, 2018)

If you use INLINE_RUNTIME_CHUNK=false yarn run build no scripts, independent of size, are inlined. See this pull request for details.

END UPDATES

I have an app that is hosted on github-pages and because I can't control Content Security Policy HTTP headers I have to do it with a <meta http-equiv="Content-Security-Policy" content="${csp}"> tag in the HTML. That's working fine and the way I do it is that I have a script that looks like this:

#!/usr/bin/env node
const fs = require("fs");
const crypto = require("crypto");

const CSP_TEMPLATE = `
default-src 'none';
connect-src 'self' kinto.workon.app peterbecom.auth0.com;
frame-src peterbecom.auth0.com;
img-src 'self' avatars2.githubusercontent.com https://*.googleusercontent.com;
script-src 'self'%SCRIPT_HASHES%;
style-src 'self' 'unsafe-inline';
font-src 'self' data:;
manifest-src 'self'
`.trim();

const htmlFile = process.argv[2];
if (!htmlFile) throw new Error("missing file argument");
let html = fs.readFileSync(htmlFile, "utf8");

let hashes = "";
let csp = CSP_TEMPLATE;
const matches = html.match(/<script>.*<\/script>/g);
if (matches) {
  matches.forEach(scriptTag => {
    const hash = crypto.createHash("sha256");
    hash.update(scriptTag.replace(/<script>/, "").replace("</script>", ""));
    const digest = hash.digest("hex");
    hashes += ` 'sha256-${digest.toString("base64")}'`;
  });
}
csp = csp.replace(/%SCRIPT_HASHES%/, hashes);

const metatag = `
  <meta http-equiv="Content-Security-Policy" content="${csp}">
`
  .replace(/\n/g, "")
  .trim();
if (html.search(metatag) > -1)
  throw new Error("already has CSP metatag in HTML");
const anchor = '<meta charset="utf-8">';
const newHtml = html.replace(anchor, `${anchor}${metatag}`);
fs.writeFileSync(htmlFile, newHtml, "utf8");

Laugh all you like at my hurried node scripting but it works. It finds any <script>ANYTHING</script> tags (which means it disregards any <script src="... tags), calculates a sha256 hash string out of it and then puts that into the CSP block.

The output becomes something like this:

<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="utf-8">
    <meta 
      http-equiv="Content-Security-Policy" 
      content="default-src 'none';script-src 'self' 'sha256-bb84aa7f904e73495b9e99f08531053f3a86f3c1b2e232e3abbac252bf723f1f';">
  </head>
  <body>
    ...
    <script>....</script>
  </body>
</html>

I don't know if I've done it right but at least what didn't use to work now works; the page loads in my browsers now.

I found this in an issue discussing measuring page performance with puppeteer and it's pure gold. Especially because it's so accessible and easy to use.

Here's the code:

const puppeteer = require('puppeteer');

async function run() {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();

  await page.goto('https://www.peterbe.com/');

  console.log('\n==== performance.getEntries() ====\n');
  console.log(
    await page.evaluate(() =>
      JSON.stringify(performance.getEntries(), null, '  ')
    )
  );

  console.log('\n==== performance.toJSON() ====\n');
  console.log(
    await page.evaluate(() => JSON.stringify(performance.toJSON(), null, '  '))
  );

  console.log('\n==== page.metrics() ====\n');
  const perf = await page.metrics();
  console.log(JSON.stringify(perf, null, '  '));

  browser.close();
}

run();

When you run it you get this output: https://gist.github.com/peterbe/afb09bf9277e5fa9242f8d270c687640
To run it you need to have a decently up-to-date version of puppeteer installed.

I don't claim (far from it actually!) to understand all the metrics points in there but I believe this is basically what the Network panel in the Google Chrome Dev tools is built upon. But some details and facts are easy to figure out and use in your analysis. For example, the fact that the getEntries() lists all the resources that had to be downloaded in the order they were downloaded. Also, at the end of getEntries() you get the first-paint which is often a useful metric.

Anyway, give it a spin. Wrap this up in a platform and see if you can build something really simple and really tailored to your web projects web performance testing.

Here's how you do it if you don't care about the order:

const array1 = [1, 2, 3];
const array2 = [2, 3, 4];
console.log([...new Set([...array1, ...array2])]);
// prints [1, 2, 3, 4]

It merges two arrays first. Then it creates a set out of that merged array and lastly convers the set back out to an array.

I searched for a solution and all I found was dated or wrong. This oneliner works and I'm using it to make it possible to add a list of product versions to another list and I don't want to mutate existing arrays because of React state stuff.

If you want to see the ES5 version, check out this Babel repl.

Demo here. The demo uses React and a list of blog post titles that get immediately filtered when you type in a search. I.e. you have the whole list but show less when a search term is entered.

That the demo uses React isn't important. What's important is the search function. It looks like this:

function filterList(q, list) {
  function escapeRegExp(s) {
    return s.replace(/[-/\\^$*+?.()|[\]{}]/g, "\\$&");
  }
  const words = q
    .split(/\s+/g)
    .map(s => s.trim())
    .filter(s => !!s);
  const hasTrailingSpace = q.endsWith(" ");
  const searchRegex = new RegExp(
    words
      .map((word, i) => {
        if (i + 1 === words.length && !hasTrailingSpace) {
          // The last word - ok with the word being "startswith"-like
          return `(?=.*\\b${escapeRegExp(word)})`;
        } else {
          // Not the last word - expect the whole word exactly
          return `(?=.*\\b${escapeRegExp(word)}\\b)`;
        }
      })
      .join("") + ".+",
    "gi"
  );
  return list.filter(item => {
    return searchRegex.test(item.title);
  });
}

I use this in a single-page content management app. There's a list of records and a search input. Every character you put into the search bar updates the list of records shown.

What it does is that it allows you to search texts based on multiple whole words. But the key feature is that the last word doesn't have to be whole. For example, it will positively match "This is a blog post about JavaScript" if the search is "post javascript" or "post javasc". But it won't match on "pos blog".

The idea is that if a user has typed in a full word followed by a space, all previous words needs to be matched fully. For example if the input is "java " it won't match on "This is a blog post about JavaScript" because the word java, alone, isn't in the search text.

Sure, there are different ways to write this but I think this functionality is good for this kind of filtering search. A different implementation would have a function that returns the regex and then it can be used both for filtering and for highlighting.

Hope it helps.

Suppose you have an array like this:

const items = ["B", "M", "X"];

And now you want to replace that second item ("J" instead of "M") and suppose that you already know its position as opposed to finding its position by doing an Array.prototype.find.

Here's how you do it:

const index = 1;
const replacementItem = "J";

const newArray = Object.assign([], items, {[index]: replacementItem});

console.log(items); // ["B", "M", "X"]
console.log(newArray); //  ["B", "J", "X"]

Wasn't immediately obvious to me but writing it down will help me remember.

UPDATE

There's a much faster way and that's to use slice and it actually looks nicer too:

function replaceAt(array, index, value) {
  const ret = array.slice(0);
  ret[index] = value;
  return ret;
}
const newArray = replaceAt(items, index, "J");

See this codepen.

UPDATE (Feb 2019)

Here's a more powerful solution that uses Immer. It looks like this:

const items = ["B", "M", "X"];
const index = 1;
const replacementItem = "J";

const newArray = immer.produce(items, draft => {
  draft[index] = "J";
});

console.log(items); // ["B", "M", "X"]
console.log(newArray); //  ["B", "J", "X"]

See this codepen.

It's more "powerful", because, if the original array (that you don't want to mutate) contains items that are mutable, you don't want to actually mutate them. This codepen demonstrates that subtlety. And this codepen demonstrates how to solve that with Immer.