I know that data science is a broad and somewhat vague term but this -
We will cover:
Core features of modern JavaScript
Programming with callbacks and promises
Creating objects and classes
Writing HTML and CSS
Creating interactive pages with React
Building data services
Testing
Data visualization
Combining everything to create a three-tier web application
It decreases the amount of boilerplate "how to program in X" text you have to write. Producing text, especially novel text, is expensive in a non-fiction book.
"JavaScript relies heavily on callback functions: Instead of a function giving us a result immediately, we give it another function that tells it what to do next. Many other languages use them as well, but JavaScript is often the first place that programmers with data science backgrounds encounter them."
That sentence from the book clarifies a lot for me. It is Javascript for Data Science People. Taken in that context this is an excellent book written with empathy for the Data Science user who is usually making uneasy excursions which they hope and pray is only temporary into Javascript and running back to Python the first time they encounter a Promise or a Callback.
The book does cover a lot of basic Javascript material, as its target is actual natural scientists who may not have much experience with the language, but towards the end it does cover things like Data-Forge (which is a data science library in Javascript)
The title is „JavaScript for Data Science“, not „Data Science for JavaScript“. It’s like... in a bar: they will serve a beer for you, so they have the beer and you have you. For a book called „JS for DS“, you should have the the DS while they bring the JS.
Compare this with: „Data wrangling with JavaScript“ [1]
Well the problem with “data science” is that it costs a shit ton of money but rarely integrates into anything. A book about wiring data science models into real user facing application maybe isn’t data science, but sure is useful...
I'm glad more people are doing DS/ML/AI with JavaScript, thanks for this book and keep up the great work! -- We are also working in this space, would love to connect, you can find me in javier at hal9.ai
I don’t want to repeat the old and tired JavaScript hate, but this just isn’t a great idea.
I’d suggest that there are 3 important primitives for data science: flexible numeric types, fast math/algorithm libraries, and data manipulation being easy.
JavaScript doesn’t really have any of these. Numbers are 64bit floats only - no integers, no big numbers. There aren’t equivalents to Numpy/Pandas/Scikit Learn, and the lack of standard library and expressiveness in data manipulation in the language makes basic tasks harder.
JavaScript has its uses, but there’s really no reason to force data science be one of them.
That's not the problem. The problem is mindshare and network effects. When analyzing why Python is used one way and JS another we're tempted to retroactively rationalize this with something fundamental about the language. There's nothing fundamental about it. It's just happenstance. Python was around longer as a general purpose script, and it filled that niche. JS is relatively new as a script outside the browser.
I sincerely believe it is possible for JavaScript to be a viable language ecosystem, but there is dire need for cohesion, collaboration, and longevity. As it stands, there are so many potentially viable projects strewn across the NPM landscape like old, discarded toys.
I'm not aware of an initiative, let alone ethos, in the JS community that comes anywhere close to something like NumFocus.
You can get a long way nowadays with Arquero[0] and Observable[1]. Arquero allows columnar based data storage and processing, with a grammar of data processing verbs similar to e.g. dplyr. Not as fast as vectorized computations in e.g. Python or R, but faster than has previously been possible.
I'm not suggesting these are the first tools you'd reach for for data science in production, but I've found them extremely useful for prototyping, experimenting with algorithms, and visualization. I think it's got to the stage they should be seriously considered for some types of relatively simple data processing work due to their ease of deployment.
That's typical with most JS features, it takes some time for engine performance optimizations to catch up with them. In this particular case I suppose things are moving slower than expected, but with demand increasing prioritization will take place.
I don't see JS as less powerful than Python for data science, it's faster than Python, or can use bindings just like Python. JS is maybe less commonly used than Python in data science nowadays, but I wouldn't be surprised if this changes in next years. There are equivalent libs like tensorflow-core, there are native features like BigInt, and there are libs for 64bits floats (decimal.js, big.js). I'd be glad to spend some time converting Scikit-learn into JS and also show you how expressive JS actually is, if you show me some Python code, I'll translate it
The fact that the number support isn’t part of the language is Linda the problem though.
When you’re writing data science code, the value is in the answer more than the process of getting to that answer. Anything that complicates that gets in the way. This is why things like Pandas are so popular despite having some questionable engineering. Using a library for big number support, having to get that to play nicely with other libraries, it all goes against the aims.
Now for data engineering it’s very different. I wouldn’t choose JS myself, but it’s a much more reasonable choice. For engineering the process by which you get the answer matters far more - is it scalable, testable, repeatable, etc. Having to use a library for big number support is fine.
It’s two very different ways of working and I’m still fairly convinced that JS is not conducive to the former.
Is that generally true for data science type tasks, though, where the "fast" in python is really numpy, pandas, etc?
>or can use bindings just like Python
But there's not really anything like numpy/pandas for it to bind to at the moment, is there? Meaning anything as broad in functionality, fast, mature, etc.
We're using NodeJS for data science with Tensorflow JS and it's excellent, at least for our use case, which is 90% discrete data, mostly classification tasks.
NodeJS evented architecture is great for multitasking training (and prediction) jobs. I use Node Streams to extract and process data flows out of several data sources on my Macbook Air M1 using the new Neural Engine 16-core chip to train CNN models with excellent results.
Data prediction then runs on a ReactJS app, which gives my users a way to model, transform and visualize data on a browser. Everything is in Typescript, which reduces cognitive overload for our programmers and produces good end-to-end duck-type coherence and easy, integrated testing.
Now, most data science libs for Javascript are either on their infancy, are proof-of-concept or just abandoned, but TFJS is solid and if you know what, why and to which extent you're using JS for data science, then it's absolutely fine.
You should absolutely read "JavaScript and the next decade of data programming" by Ben Schmidt [1] before outright saying that it wouldn't be a great idea.
JavaScript does have integers (e.g. `Uint8Array`) and it also has big numbers (e.g. `BigInt`). It's true that there's not yet an equivalent to Numpy/Pandas/Scikit yet, but POCs show that it will be possible to create such a thing and that we will be able to use the WebGPU API to access higher performance than is available using Python [2].
I'm not saying that it will definitely happen, but why not?
I don't want to argue for or against using JS for "data science" (I myself used R for that but I use JS a lot for other things), just a clarification on this one concrete claim.
> That is not true. BigInt has been available for a bit already.
performance-wise, BigInts are terrible. Tried to use them, made things about a hundred times slower. What JS needs are 64 bit integer types, and some form of typing system that allows differentiating between various number types.
The JIT that understands what number type you want and switches between 31 bit ints and doubles when assumptions are violated without big performance loss. Something similar is likely possible with bigints and 64bit ints
Genuine question: I imagine most data science things involve arrays of numbers, not just single numbers. JS has UInt8Array, i.e. it does kinda have integers if you want them in an array anyway. Can that speed things up?
In my case, it did involved reading binary files from ArrayBuffers where some attributes were stored as int64. I've been using DataView to read BigInt64s and then used those frequently. Was terribly slow. I've then reverted to alternatives wherever possible, e.g. immediately converting the BigInt64s to Numbers/Doubles where 53 bit integers were sufficient, or splitting down to two 32 bit integers and do some more involved bit magic on them. Much faster, but overall I wasn't happy with the whole process and complexity. I'd rather have native 64bit integer values in JS.
> repeat the old and tired JavaScript hate, but this just isn’t a great idea.
There is absolutely nothing wrong with coders/analysts/scientists building solutions in any language. The "hate" that you mention -- and then proceed to echo -- is a narrow way of asserting the superiority of $mylanguage and the inferiority of $yourlanguage.
> flexible numeric types, fast math/algorithm libraries, and data manipulation
Your point b) is usually written in a performant, compiled language, and your point c) can be built from robust primitives in any language. However, I will add a point d) about speed and memory usage.
I do data analysis with the simplest set of performant tools: sqlite, bash-awk-sed-grep, Perl, Python, C++, SVG, and a browser to render. Any kind of glorified REPL beyond a terminal creates fragile complexity and dependency Hell.
My kit doesn't include Node.js or ECMAscript but I'm willing to open my mind enough to think it might, one day. The current tooling for data analysis (or "data science" if we want to be faddish) is a mess and I look forward to better tools in the future.
On point 3 - I had to implement a logistic regression model in js recently and implementing all of the required math methods (eg dot product, transpose, vectorized addition, etc.) were actually super easy with js’s functional array utilities.
the reason to force data science is that same as the reason to develop libraries in languages for tasks which that language might otherwise seem not well suited to, that there is a large userbase of the language who know how to use it and would like to explore using that language for doing other things than it is normally used for. You may of course suggest that they should just learn a new language, but the history of computing shows that solutions for using languages to new purposes they might not seem suited for happens whenever such a purpose arises.
To address some of the skepticism about when and where javascript would be appropriate in data science, would you want to fit a logistic regression model in javascript? Probably not, but to build a solver that takes model outputs and visualizes the changes in predicted probabilities based on different combinations of variables? This is definitely where javascript would make sense. Visualization, dashboards, reporting, and exploratory analysis are all ripe domains for developing rich responsive UIs. Basically, any layer where you have a data-to-human interface can be leveraged with javascript.
There is a lot of great work happening in this space already. In the R world for example, shiny makes heavy use of js to the point that you often can't tell where R code ends and javascript begins. Plotly's Dash provides bindings for R, Python, and Julia. Personally, as a data scientist, I have been excitedly learning React because it really rips the landscape wide open for all the use cases I mentioned above. It then makes sense to have libraries that give JS users a good data model and can do most of the same numerical computation that we'd be doing in other languages. Again, you probabaly don't want to do serious numerical work in js, but remember people said that about Python ten years ago too.
I love the framing of this book, because I want more data scientists to start thinking about the presentation of data and spark some bits of ingenuity to make datasets and model outputs accessible to non-data scientists. Data scientists should be the ones writing the tools that interface data with humans because of their domain knowledge. But this is a different skillset and usually the work of SW engineers. Of course engineers can also have great data intuition too, but I really do encourage data scientists to develop their front end skills, it's well worth it.
I don't see the point of this. You already have a ubiquitous, easy-to-learn, high-level language that's great for data science, it's called python. If you're a JavaScript developer who wants to get into data science but are too lazy to learn python, you probably weren't that interested in data science in the first place.
Python definitely has some problems, but if you were going to have a new lingua franca for data science, it would probably be something like Julia, certainly not JavaScript.
My hunch is that there has been 10X more investment in engineering for JavaScript: nodejs, webassembly, webgl, webgpu, react native, deno, typescript, electron, chrome, etc. That will be harder to rewrite in Python than to rewrite TensorFlow and a few math libraries in JavaScript.
Data science is not a standardized term, however I don't get what specifically makes this text relevant for the domain of data science... For some data science projects one could surely use javascript, however in mamy cases one misses important libraries, for purposes such as statistical analysis, data manipulation, machine learning, ...
I am a noob to Javascript, so if someone knows better, than please correct me about this, but arrow functions aren't meant to replace normal function syntax, right? From [1], it seems like the main point of arrow syntax is to allow you to inherit the "this" parameter if you are inside a method. Meanwhile, you need normal function syntax if you are creating a constructor, making a method function for a prototype, or making generator functions. (I didn't even know javascript had generator functions until just now :))
So it seems a bit weird to me that they advocate using arrow function syntax instead of the regular syntax. They seem to be advocating using the new class syntax instead, so I guess they don't need the constructor or method creation features of the normal syntax, but I still don't see why they would specifically advocate for arrow function syntax. Is it faster? They say it interferes with other features, but which features?
I've seen a majority of sources abandon the function keyword entirely in favor of const arrow declarations (and shorthand method syntax).
FWIW I personally like the function keyword, since it's clear what it is to non-JS readers, but primarily because it hoists to the top of its file, so unimportant utility functions can sit unobtrusively at the end of the file, thereby letting readers encounter more important logic earlier in the file.
Not changing `this` is a huge benefit that shouldn't be ignored. Especially when you're programming in a more functional style, it makes sense to default to arrow functions because you never want to engage in `this` shenanigans anyway. So, yes, I'd say it's a pretty common idiom in the JS community to replace "normal" function declarations.
I agree that inheriting the `this` for arrow functions is beneficial. To me it seems like you would want to use the normal syntax for global functions for hoisting and to prevent unintentional re-definitions, the arrow functions where you would use lambda functions in other languages, and the class method syntax for methods.
side-note: Most of my JS experience is writing userscripts for myself, so I definitely do my share of 'this' shenanigans.
As a heads up since you mentioned "class method syntax", methods are one of the most important places to have lexical `this` binding in many scenarios.
Take the following example, which is a normal class method:
> alertSum() { alert(this.a + this.b); }
And here we have an arrow function used to create an instance method (just an arrow function assigned to a property on the instance):
> alertSum = () => { alert(this.a + this.b); }
Then let's say we want to pass the method directly as callback:
The first example (class method syntax) won't have the necessary `this` context unless it has its context bound to the instance through `Function.prototype.bind`. There are other patterns to avoid this (e.g. wrapping all callbacks in arrow functions when passing them), but it's useful to consider that classes methods can easily create confusion because that's _exactly where_ someone more used to a different language may assume the `this` context is bound lexically.
Excellent point! I can see that getting confusing quickly.
Edit: I was confused about how this could work, so I dug through [1] for a bit. It appears that for each object of that class created, an arrow function will be created on that object and its this will indeed be bound to the same scope that the constructor function is bound to. This is really cleaver and I applaud whoever thought it up!
It is interesting to note that this creates a new arrow function on each object as opposed to the normal definitions which create a single function which is stored in the prototype of the class. (its easier to check this in a browser's dev console then it is to decode the spec)
This would suggest that one should use different approaches for different types of objects: It makes sense to use arrow functions for "resource" or "actor" objects, of which there are few but they may have callback functions. It makes sense to use normal method definitions for "plain old data", of which there may be many, (which would make the arrow functions too expensive) but they should not have callback functions.
> This is really cleaver and I applaud whoever thought it up!
Not really. It's contortionist and wasteful and one of the many reasons why mainstream web apps are one big celebration of bloat on a boat.
The neophyte programmers who have turned into expert Modern JS programmers are always recommending arrow functions like this because they've never actually looked at the event listener interface. What happens is they try to make things more complicated than they need to be and bodge their event registration. So they apply a "fix" by doing what they do with everything else: layering on even more. "What we need," they say, "are arrow functions."
No.
Go the other way. Approach it more sensibly. You'll end up with a fix that is shorter than the answer that the cargo cult NPM/GitHub/Twitter programmers give. It's familiar to anyone coming from a world with interfaces as a language-level construct and therefore knows to go look at the interface definition of the interface that you're trying to implement.
Make your line for registering an event listener look like this: `this.button.addEventListener("click", this)`, and change the name of your `addSum` method to `handleEvent`. (Read it aloud. The object that we're dealing with (`this`) is something that we need to be able to respond to clicks, so we have it listen for them. Gee, what a concept.) In other words, the real fix is to make sure that the thing we're passing in to `addEventListener` is... actually an event listener.
This goes over 90% of frontend developers' heads (and even showing them this leads to them crying foul in some way; I've seen them try to BS their way through the embarrassment before) because most of the codebases they learned from were written by other people who, like themselves, only barely knew what they were doing. Get enough people taking this monkey-see-monkey-do approach, and from there you get "idioms" and "best practices" (no matter whether they were even "good" in the first place, let alone best).
I want to respond to this constructively, because you highlighted a useful interface I'd never taken note of previously; maybe we can focus this discussion on a technical level. Meanwhile, if you haven't had a positive response to technical feedback directed to JS engineers about this, I would encourage rereading the comment you wrote. I genuinely hope this is useful feedback, as I very much value insight from other languages and levels of abstraction, and I'd love for you not to get turned off to sharing that insight by a bad response from JS engineers. JavaScript is high level, and it's too easy to get disconnected from all of the work the engine and underlying computer are doing to make a program work in this environment.
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As I understand the interface, practical use of the EventListener interface boils down to the implementer performing a form of event delegation, where you'd wind up delegating from a single `handleEvent()` method on a class to handle different event types and/or events with different target elements -- as opposed to a single click handler in a simple button click example. I'd love to understand and quantify the benefit of this. If it's a significant improvement, it'd be doubly unfortunate, as many callback-based interfaces in JavaScript APIs and libraries at a higher level don't support such a model.
Assuming there's a strong benefit, I also wonder if there's an opportunity for build-time tooling to rewrite code from ad-hoc callbacks to more efficient delegation along these lines. Tangentially, I also don't know about `Function.prototype.bind` vs wrapping arrow functions in terms of performance; that's also something I'm curious about, as they're often a 1:1 analog.
I'm tempted to test a few of these things out myself, but if you have references, that would be helpful.
> if you haven't had a positive response to technical feedback directed to JS engineers about this, I would encourage rereading the comment you wrote
You're mixing up cause and effect; there's a reason why the perspective laid out in that comment has come to carry the amount of derision evident in its tone. It's wrong to assume things started out like this (and it's wrong to assume that a different tone will achieve better results; experience shows that the difference in results, if any, is worse otherwise).
> Assuming there's a strong benefit, I also wonder if there's an opportunity for build-time tooling to rewrite code[...]
That's another example of "layering on more" approach, and the small matter of changing the actual runtime mechanism in isolation isn't going to solve much. The big, relevant matter at hand is a complete difference in mindset that programmers have when they're approaching a problem with the ultimate intent of solving it with code.
For example, let's say you have a list of items, and M different kinds of events you want to respond to. That's not just a matter of a difference of e.g. 1 listener (implementing `handleEvent`) vs 2 or more (individual arrow functions). If that list is N items long, now we're talking about M × N different objects (worse, closures—each with their own lexical scope, keeping the bindings alive and potentially thwarting the GC's work)[0]. But the programmer who knows not to use arrow functions here doesn't just stop at implementing `handleEvent`, he or she also recognizes that if all of those listeners share common behavior, then the whole thing can be handled by a single event listener—on an ancestor element that just looks at the event target.
Once again, though, this is much bigger than event listeners. This is about a mindset that pervades everything at every level. The mindset of programmers working in "modern", "standard"[1][2] JS is a mindset that fundamentally impacts how they approach everything, from how to decompose a system into its natural parts, to what routines need to be written and what factors to be aware of while implementing them.
Note that unlike the comments elsewhere, this isn't mistakenly misplaced aggression towards JS per se, nor is it an endorsement of other communities/ecosystems like Python, which tends to have programmers that are just as bad, if not worse. A big part of the problems afflicting the world of modern JS for that matter is programmers who have ended up there by way of Python or similar.
0. Runtimes will have some mitigations for this, but eventually that runway ends; the myth of the sufficiently smart compiler although an enduring one, is unattainable
2. Let's consider, for that matter, the obnoxious temerity that it takes to decide to anoint one's opinionated, less-than-well-informed set of personal preferences—many of which ironically reek of fighting against the language itself—as "standard"
Just FYI, the standardjs link doesn't seem to support your point here. It seems like standardjs is mostly about forbidding confusing syntax and obsolete APIs. (like .__iterator__, which appears to be replaced by Symbol.iterator, or .__proto__ which is replaced by .getPrototypeOf())
The only item which standardjs forbids that I could identify as possibly producing a decent performance improvement if used is the "with" statement. They also forbid wrapping non-objects in objects, which I guess could provide extra-expressiveness, but seems like it would usually just be a performance penalty.
I have seen people recommending obviously inefficient things like including large third-party libraries just to look up an element by class name, but standardjs looks like it is just a set of linting rules. I don't agree with all of them but I don't think there is a set of rules everyone would agree to.
> Make your line for registering an event listener look like this: `this.button.addEventListener("click", this)`, and change the name of your `addSum` method to `handleEvent`. (Read it aloud. The object that we're dealing with (`this`) is something that we need to be able to respond to clicks, so we have it listen for them. Gee, what a concept.) In other words, the real fix is to make sure that the thing we're passing in to `addEventListener` is... actually an event listener.
Eh, show me an object that both owns a button and is an event listener attached to that button, and I’ll bet you just showed me an object that violates the SRP. OO event listeners make sense to encapsulate state narrowly associated with handling the events being listened for.
But, having been doing OOP since I was a teenager in the late 1980s (and even that after programming for more than half a decade), I don’t prefer to do as much JS as possible in a functional style because I don’t get interfaces
or other OO concepts, but because I understand the limits of their utility and managed not to be one of the one-paradigm-to-rule-them-all programmers that came out of the excessively OO-focussed pedagogy of much of the 90s and 00s.
> managed not to be one of the one-paradigm-to-rule-them-all programmers that came out of the excessively OO-focussed pedagogy of much of the 90s and 00s
Sounds like a veiled criticism towards an implied target (of me), which would be interesting, considering the retort is an appeal to "SRP" (referred to only with shorthand, even), and indeed, the first mention of OO(P) is your comment. The shape of your foe isn't what you think it is.
> OO event listeners make sense to encapsulate state narrowly associated with handling the events being listened for
For this defense to be valid, you have to ignore the preconditions that got us here. The entire context here is making sure that `this` refers to the correct thing at the time that the event listener is executed. Either you want that, or you don't—pick one.
(And as with, like, 90% of mainstream applications of the label "functional programming", look at what people are actually talking about when they use those words, and it's immediately apparent that theirs is a style of programming where the label is unjustifiable, considering it's fundamentally at odds with what functional programming actually is. Again, pick one: you either intend to do FP and do so through the use of functions, or you want your state baggage. Modern appeals to FP by JS programmers in the mainstream and the practices that get smuggled in under that brand are just as bankrupt as arguments for modern JS practitioners' best practices regarding anything else—ones that are entirely self-defeating or fail to hold up under scrutiny otherwise.)
I'm learning all sorts of things today! handleEvent certainly seems like the language certified way to do this. It does seem like that means you need a case statement in handleEvent if you want to listen for multiple events, which I guess is not the end of the world. It does solve the "redefine the function for every object" problem though, provided any third party apis understand the EventListener interface.
> handleEvent certainly seems like the language certified way to do this
It's a platform API (the browser DOM). It's a completely separate matter from JS the language. It has, though, been the "correct" way to work with events since at least as far back as 1998 or so. It's the official platform APIs that had to change to accommodate the function-as-a-listener pattern (requiring an entire revision to the interface definition language itself so that it would have the power to express it), since so many browsers implemented that non-standard extension, and so many programmers insisted on using it. And that pattern is also directly responsible for why arrow functions and Function.prototype.bind were added to the language itself. If only it had been addressed differently, writing programs for the web browser might look a lot different than the way it does today.
As a data scientist who does more frontend, I think this is a really valuable concept. Hello by users/stakeholders engage with our work is the way to push it forward in the org and a dash of frontend can do wonders for getting that message across.
It’s wonderful that people are making resources about the frontend for data scientists
Glad you also see it this way! Would love to chat with you and get some feedback on a platform we are building at hal9.ai, my email is javier at hal9.ai -- Looking forward to chat.
I thought of writing a Javascript + tensor flow.js + NLP + web scraping + linked data + etc. book about a year ago. tensorflow.js is especially very cool: well documented with great examples. In fact, it was the great tensor flow.js examples and demos that convinced me to not write the book because I didn't feel like I could do much value add on that subject.
Really cool but no one needs this... as a data scientist learning javascript, teach me how to run data science models using javascript! That's where the real gold is... I'm even thinking of writing articles about this myself... JS is great for making things more tangible and interactive
Personally, I'm excited to build apps that don't require cloud computing and if they do, have access to one of the largest software engineering libraries through NPM. Sure, I'm not doing just Data Science in JavaScript but rather building apps that use DS/ML/AI, but that's still a valid use case. The alternative would be to use Python for prototyping then rewrite for production apps.
