OpenAI is shockingly good at unminifying code
Written by Frank Fiegel on .
While browsing the Internet for inspiration, I came across an interesting-looking component.
I thought the block with the running ASCII art looked cool, but I couldn't quite figure out how it was implemented, so I started looking at the source code.
I found the code that looked like it might be doing the job, but it was minified.
const { floor: ra, abs: KE, min: QE } = Math,
O5 = ["reactive.network REACTIVE.NETWORK", "$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,^`'. .:â–‘â–’â–“â–ˆ"],
G7 = Date.now() % 3 ? O5[1] : O5[0],
V5 = G7.length,
JE = { fps: 60 };
function eT(e, t, n, r) {
const i = t.time * 8e-5,
s = QE(t.cols, t.rows),
o = t.metrics.aspect * 0.2,
l = { x: ((4 * (e.x - t.cols / 6.25)) / s) * o, y: (5 * (e.y - t.rows / 4)) / s },
u = ra(KE(YE(l) - i) * V5 + (ra(e.x / 1) % 2) * 2) % V5;
return G7[u];
}
const tT = () => {
const e = j.useRef(null),
[t, n] = j.useState({ height: null, width: null });
return (
j.useEffect(() => {
function r() {
n({ height: window.innerHeight, width: window.innerWidth });
}
if (typeof window < "u") return n({ height: window.innerHeight, width: window.innerWidth }), window.addEventListener("resize", r), () => window.removeEventListener("resize", r);
}, []),
j.useEffect(() => {
const r = e.current;
if (!r) return;
const i = 12,
s = ra(t.width / i) * 1.6,
o = ra(t.height / i),
l = { aspect: s / o },
u = setInterval(() => {
let c = "";
for (let d = 0; d < o; d++) {
for (let f = 0; f < s; f++) c += eT({ x: f, y: d }, { cols: s, rows: o, metrics: l, time: Date.now() });
c += `
`;
}
r.textContent = c;
}, 1e3 / JE.fps);
return () => clearInterval(u);
}, [t]),
a.jsx("div", { style: { position: "absolute", top: 0, left: 0, width: "100%", height: "100%" }, children: a.jsx("div", { ref: e, style: { width: "100%", height: "100%", whiteSpace: "pre", overflow: "hidden" } }) })
);
};
function nT(e) {
return Math.cos(e.x * e.x - e.y * e.y);
}
const { floor: ia, abs: rT, min: iT } = Math,
D5 = ["reactive.network REACTIVE.NETWORK", "$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,^`'. .:â–‘â–’â–“â–ˆ"],
X7 = Date.now() % 3 ? D5[1] : D5[0],
F5 = X7.length,
sT = { fps: 60 };
function oT(e, t, n, r) {
const i = t.time * 8e-5,
s = iT(t.cols, t.rows),
o = t.metrics.aspect * 0.2,
l = { x: ((4 * (e.x - t.cols / 6.25)) / s) * o, y: (5 * (e.y - t.rows / 4)) / s },
u = ia(rT(nT(l) - i) * F5 + (ia(e.x / 1) % 2) * 2) % F5;
return X7[u];
}
const aT = () => {
const e = j.useRef(null),
[t, n] = j.useState({ height: null, width: null });
return (
j.useEffect(() => {
function r() {
n({ height: window.innerHeight, width: window.innerWidth });
}
if (typeof window < "u") return n({ height: window.innerHeight, width: window.innerWidth }), window.addEventListener("resize", r), () => window.removeEventListener("resize", r);
}, []),
j.useEffect(() => {
const r = e.current;
if (!r) return;
const i = 12,
s = ia(t.width / i) * 1.6,
o = ia(t.height / i),
l = { aspect: s / o },
u = setInterval(() => {
let c = "";
for (let d = 0; d < o; d++) {
for (let f = 0; f < s; f++) c += oT({ x: f, y: d }, { cols: s, rows: o, metrics: l, time: Date.now() });
c += `
`;
}
r.textContent = c;
}, 1e3 / sT.fps);
return () => clearInterval(u);
}, [t]),
a.jsx("div", { style: { position: "absolute", top: 0, left: 0, width: "100%", height: "100%" }, children: a.jsx("div", { ref: e, style: { width: "100%", height: "100%", whiteSpace: "pre", overflow: "hidden" } }) })
);
},
Usually, I would just powerthrough reading the minimized code to understand the implementation (or look for a .map
file to restore the original code). However, I realized that I never tried asking ChatGPT to do it for me... So I copied all of the above code and asked ChatGPT to "explain the code". Here is the response:
The provided code is quite complex, but I'll break it down into a more understandable format, explaining its different parts and their functionalities.
Overview
The code defines several functions and components using JavaScript, specifically in the context of a React application. It deals with generating some dynamic text content, presumably ASCII art or some kind of visual effect using characters from a predefined set. Additionally, it includes utility functions for event handling, performance timing, and HTML content conversion.
Key Components and Functions
- Character Set Selection:
const { floor: ra, abs: KE, min: QE } = Math; const O5 = ["reactive.network REACTIVE.NETWORK", "$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,^`'. .:â–‘â–’â–“â–ˆ"]; const G7 = Date.now() % 3 ? O5[1] : O5[0]; const V5 = G7.length;
- This part of the code imports some common Math functions (
floor
,abs
, andmin
) and defines two sets of characters, stored inO5
.- Based on the current time (
Date.now() % 3
), it selects one of these sets (G7
) to use later.- The length of the selected character set is stored in
V5
.- Dynamic Character Selection Function:
function eT(e, t, n, r) { const i = t.time * 8e-5; const s = QE(t.cols, t.rows); const o = t.metrics.aspect * 0.2; const l = { x: ((4 * (e.x - t.cols / 6.25)) / s) * o, y: (5 * (e.y - t.rows / 4)) / s }; const u = ra(KE(YE(l) - i) * V5 + (ra(e.x / 1) % 2) * 2) % V5; return G7[u]; }
- The
eT
function generates a character based on the input position (e.x
,e.y
) and the current time (t.time
).- It adjusts the position using some aspect ratio calculations and selects a character from
G7
based on a combination of the position and time.- The purpose of
YE
function isn't directly clear from the code, but it seems to be a custom function used in this calculation.- React Component (
tT
) for Displaying Dynamic Content:const tT = () => { const e = j.useRef(null); const [t, n] = j.useState({ height: null, width: null }); j.useEffect(() => { function r() { n({ height: window.innerHeight, width: window.innerWidth }); } if (typeof window < "u") { n({ height: window.innerHeight, width: window.innerWidth }); window.addEventListener("resize", r); return () => window.removeEventListener("resize", r); } }, []); j.useEffect(() => { const r = e.current; if (!r) return; const i = 12; const s = ra(t.width / i) * 1.6; const o = ra(t.height / i); const l = { aspect: s / o }; const u = setInterval(() => { let c = ""; for (let d = 0; d < o; d++) { for (let f = 0; f < s; f++) c += eT({ x: f, y: d }, { cols: s, rows: o, metrics: l, time: Date.now() }); c += ` `; } r.textContent = c; }, 1e3 / JE.fps); return () => clearInterval(u); }, [t]); return a.jsx("div", { style: { position: "absolute", top: 0, left: 0, width: "100%", height: "100%" }, children: a.jsx("div", { ref: e, style: { width: "100%", height: "100%", whiteSpace: "pre", overflow: "hidden" } }) }); };
- This is a React component that sets up an interval to periodically update the content of a
div
element (e.current
) with dynamically generated characters.- It calculates the number of columns (
s
) and rows (o
) based on the window size and then fills thediv
with characters generated by theeT
function.- The effect runs at a specified frames per second (
JE.fps
).
I followed up asking to "implement equivalent code in TypeScript and make it human readable" and got the following response:
import React, { useEffect, useRef, useState } from 'react';
const selectedCharacterSet =
"$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,^`'. .:â–‘â–’â–“â–ˆ";
const characterSetLength = selectedCharacterSet.length;
const calculateCharacter = (
x: number,
y: number,
cols: number,
rows: number,
aspect: number,
time: number,
): string => {
const timeFactor = time * 0.000_08;
const size = Math.min(cols, rows);
const aspectRatio = aspect * 0.2;
const position = {
x: ((4 * (x - cols / 6.25)) / size) * aspectRatio,
y: (5 * (y - rows / 4)) / size,
};
const index =
Math.floor(
Math.abs(
Math.cos(position.x * position.x - position.y * position.y) -
timeFactor,
) *
characterSetLength +
(Math.floor(x) % 2) * 2,
) % characterSetLength;
return selectedCharacterSet[index];
};
type Size = {
height: null | number;
width: null | number;
};
const AsciiArtGenerator: React.FC = () => {
const textRef = useRef<HTMLDivElement>(null);
const [size, setSize] = useState<Size>({ height: null, width: null });
useEffect(() => {
const handleResize = () => {
setSize({ height: window.innerHeight, width: window.innerWidth });
};
// Initial size setting
handleResize();
window.addEventListener('resize', handleResize);
return () => {
window.removeEventListener('resize', handleResize);
};
}, []);
useEffect(() => {
const element = textRef.current;
if (!element || !size.width || !size.height) return undefined;
const cols = Math.floor(size.width / 12) * 1.6;
const rows = Math.floor(size.height / 12);
const aspectRatio = cols / rows;
const intervalId = setInterval(() => {
let content = '';
for (let y = 0; y < rows; y++) {
for (let x = 0; x < cols; x++) {
content += calculateCharacter(
x,
y,
cols,
rows,
aspectRatio,
Date.now(),
);
}
content += '\n';
}
element.textContent = content;
}, 1_000 / 60); // 60 fps
return () => {
clearInterval(intervalId);
};
}, [size]);
return (
<div
ref={textRef}
style={{
height: '100%',
overflow: 'hidden',
whiteSpace: 'pre',
width: '100%',
}}
/>
);
};
export default () => {
return <AsciiArtGenerator />;
};
To my surprise, the response is not only good enough, but it is also very readable.
Here is the above component in action:
Comparing the outputs, it looks like LLM response overlooked a few implementation details, but it is still a good enough implementation to learn from. Definitely a neat use case I've not considered before!
Update (2024-08-29): Initially, I thought that the LLM didn't replicate the logic accurately because the output was missing a few characters visible in the original component (e.g.,
░▒▓█
). However, a user on HN forum pointed out that it was likely a copy-paste error.Upon further investigation, I discovered that the original code contains different characters than what I pasted into ChatGPT. This appears to be an encoding issue, as I was able to get the correct characters after downloading the script. After updating the code to use the correct characters, the output is now identical to the original component.
I apologize, GPT-4, for mistakenly accusing you of making mistakes.