Based on some places I used to work, upper management seemed convinced that the “idea” stage was the hardest and most important part of any project, and that the easy part is planning, gathering requirements, building, testing, changing, and maintaining custom business applications for needlessly complex and ever changing requirements.
Absolutely.
I’ve seen so many projects hindered by bad decisions around performance. Big things like shoehorning yourself into an architecture, language, or particular tool, but even small things like assuming the naive approach is unacceptably slow. If you never actually measure anything though, your assumptions are just assumptions.
My take on a modern Java solution (parts 1 & 2).
package thtroyer.day1;
import java.util.*;
import java.util.stream.IntStream;
import java.util.stream.Stream;
public class Day1 {
record Match(int index, String name, int value) {
}
Map numbers = Map.of(
"one", 1,
"two", 2,
"three", 3,
"four", 4,
"five", 5,
"six", 6,
"seven", 7,
"eight", 8,
"nine", 9);
/**
* Takes in all lines, returns summed answer
*/
public int getCalibrationValue(String... lines) {
return Arrays.stream(lines)
.map(this::getCalibrationValue)
.map(Integer::parseInt)
.reduce(0, Integer::sum);
}
/**
* Takes a single line and returns the value for that line,
* which is the first and last number (numerical or text).
*/
protected String getCalibrationValue(String line) {
var matches = Stream.concat(
findAllNumberStrings(line).stream(),
findAllNumerics(line).stream()
).sorted(Comparator.comparingInt(Match::index))
.toList();
return "" + matches.getFirst().value() + matches.getLast().value();
}
/**
* Find all the strings of written numbers (e.g. "one")
*
* @return List of Matches
*/
private List findAllNumberStrings(String line) {
return IntStream.range(0, line.length())
.boxed()
.map(i -> findAMatchAtIndex(line, i))
.filter(Optional::isPresent)
.map(Optional::get)
.sorted(Comparator.comparingInt(Match::index))
.toList();
}
private Optional findAMatchAtIndex(String line, int index) {
return numbers.entrySet().stream()
.filter(n -> line.indexOf(n.getKey(), index) == index)
.map(n -> new Match(index, n.getKey(), n.getValue()))
.findAny();
}
/**
* Find all the strings of digits (e.g. "1")
*
* @return List of Matches
*/
private List findAllNumerics(String line) {
return IntStream.range(0, line.length())
.boxed()
.filter(i -> Character.isDigit(line.charAt(i)))
.map(i -> new Match(i, null, Integer.parseInt(line.substring(i, i + 1))))
.toList();
}
public static void main(String[] args) {
System.out.println(new Day1().getCalibrationValue(args));
}
}
Bill is a liability.
Project Panama is aimed at improving the integration with native code. Not sure when it will be “done”, but changes are coming.
Wow, that looks really nice!
I use Lua for PICO-8 stuff and it works well enough, but certain parts are just needlessly clumsy to me.
Looks like TIC-80 supports wren. Might have to give that a try sometime!
Yep, absolutely.
In another project, I had some throwaway code, where I used a naive approach that was easy to understand/validate. I assumed I would need to replace it once we made sure it was right because it would be too slow.
Turns out it wasn’t a bottleneck at all. It was my first time using Java streams with relatively large volumes of data (~10k items) and it turned out they were damn fast in this case. I probably could have optimized it to be faster, but for their simplicity and speed, I ended up using them everywhere in that project.
I’ve got so many more stories about bad optimizations. I guess I’ll pick one of those.
There was an infamous (and critical) internal application somewhere I used to work. It took in a ton of data, putting it in the database, and then running a ton of updates to populate various fields and states. It was something like,
It was an unreadable mess. Trying to debug it was awful. Business rules encoded as a chain of sql updates are incredibly hard to reason about. Like, how did this row end up with that data??
Me and a coworker eventually inherited the mess. Once we deciphered exactly what the rules were and realized they weren’t actually that complicated, we changed the architecture to:
I don’t remember the exact performance impact, but it wasn’t markedly faster or slower than the previous “fast” SQL-based approach. We found and fixed numerous bugs, and when new issues came up, issues could be fixed in hours rather than days/weeks.
A few words of caution: Don’t assume that building things with a certain tech or architecture will absolutely be “too slow”. Always favor building things in a way that can be understood. Jumping to the wrong tool “because it’s fast” is a terrible idea.
Edit: fixed formatting on Sync
This is a very strange article to me.
Do some tasks run slower today than they did in the past? Sure. Are there some that run slower without a good reason? Sure.
But the whole article just kind of complains. It never acknowledges that many things are better than they used to be. It also just glosses over the complexities and tradeoffs people have to make in the real world.
Like this:
Windows 10 takes 30 minutes to update. What could it possibly be doing for that long? That much time is enough to fully format my SSD drive, download a fresh build and install it like 5 times in a row.
I don’t know what exactly is involved in Windows updates, but it’s likely 1) a lot of data unpacking, 2) a lot of file patching, and 3) done in a way that hopefully won’t bork your system if something goes wrong.
Sure, reinstalling is probably faster, but it’s also simpler. If your doctor told you, “The cancer is likely curable. Here’s the best regimen to get you there over the next year”, it would be insane to say, “A YEAR!? I COULD MAKE A WHOLE NEW HUMAN IN A YEAR!” But I feel like the article is doing exactly that, over and over.
Which they could have done a much better job with.
It was basically just hosted SVN if I remember right, and they never added git support when it became the de facto version control system.
Having used PHP and Java extensively in my career, it’s always entertaining to read what people think about these languages.