Schwartzian transform
The Schwartzian Transform is like sorting your toys by what's written on the box, instead of by what the actual toy looks like. Let's say you have a bunch of toy cars, and you want to sort them by color. You could look at each car and put it in a pile based on its color. But that would take a long time if you have a lot of cars! Instead, you could take a piece of paper and write down some information about each car - maybe its color, and its name. Then you can sort the pieces of paper based on the color, and once they're sorted, you can look at the name to figure out which car it corresponds to.
That's basically what the Schwartzian Transform does - it's a way of sorting a large list of items based on some attribute (like color) without having to look at each item directly. Instead, you create a new list that has the attribute you want to sort by, along with a "key" that will let you match each item back to its original place in the list. Then you sort the new list by the attribute, and once it's sorted, you can use the key to figure out which item corresponds to each value.
So if we go back to the toy cars example, you would create a new list of pieces of paper (let's call it the "transformed" list) with two pieces of information on each paper - the car's color, and a number that represents its original position in the list. You might have something like this:
1. Red, 3
2. Blue, 4
3. Green, 1
4. Yellow, 2
Now you sort this new list based on the first part (the color) to get:
1. Blue, 4
2. Green, 1
3. Red, 3
4. Yellow, 2
And once you have this sorted list, you can use the second part (the number) to match each piece of paper back to its corresponding toy car in the original list.
This might seem like a lot of work, but it can actually be much faster than directly comparing each item in the list, especially if the attribute you're sorting by is expensive to calculate. Plus, once you've done the transform once, you can use the same sorted list in multiple places without having to sort it again each time.
That's basically what the Schwartzian Transform does - it's a way of sorting a large list of items based on some attribute (like color) without having to look at each item directly. Instead, you create a new list that has the attribute you want to sort by, along with a "key" that will let you match each item back to its original place in the list. Then you sort the new list by the attribute, and once it's sorted, you can use the key to figure out which item corresponds to each value.
So if we go back to the toy cars example, you would create a new list of pieces of paper (let's call it the "transformed" list) with two pieces of information on each paper - the car's color, and a number that represents its original position in the list. You might have something like this:
1. Red, 3
2. Blue, 4
3. Green, 1
4. Yellow, 2
Now you sort this new list based on the first part (the color) to get:
1. Blue, 4
2. Green, 1
3. Red, 3
4. Yellow, 2
And once you have this sorted list, you can use the second part (the number) to match each piece of paper back to its corresponding toy car in the original list.
This might seem like a lot of work, but it can actually be much faster than directly comparing each item in the list, especially if the attribute you're sorting by is expensive to calculate. Plus, once you've done the transform once, you can use the same sorted list in multiple places without having to sort it again each time.