Fixes#8497
This works on every other supported version of macOS but doesn't work on
macOS tahoe. Putting it on the next event loop tick works at least on
Sequoia and Tahoe so let's just do that.
Fixes#8497
This works on every other supported version of macOS but doesn't work on
macOS tahoe. Putting it on the next event loop tick works at least on
Sequoia and Tahoe so let's just do that.
Replaces #7952Fixes#7951
This reimplements our color operation parsing completely to make it
fully compatible (as far as I can tell) with xterm. Our previous
implementation had numerous problems, I think because we kept addressing
singular compatibility issues as they were experienced in the field
rather than doing a proper thoughtful audit compared to the xterm
implementation. This PR does that audit.
**Specifically, this updates/adds: OSC 4, 5, 10-19, 104, 105, 110-119.**
To ease maintenance, understanding, and testing, I've pulled color
operation parsing out into a separate file and function that operates on
the full buffered OSC command. This is similar to Kitty protocols
previously. This hurts performance but that's acceptable to me for now
while we get compatibility down and test coverage added.
We can address more performance later if it becomes a bottleneck, but
these color operations are pretty rare.
I've associated each test with a `printf` command you can run in xterm
to compare.
## Xterm Divergence
We purposely diverge from xterm in some scenarios:
- Whitespace is allowed around x11 color names. Kitty allows this.
- Invalid index values for 104/105 are ignored. xterm typically halts
processing. Kitty allows this.
## TODO
- [x] Update our parser to use the new color parsing functions
- [x] Update the stream handler to use the new types
- [x] Fix our stream handler to emit on response per query
These keys are present in some old unix keyboards, but more importantly,
their keycodes can be mapped to physical keys in modern programmable
keyboards.
Using them in Linux is a way to be able to have the same keys for
copy/pasting in GUI apps and in terminal apps instead of switching
between ctrl-c/ctrl-v and ctrl-shift-c/ctrl-shift-v.
These keys are present in some old unix keyboards, but more importantly,
their keycodes can be mapped to physical keys in modern programmable
keyboards.
Using them in Linux is a way to be able to have the same keys for
copy/pasting in GUI apps and in terminal apps instead of switching between
ctrl-c/ctrl-v and ctrl-shift-c/ctrl-shift-v.
this test previously didn't fail when accessing freed members of config
because deiniting `command_arena` was a no-op; `command_arena` was
derived from `arena`, which allocated memory after `command_arena` was
created/used
this test previously didn't fail when accessing freed members of config
because deiniting `command_arena` was a no-op; `command_arena` was derived
from `arena`, which allocated memory after `command_arena` was created/used
This aligns the `buf` of `4096` bytes in the benchmarks to the cache
line, to ensure a consistent number of cache lines are used, and also to
avoid any sub-`usize` alignment issues as seen in
https://github.com/ghostty-org/ghostty/pull/8548.
This has less of an effect as
https://github.com/ghostty-org/ghostty/pull/8548, and looking at the
before and after of the current benchmarks in the repo doesn't show any
noticeable difference.
In my case, I've been comparing the `table` option with [uucode in this
branch](https://github.com/ghostty-org/ghostty/compare/main...jacobsandlund:jacob/uucode?expand=1),
and I did see a difference.
### Before
I ran the before code several times (6 with the exact same binary, but
several more with essentially the same code), always getting something
like this, with `table` edging out `uucode` by something like 3-4ms:
```
Benchmark 1: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=table
Time (mean ± σ): 927.8 ms ± 1.3 ms [User: 883.7 ms, System: 42.5 ms]
Range (min … max): 926.0 ms … 929.8 ms 10 runs
Benchmark 2: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=uucode
Time (mean ± σ): 930.9 ms ± 1.4 ms [User: 886.8 ms, System: 42.5 ms]
Range (min … max): 928.5 ms … 933.4 ms 10 runs
```
### After
After this change, it shows `uucode` coming in at 10-11ms (~1%) faster:
```
Benchmark 1: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=table
Time (mean ± σ): 930.6 ms ± 1.3 ms [User: 886.5 ms, System: 42.4 ms]
Range (min … max): 928.9 ms … 932.4 ms 10 runs
Benchmark 2: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=uucode
Time (mean ± σ): 920.1 ms ± 1.4 ms [User: 876.3 ms, System: 42.1 ms]
Range (min … max): 918.4 ms … 923.3 ms 10 runs
Summary
zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=uucode ran
1.01 ± 0.00 times faster than zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=table
```
This ~1% faster time checks out, since from looking at the assembly,
it's an exact match minus this small place where the compiler can
optimize `uucode` a little better:
```
# both table.asm/uucode.asm:
140 const high = cp >> 8;
141 const low = cp & 0xFF;
** 142 return self.stage3[self.stage2[self.stage1[high] + low]];
<+464>: ubfx x12, x11, #8, #13
<+468>: ldrh w12, [x27, x12, lsl #1]
<+472>: add x11, x28, w11, uxtb #1
<+476>: ldrh w11, [x11, x12, lsl #1]
# table.asm:
<+480>: lsl x11, x11, #1
** 158 table.get(@intCast(cp)).width);
159 }
160 }
<+484>: ldrb w11, [x22, x11]
# uucode.asm:
** 148 return @field(data(stages, cp), name);
<+480>: ldrh w11, [x22, x11, lsl #1]
```
### More confusion with showing addresses
Confusingly, when I added `std.debug.print("buf addr={}\n",
.{@intFromPtr(&buf)})` to show the addresses, this somehow made the
`before` case show `uucode` as being faster. Then, when I added
alignment, `uucode` and `table` were taking about the same time
(**edit:** _uucode was only ~4 ms faster, but see more in "Edit: more
investigation"_)
If I run without the `std.debug.print` and with `--show-output`, the
times are different, so just making a note of this.
```
Benchmark 1: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=table
Time (mean ± σ): 904.2 ms ± 1.2 ms [User: 884.6 ms, System: 40.3 ms]
Range (min … max): 902.8 ms … 906.1 ms 10 runs
Benchmark 2: zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=uucode
Time (mean ± σ): 892.7 ms ± 2.0 ms [User: 873.2 ms, System: 40.1 ms]
Range (min … max): 887.9 ms … 895.6 ms 10 runs
Summary
zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=uucode ran
1.01 ± 0.00 times faster than zig-out/bin/ghostty-bench +codepoint-width --data=data.txt --mode=table
```
I think, even with this confusing case, aligning is going to be more
consistent than not.
### Edit: more investigation
I wasn't satisfied with the discovery that adding `std.debug.print` made
this difference and I wanted to dig in and figure out exactly what's
going on, but I didn't get a satisfactory answer. Here's what I tried:
* I compared the un-aligned addresses from `stepTable` and `stepUucode`,
but both seemed similar (not aligned to 128, different each run, but
aligned to 8). Note though that `uucode` was running ~1% faster still,
similar to the aligned case even though here it was un-aligned.
* Instead of doing `std.debug.print` in the step function, I printed in
teardown, just in case. This had no difference in the unaligned case,
but with alignment it brought the ~4 ms faster `uucode` (as noted above)
back closer to the original "after" at around 11-12 ms faster (~1%).
* I forced the `buf` in `stepUucode` to not be aligned (e.g. by making
it `= other_aligned_buf[3..4096 + 3]`). Still it was ~1% faster.
* I compared the assembly of `stepTable` and `stepUucode` for both
aligned and not aligned cases, including doing a diff of the diff of
these two across aligned and not aligned. The only difference between
`stepTable` and `stepUucode` is what's noted above, and nothing stood
out in the double diff.
* I tried going back to the original un-aligned non-printing code, but
then swapped the lines that get from `table` or `uucode`, so that
`stepTable` and `stepUucode` were actually doing the opposite. And the
result is`stepTable` (actually `uucode`) was 10-11 ms (~1%) faster, just
like the aligned case!
In summary, I wasn't able to replicate the original benchmark behavior
_and print out buffer addresses that pointed to alignment being the
issue_. I still feel like in theory aligning the buffer ought to make
the benchmark more reliable, and indeed the original un-aligned version
gives the result that is more of an outlier, but the evidence here is
weak, so I'm alright if we stick with the status quo and close. I think
a lesson here is benchmarks are hard to get precise.
Release notes at:
https://github.com/vancluever/z2d/blob/v0.8.0/CHANGELOG.md
This is a small update and likely contains nothing related to Ghostty,
but I wanted to make sure it got in before the 1.2.0 release since it
contains the removal of non-functional code that wasn't compiling, just
for correctness' sake.
Also if for some reason ARGB/XRGB is needed for some utility purpose,
it's there now. 🙂
Release notes at:
https://github.com/vancluever/z2d/blob/v0.8.0/CHANGELOG.md
This is a small update and likely contains nothing related to Ghostty,
but I wanted to make sure it got in before the 1.2.0 release since it
contains the removal of non-functional code that wasn't compiling, just
for correctness' sake.
Also if for some reason ARGB/XRGB is needed for some utility purpose,
it's there now. :)
Bumps
[namespacelabs/nscloud-cache-action](https://github.com/namespacelabs/nscloud-cache-action)
from 1.2.16 to 1.2.17.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a
href="https://github.com/namespacelabs/nscloud-cache-action/releases">namespacelabs/nscloud-cache-action's
releases</a>.</em></p>
<blockquote>
<h2>v1.2.17</h2>
<h2>What's Changed</h2>
<ul>
<li>Delete existing files at path before creating bind mount, this was
already handled correctly for existing directories but not for
files</li>
</ul>
<p><strong>Full Changelog</strong>: <a
href="https://github.com/namespacelabs/nscloud-cache-action/compare/v1.2.16...v1.2.17">https://github.com/namespacelabs/nscloud-cache-action/compare/v1.2.16...v1.2.17</a></p>
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<details>
<summary>Commits</summary>
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<li><a
href="a289cf5d2f"><code>a289cf5</code></a>
Merge pull request <a
href="https://redirect.github.com/namespacelabs/nscloud-cache-action/issues/33">#33</a>
from namespacelabs/delete-existing-files-at-path-befor...</li>
<li><a
href="3851f57081"><code>3851f57</code></a>
Delete existing files at path before creating bind mount</li>
<li><a
href="58efedf646"><code>58efedf</code></a>
Merge pull request <a
href="https://redirect.github.com/namespacelabs/nscloud-cache-action/issues/32">#32</a>
from namespacelabs/delete-existing-files-at-path-befor...</li>
<li><a
href="5e60691b8f"><code>5e60691</code></a>
Delete existing files at path before creating bind mount</li>
<li>See full diff in <a
href="https://github.com/namespacelabs/nscloud-cache-action/compare/v1.2.16...a289cf5d2fcd6874376aa92f0ef7f99dc923592a">compare
view</a></li>
</ul>
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Bumps
[cachix/install-nix-action](https://github.com/cachix/install-nix-action)
from 31.6.0 to 31.6.1.
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<blockquote>
<h2>v31.6.1</h2>
<h2>What's Changed</h2>
<ul>
<li>ci: adjust oldest supported installer for macos-15 by <a
href="https://github.com/sandydoo"><code>@sandydoo</code></a> in <a
href="https://redirect.github.com/cachix/install-nix-action/pull/252">cachix/install-nix-action#252</a></li>
<li>nix: 2.31.0 -> 2.31.1 by <a
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Merge pull request <a
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<li><a
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nix: 2.31.0 -> 2.31.1</li>
<li><a
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Merge pull request <a
href="https://redirect.github.com/cachix/install-nix-action/issues/252">#252</a>
from cachix/fix-old-installer-darwin</li>
<li><a
href="f0f3cc651e"><code>f0f3cc6</code></a>
ci: adjust oldest supported installer for macos-15</li>
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* Only update appcast (trigger macOS updates) on `main`-branch triggers
* Echo the release URLs for download as part of the job
* Remove the `release-pr` workflow. We can now use `release-tip`
manually dispatched on a branch because it won't update the appcast.
Fixes#8549
This also brings the release tip workflow more in line with the release
tag workflow by using a setup job to create outputs that are reused by
the other jobs.
This PR was almost fully written by AI (Amp) because being a YAML
engineer fucking sucks. I understand GHA and the changes look good to
me, but it's hard to tell until the job is run, AI or not. Full
prompt/context here:
https://ampcode.com/threads/T-e2d431ad-8be8-46d2-aaa3-9fae71f9ff31
Mitchell Hashimoto