# Summary
This PR resolves about the issue.
fixes #10810
And the formerly context is in the PR.
#22582
Here is an expected behaviour example with this change.
- 🦕.test.ts
```ts
import { assertEquals } from "https://deno.land/std@0.215.0/assert/mod.ts";
Deno.test("example test", () => {
assertEquals("🍋", "🦕");
});
```
This commit adds initial support for ".npmrc" files.
Currently we only discover ".npmrc" files next to "package.json" files
and discovering these files in user home dir is left for a follow up.
This pass supports "_authToken" and "_auth" configuration
for providing authentication.
LSP support has been left for a follow up PR.
Towards https://github.com/denoland/deno/issues/16105
Fixes #23571.
Previously, we required a `deno.json` to be present (or the `--lock`
flag) in order for us to resolve a `deno.lock` file. This meant that if
you were using deno in an npm-first project deno wouldn't use a
lockfile.
Additionally, while I was fixing that, I discovered there were a couple
bugs keeping the future `install` command from using a lockfile.
With this PR, `install` will actually resolve the lockfile (or create
one if not present), and update it if it's not up-to-date. This also
speeds up `deno install`, as we can use the lockfile to skip work during
npm resolution.
This PR removes the use of the custom `utc_now` function in favor of the
`chrono` implementation. It resolves #22864.
---------
Co-authored-by: Bartek Iwańczuk <biwanczuk@gmail.com>
This brings in [`runtimelib`](https://github.com/runtimed/runtimed) to
use:
## Fully typed structs for Jupyter Messages
```rust
let msg = connection.read().await?;
self
.send_iopub(
runtimelib::Status::busy().as_child_of(msg),
)
.await?;
```
## Jupyter paths
Jupyter paths are implemented in Rust, allowing the Deno kernel to be
installed completely via Deno without a requirement on Python or
Jupyter. Deno users will be able to install and use the kernel with just
VS Code or other editors that support Jupyter.
```rust
pub fn status() -> Result<(), AnyError> {
let user_data_dir = user_data_dir()?;
let kernel_spec_dir_path = user_data_dir.join("kernels").join("deno");
let kernel_spec_path = kernel_spec_dir_path.join("kernel.json");
if kernel_spec_path.exists() {
log::info!("✅ Deno kernel already installed");
Ok(())
} else {
log::warn!("ℹ️ Deno kernel is not yet installed, run `deno jupyter --install` to set it up");
Ok(())
}
}
```
Closes https://github.com/denoland/deno/issues/21619
The stderr stream from the LSP is consumed by a separate thread, so it
may not have processed the part we care about yet. Instead, wait until
you see the measure for the request you care about.
VScode will typically send a `textDocument/semanticTokens/full` request
followed by `textDocument/semanticTokens/range`, and occassionally
request semantic tokens even when we know nothing has changed. Semantic
tokens also get refreshed on each change. Computing semantic tokens is
relatively heavy in TSC, so we should avoid it as much as possible.
Caches the semantic tokens for open documents, to avoid making TSC do
unnecessary work. Results in a noticeable improvement in local
benchmarking
before:
```
Starting Deno benchmark
-> Start benchmarking lsp
- Simple Startup/Shutdown
(10 runs, mean: 383ms)
- Big Document/Several Edits
(5 runs, mean: 1079ms)
- Find/Replace
(10 runs, mean: 59ms)
- Code Lens
(10 runs, mean: 440ms)
- deco-cx/apps Multiple Edits + Navigation
(5 runs, mean: 9921ms)
<- End benchmarking lsp
```
after:
```
Starting Deno benchmark
-> Start benchmarking lsp
- Simple Startup/Shutdown
(10 runs, mean: 395ms)
- Big Document/Several Edits
(5 runs, mean: 1024ms)
- Find/Replace
(10 runs, mean: 56ms)
- Code Lens
(10 runs, mean: 438ms)
- deco-cx/apps Multiple Edits + Navigation
(5 runs, mean: 8927ms)
<- End benchmarking lsp
```
This PR directly addresses the issue raised in #23282 where Deno panics
if `deno coverage` is called with `--include` regex that returns no
matches.
I've opted not to change the return value of `collect_summary` for
simplicity and return an empty `HashMap` instead
Precursor to #23236
This implements the SNI features, but uses private symbols to avoid
exposing the functionality at this time. Note that to properly test this
feature, we need to add a way for `connectTls` to specify a hostname.
This is something that should be pushed into that API at a later time as
well.
```ts
Deno.test(
{ permissions: { net: true, read: true } },
async function listenResolver() {
let sniRequests = [];
const listener = Deno.listenTls({
hostname: "localhost",
port: 0,
[resolverSymbol]: (sni: string) => {
sniRequests.push(sni);
return {
cert,
key,
};
},
});
{
const conn = await Deno.connectTls({
hostname: "localhost",
[serverNameSymbol]: "server-1",
port: listener.addr.port,
});
const [_handshake, serverConn] = await Promise.all([
conn.handshake(),
listener.accept(),
]);
conn.close();
serverConn.close();
}
{
const conn = await Deno.connectTls({
hostname: "localhost",
[serverNameSymbol]: "server-2",
port: listener.addr.port,
});
const [_handshake, serverConn] = await Promise.all([
conn.handshake(),
listener.accept(),
]);
conn.close();
serverConn.close();
}
assertEquals(sniRequests, ["server-1", "server-2"]);
listener.close();
},
);
```
---------
Signed-off-by: Matt Mastracci <matthew@mastracci.com>
Moves sloppy import resolution from the loader to the resolver.
Also adds some test helper functions to make the lsp tests less verbose
---------
Co-authored-by: David Sherret <dsherret@gmail.com>
1. Generally we should prefer to use the `log` crate.
2. I very often accidentally commit `eprintln`s.
When we should use `println` or `eprintln`, it's not too bad to be a bit
more verbose and ignore the lint rule.
Fixes the `Debug Failure` errors described in
https://github.com/denoland/deno/issues/23643#issuecomment-2094552765 .
The issue here was that we were passing diagnostic codes as strings but
TSC expects the codes to be numbers. This resulted in some quick fixes
not working (as illustrated by the test added here which fails before
this PR).
The first commit is the actual fix. The rest are just test related.
A bunch of small things, mostly around timing and making sure the
jupyter kernel is actually running and ready to respond to requests. I
reproduced the flakiness by running a script to run a bunch of instances
of the test in parallel, where I could get failures consistently. After
this PR, I can't reproduce the flakiness locally which hopefully means
that applies to CI as well
