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The old `vscode` package is outdated and it is recommened to switch to
these two new packages. This also solves a problem of a missing `.d.ts`
for `vscode` in Nixos.
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In most cases the primary label span repeats information found elsewhere
in the diagnostic. For example, with E0061:
```
{
"message": "this function takes 2 parameters but 3 parameters were supplied",
"spans": [{"label": "expected 2 parameters"}]
}
```
However, with some mismatched type errors (E0308) the expected type only
appears in the primary span's label, e.g.:
```
{
"message": "mismatched types",
"spans": [{"label": "expected usize, found u32"}]
}
```
I initially added the primary span label to the message unconditionally.
However, for most error types the child diagnostics repeat the primary
span label with more detail. `rustc` also renders the duplicate text but
because the span label and child diagnostics appear in visually distinct
places it's not as confusing.
This takes a heuristic approach where it will only add the primary span
label if there are no child message lines.
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There are two issues with the implementation of `provideCodeActions`
introduced in #1439:
1. We're returning the code action based on the file its diagnostic is
in; not the file the suggested fix is in. I'm not sure how often
fixes are suggested cross-file but it's something we should handle.
2. We're not filtering code actions based on the passed range. The means
if there is any suggestion in a file we'll show an action for every
line of the file. I naively thought that VS Code would filter for us
but that was wrong.
Unfortunately the VS Code `CodeAction` object is very complex - it can
handle edits across multiple files, run commands, etc. This makes it
complex to check them for equality or see if any of their edits
intersects with a specified range.
To make it easier to work with suggestions this introduces a
`SuggestedFix` model object and a `SuggestFixCollection` code action
provider. This is a layer between the raw Rust JSON and VS Code's
`CodeAction`s. I was reluctant to introduce another layer of abstraction
here but my attempt to work directly with VS Code's model objects was
worse.
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Currently all of our VS Code diagnostics are given the source of
`rustc`. However, if you have something like `cargo-watch.command` set
to `clippy` it will also watch for Clippy lints. The `rustc` source is a
bit misleading in that case.
Fortunately, Rust's tool lints (RFC 2103) line up perfectly with VS
Code's concept of `source`. This checks for lints scoped to a given tool
and then splits them in to a `source` and tool-specific `code`.
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As promised in #1439 this is an initial attempt at unit testing the
VSCode extension. There are two separate parts to this: getting the test
framework working and unit testing the code in #1439.
The test framework nearly intact from the VSCode extension generator.
The main thing missing was `test/index.ts` which acts as an entry point
for Mocha. This was simply copied back in. I also needed to open the
test VSCode instance inside a workspace as our file URI generation
depends on a workspace being open.
There are two ways to run the test framework:
1. Opening the extension's source in VSCode, pressing F5 and selecting
the "Extensions Test" debug target.
2. Closing all copies of VSCode and running `npm test`. This is started
from the command line but actually opens a temporary VSCode window to
host the tests.
This doesn't attempt to wire this up to CI. That requires running a
headless X11 server which is a bit daunting. I'll assess the difficulty
of that in a follow-up branch. This PR is at least helpful for local
development without having to induce errors on a Rust project.
For the actual tests this uses snapshots of `rustc` output from a real
Rust project captured from the command line. Except for extracting the
`message` object and reformatting they're copied verbatim into fixture
JSON files.
Only four different types of diagnostics are tested but they represent
the main combinations of code actions and related information possible.
They can be considered the happy path tests; as we encounter
corner-cases we can introduce new tests fixtures.
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