Also upgrade the test project to LTS 3.1 dotnet framework, as MS is
making it very difficult to get framework 2.2 anymore.
Also remove some object files which apparently were included in the
repo.
The gradle wrapper is too large of a dependency to include for every
download of vimspector. Users can use a local installation of gradle to
run the sample kotlin application if necessary.
The example was was using 'launchCommand' which is not valid according
to the schema; it should be 'runCommand'.
But also, it never really worked. Vimspector would start the "adapter"
(in this case, try and connect to the TCP port) before running the
"prepare" commands, wich in this case would actually start debugpy
listening. So to solve that we run the prepare commands earlier.
Hopefully this won't cause a regression for Java and C++ remote attach,
which we don't really have tests for.
Finally, due to the way docker works, when you forward a port and
nothing is listening on it, docker _accepts_ the connection then
immediately drops it. This is _super_ annoying meaning that it looks to
vimspector liek the server instantly dies if it takes nonzero time for
the remote commands to open the port. So to solve this we add loaunch
and attach delays which can be configured in the adapter config. This
actually solves a prolem where the java debugger just takes agest to
attach on remote launch too.
(Finally, finally...) updated the vimspector schema to represent
the real launch/attach remote configuration, which was incorrectly
spec'd at the adapter level, but it's actually per launch/attach block.
Change lua test files to call `require 'lldebugger'` only when using
love, because it's not needed with lua or luajit. Also add `stopOnEntry`
key to test `.vimspector.json` because it works correctly with this
change.
Change Dockerfile to install lua, luajit and love and also to install
nodejs 12 needed to build the lua debug adapter. Create the
love-headless test in support/test/lua to test love without an x server.
We add a 'temporary' option to line breakpionts and try and clear any
temporary breakpionts on the line we end up stopping on. This might not
be art, but _probably_ works in almost all cases that matter.
it's a bit hacky the way we have to push the reason around, but we don't
know where we stopped until we actually get the stack trace response and
SetCurrentFrame
Move temporary breakpionts to match server response
Also delete any existing ones when adding a new one and add tests for
run-to-cursor.
Only continue after we successfully set the breakpoints. This makes it
work in go
It seems that the behaviour of the start parameter being missing is
server (or perhaps a specific client) dependent. The specification
clearely says that it should be inserted at the column of the original
request, but the servers clearly expect either for that column to be the
beginning of an identifier or for the client to ignore the spec and
request from that position anyway.
Reading the VSCode code, we see that the 'word' before the cursor is
guessed, and if only if BOTH 'start' AND 'length' are supplied, then
they are used to determine where insertion starts, otherwise the current
'word' is used. Unclear what 'word' means in the specific contexts, but
we're relying on iskeyword.
Initially I considered using #i, #s, etc. to coerce to specific types,
but then it wasn't clear of the semantics (particularly for bool, where
JSON bool true/false, Python bool True/False).
But it turns out that we can just coerce any key from a JSON string.
Users can _probably_ type JSON strings for most things, or use variables
to run scripts to generate them, this allows essentially complete
flexibility to define the data types needed to populate the launch spec.
The purpose of this is to allow some level of automated setup by
requesting data from the user and then (subsequently) saving the
flattneed config to the vimspector config file.
Debate rages about whether JSON should have comments. The specification
says it shouldn't but the author of JSON suggested that if you want to
use JSON for configuration, then pipe it through jsmin before parsing.
So that's what we do, using a tiny JSON minifier from
https://github.com/getify/JSON.minify/tree/pythonCloses#135
