[Task link](https://www.pivotaltracker.com/story/show/182194574).
[ci no changelog needed]
This PR implements a new selection box that will replace an old (not really working) one in the component browser. The old selection box wasn't working well with the headers of the component groups, so we were forced to make a much harder implementation.
The new implementation duplicates some visual components and places them in a separate layer. Then, a rectangular mask cuts off everything that is not "selected". This way:
- We have more control over what the selected entries should look like.
- We can easily support the multi-layer structure of the component groups with headers.
- We avoid problems with nested masks that our renderer doesn't support at the moment.
To be more precise, we duplicate the following:
- Background of the component group becomes the "fill" of the selection.
- Entries text and icons - we can alter them easily.
- Header background and header text. By placing them in separate scene layers we ensure correct rendering order.
https://user-images.githubusercontent.com/6566674/173657899-1067f538-4329-44f9-9dc2-78c8a4708b5a.mp4
# Important Notes
- This PR implements the base of our future selection mechanism, selecting entries with a mouse and keyboard still has several issues that will be fixed in the future tasks.
- The scrolling behavior will also be improved in future tasks. Right we only restrict the selection box position so that it never leaves the borders of the component group.
- I added a new function to `add` shapes to new layers in a non-exclusive way (we had only `add_exclusive`) before. I have no idea how we didn't use this feature before even though we mention it a lot in the docs.
- The demo scene restricts the position of the selection box for one-column component groups but does not for the wide component group.
### Pull Request Description
Using the new tooling (#3491), I investigated the **performance / compile-time tradeoff** of different codegen options for release mode builds. By scripting the testing procedure, I was able to explore many possible combinations of options, which is important because their interactions (on both application performance and build time) are complex. I found **two candidate profiles** that offer specific advantages over the current `release` settings (`baseline`):
- `thin16`: Supports incremental compiles in 1/3 the time of `baseline` in common cases. Application runs about 2% slower than `baseline`.
- `fat1-O4`: Application performs 13% better than `baseline`. Compile time is almost 3x `baseline`, and non-incremental.
(See key in first chart for the settings defining these profiles.)
We can build faster or run faster, though not in the same build. Because the effect sizes are large enough to be impactful to developer and user experience, respectively, I think we should consider having it both ways. We could **split the `release` profile** into two profiles to serve different purposes:
- `release`: A profile that supports fast developer iteration, while offering realistic performance.
- `production`: A maximally-optimized profile, for nightly builds and actual releases.
Since `wasm-pack` doesn't currently support custom profiles (rustwasm/wasm-pack#1111), we can't use a Cargo profile for `production`; however, we can implement our own profile by overriding rustc flags.
### Performance details
As you can see, `thin16` is slightly slower than `baseline`; `fat1-O4` is dramatically faster.
<details>
<summary>Methodology (click to show)</summary>
I developed a procedure for benchmarking "whole application" performance, using the new "open project" workflow (which opens the IDE and loads a complex project), and some statistical analysis to account for variance. To gather this data:
Build the application with profiling:
`./run.sh ide build --profiling-level=debug`
Run the `open_project` workflow repeatedly:
`for i in $(seq 0 9); do dist/ide/linux-unpacked/enso --entry-point profile --workflow open_project --save-profile open_project_thin16_${i}.json; done`
For each profile recorded, take the new `total_self_time` output of the `intervals` tool; gather into CSV:
`echo $(for i in $(seq 0 9); do target/rust/debug/intervals < open_project_thin16_${i}.json | tail -n1 | awk '{print $2}'; do`
(Note that the output of intervals should not be considered stable; this command may need modification in the future. Eventually it would be nice to support formatted outputs...)
The data is ready to graph. I used the `boxplot` method of the [seaborn](https://seaborn.pydata.org/index.html) package, in order to show the distribution of data.
</details>
#### Build times
In the case of changing a file in `enso-prelude`, with the current `baseline` settings rebuilding takes over 3 minutes. With the `thin16` settings, the same rebuild completes in 40 seconds.
(To gather this data on different hardware or in the future, just run the new `bench-build.sh` script for each case to be measured.)
Define some workflows for batch-mode profiling.
Implemented:
- collapse nodes
- create node
- enter collapsed node
- new project
- open visualization
They can currently be built and run with a command like:
`./run.sh ide build --profiling-level=debug && dist/ide/linux-unpacked/enso --entry-point profile --workflow create_node --save-profile out.json`
And the data can be displayed with:
`dist/ide/linux-unpacked/enso --entry-point profiling_run_graph --load-profile out.json`
Demo of recording and viewing a profile with a command-line one-liner:
https://user-images.githubusercontent.com/1047859/169954795-2d9520ca-84f9-45d2-b83a-5063ebe6f718.mp4
See: https://www.pivotaltracker.com/story/show/182195399.
# Important Notes
- When defining workflows, two helpers are enough to allow us to tell when the action is really done: `Fixture::compile_new_shaders`, and `Fixture::backend_execution`. Often, it is appropriate to await both, but it depends on the task.
- The shader compiler is now driven by a `Controller`; while the `Compiler` is reset if context is lost, the `Controller`'s state survives context loss.
- A new `--load-profile` option supports specifying a profile by path when running `profiling_run_graph`.
- Drop the `with_same_start` profiler interface; we ended up preferring a child profiler convention, and this interface was not implemented compatibly with the stricter data model we've had since the introduction of `profiler::data`.
- Fix the noisy `rustfmt` output.
* The bash entry point was renamed `run.sh` -> `run`. Thanks to that `./run` works both on Linux and Windows with PowerShell (sadly not on CMD).
* Everyone's favorite checks for WASM size and program versions are back. These can be disabled through `--wasm-size-limit=0` and `--skip-version-check` respectively. WASM size limit is stored in `build-config.yaml`.
* Improved diagnostics for case when downloaded CI run artifact archive cannot be extracted.
* Added GH API authentication to the build script calls on CI. This should fix the macOS build failures that were occurring from time to time. (Actually they were due to runner being GitHub-hosted, not really an OS-specific issue by itself.)
* If the GH API Personal Access Token is provided, it will be validated. Later on it is difficult to say, whether fail was caused by wrong PAT or other issue.
* Renamed `clean` to `git-clean` as per suggestion to reduce risk of user accidently deleting unstaged work.
* Whitelisting dependabot from changelog checks, so PRs created by it are mergeable.
* Fixing issue where wasm-pack-action (third party) randomly failed to recognize the latest version of wasm-pack (macOS runners), leading to failed builds.
* Build logs can be filtered using `ENSO_BUILD_LOG` environment variable. See https://docs.rs/tracing-subscriber/0.3.11/tracing_subscriber/struct.EnvFilter.html#directives for the supported syntax.
* Improve help for ci-run source, to make clear that PAT token is required and what scope is expected there.
Also, JS parts were updated with some cleanups and fixes following the changes made when introducing the build script.
