bevy/benches
Carter Anderson 4bca7f1b6d
Improved Command Errors (#17215)
# Objective

Rework / build on #17043 to simplify the implementation. #17043 should
be merged first, and the diff from this PR will get much nicer after it
is merged (this PR is net negative LOC).

## Solution

1. Command and EntityCommand have been vastly simplified. No more marker
components. Just one function.
2. Command and EntityCommand are now generic on the return type. This
enables result-less commands to exist, and allows us to statically
distinguish between fallible and infallible commands, which allows us to
skip the "error handling overhead" for cases that don't need it.
3. There are now only two command queue variants: `queue` and
`queue_fallible`. `queue` accepts commands with no return type.
`queue_fallible` accepts commands that return a Result (specifically,
one that returns an error that can convert to
`bevy_ecs::result::Error`).
4. I've added the concept of the "default error handler", which is used
by `queue_fallible`. This is a simple direct call to the `panic()` error
handler by default. Users that want to override this can enable the
`configurable_error_handler` cargo feature, then initialize the
GLOBAL_ERROR_HANDLER value on startup. This is behind a flag because
there might be minor overhead with `OnceLock` and I'm guessing this will
be a niche feature. We can also do perf testing with OnceLock if someone
really wants it to be used unconditionally, but I don't personally feel
the need to do that.
5. I removed the "temporary error handler" on Commands (and all code
associated with it). It added more branching, made Commands bigger /
more expensive to initialize (note that we construct it at high
frequencies / treat it like a pointer type), made the code harder to
follow, and introduced a bunch of additional functions. We instead rely
on the new default error handler used in `queue_fallible` for most
things. In the event that a custom handler is required,
`handle_error_with` can be used.
6. EntityCommand now _only_ supports functions that take
`EntityWorldMut` (and all existing entity commands have been ported).
Removing the marker component from EntityCommand hinged on this change,
but I strongly believe this is for the best anyway, as this sets the
stage for more efficient batched entity commands.
7. I added `EntityWorldMut::resource` and the other variants for more
ergonomic resource access on `EntityWorldMut` (removes the need for
entity.world_scope, which also incurs entity-lookup overhead).

## Open Questions

1. I believe we could merge `queue` and `queue_fallible` into a single
`queue` which accepts both fallible and infallible commands (via the
introduction of a `QueueCommand` trait). Is this desirable?
2025-01-10 04:15:50 +00:00
..
benches Improved Command Errors (#17215) 2025-01-10 04:15:50 +00:00
src Migrate reflection benchmarks to new naming system (#16986) 2024-12-26 22:28:09 +00:00
Cargo.toml Allow clippy::too_many_arguments to lint without warnings (#17249) 2025-01-09 07:26:15 +00:00
README.md Add benchmarks and compile_fail tests back to workspace (#16858) 2024-12-21 22:30:29 +00:00

Bevy Benchmarks

This is a crate with a collection of benchmarks for Bevy.

Running benchmarks

Benchmarks can be run through Cargo:

# Run all benchmarks. (This will take a while!)
cargo bench -p benches

# Just compile the benchmarks, do not run them.
cargo bench -p benches --no-run

# Run the benchmarks for a specific crate. (See `Cargo.toml` for a complete list of crates
# tracked.)
cargo bench -p benches --bench ecs

# Filter which benchmarks are run based on the name. This will only run benchmarks whose name
# contains "name_fragment".
cargo bench -p benches -- name_fragment

# List all available benchmarks.
cargo bench -p benches -- --list

# Save a baseline to be compared against later.
cargo bench -p benches --save-baseline before

# Compare the current benchmarks against a baseline to find performance gains and regressions.
cargo bench -p benches --baseline before

Criterion

Bevy's benchmarks use Criterion. If you want to learn more about using Criterion for comparing performance against a baseline or generating detailed reports, you can read the Criterion.rs documentation.