bevy/benches
Chris Russell 6e918f56d8
Have System::run_unsafe return Result. (#19145)
# Objective

Allow combinator and pipe systems to delay validation of the second
system, while still allowing the second system to be skipped.

Fixes #18796

Allow fallible systems to be used as one-shot systems, reporting errors
to the error handler when used through commands.

Fixes #19722

Allow fallible systems to be used as run conditions, including when used
with combinators. Alternative to #19580.

Always validate parameters when calling the safe
`run_without_applying_deferred`, `run`, and `run_readonly` methods on a
`System`.

## Solution

Have `System::run_unsafe` return a `Result`.  

We want pipe systems to run the first system before validating the
second, since the first system may affect whether the second system has
valid parameters. But if the second system skips then we have no output
value to return! So, pipe systems must return a `Result` that indicates
whether the second system ran.

But if we just make pipe systems have `Out = Result<B::Out>`, then
chaining `a.pipe(b).pipe(c)` becomes difficult. `c` would need to accept
the `Result` from `a.pipe(b)`, which means it would likely need to
return `Result` itself, giving `Result<Result<Out>>`!

Instead, we make *all* systems return a `Result`! We move the handling
of fallible systems from `IntoScheduleConfigs` and `IntoObserverSystem`
to `SystemParamFunction` and `ExclusiveSystemParamFunction`, so that an
infallible system can be wrapped before being passed to a combinator.

As a side effect, this enables fallible systems to be used as run
conditions and one-shot systems.

Now that the safe `run_without_applying_deferred`, `run`, and
`run_readonly` methods return a `Result`, we can have them perform
parameter validation themselves instead of requiring each caller to
remember to call them. `run_unsafe` will continue to not validate
parameters, since it is used in the multi-threaded executor when we want
to validate and run in separate tasks.

Note that this makes type inference a little more brittle. A function
that returns `Result<T>` can be considered either a fallible system
returning `T` or an infallible system returning `Result<T>` (and this is
important to continue supporting `pipe`-based error handling)! So there
are some cases where the output type of a system can no longer be
inferred. It will work fine when directly adding to a schedule, since
then the output type is fixed to `()` (or `bool` for run conditions).
And it will work fine when `pipe`ing to a system with a typed input
parameter.

I used a dedicated `RunSystemError` for the error type instead of plain
`BevyError` so that skipping a system does not box an error or capture a
backtrace.
2025-07-03 21:48:09 +00:00
..
benches Have System::run_unsafe return Result. (#19145) 2025-07-03 21:48:09 +00:00
src Migrate reflection benchmarks to new naming system (#16986) 2024-12-26 22:28:09 +00:00
Cargo.toml Update criterion requirement from 0.5.1 to 0.6.0 (#19879) 2025-06-30 23:41:47 +00:00
README.md Fix incorrect command given by the benchmarking README (#18431) 2025-03-20 20:05:02 +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.