Module benchmarking

Expand description

Staking pallet benchmarking.

Modules§

baseline: A set of benchmarks which can establish a global baseline for all other benchmarking. These benchmarks do not require a pallet to be deployed.
v1: Macros for benchmarking a FRAME runtime.

add_benchmark: This macro adds pallet benchmarks to a Vec<BenchmarkBatch> object.
assert_impl_all: Asserts that the type implements all of the given traits.
assert_type_eq_all: Asserts that all types in a list are equal to each other.
benchmarks_instance: Same as benchmarks but for instantiable module.
benchmarks_instance_pallet: Same as benchmarks but for instantiable pallet declared frame_support::pallet.
define_benchmarks: Defines pallet configs that add_benchmarks and list_benchmarks use. Should be preferred instead of having a repetitive list of configs in add_benchmark and list_benchmark.
impl_benchmark_test_suite: This creates a test suite which runs the module’s benchmarks.
list_benchmark: This macro allows users to easily generate a list of benchmarks for the pallets configured in the runtime.
validate_pov_mode: Validates the passed pov_modes.
whitelist: Whitelist the given account.
whitelist_account

Analysis
BenchmarkBatch: The results of a single of benchmark.
BenchmarkBatchSplitResults: The results of a single of benchmark, where time and db results are separated.
BenchmarkConfig: Configuration used to setup and run runtime benchmarks.
BenchmarkList: A list of benchmarks available for a particular pallet and instance.
BenchmarkMetadata
BenchmarkRecording: Records the time and proof size of a single benchmark iteration.
BenchmarkResult: Result from running benchmarks on a FRAME pallet. Contains duration of the function call in nanoseconds along with the benchmark parameters used for that benchmark result.
Linear: Used by the new benchmarking code to specify that a benchmarking variable is linear over some specified range, i.e. Linear<0, 1_000> means that the corresponding variable is allowed to range from 0 to 1000, inclusive.

AnalysisChoice
BenchmarkError: Possible errors returned from the benchmarking pipeline.
BenchmarkParameter: An alphabet of possible parameters to use for benchmarking.
BenchmarkSelector

Benchmark: Runtime api for benchmarking a FRAME runtime.
Benchmarking: The pallet benchmarking trait.
BenchmarkingSetup: The required setup for creating a benchmark.
ParamRange: Trait that must be implemented by all structs that can be used as parameter range types in the new benchmarking code (i.e. Linear<0, 1_000>). Right now there is just Linear but this could later be extended to support additional non-linear parameter ranges.
Recording: The recording trait used to mark the start and end of a benchmark.

account: Grab an account, seeded by a name and index.
current_time: Get the number of nanoseconds passed since the UNIX epoch
show_benchmark_debug_info: show error message and debugging info for the case of an error happening during a benchmark
whitelisted_caller: This caller account is automatically whitelisted for DB reads/writes by the benchmarking macro.

benchmark: An attribute macro used to declare a benchmark within a benchmarking module. Must be attached to a function definition containing an #[extrinsic_call] or #[block] attribute.
benchmarks: An attribute macro that can be attached to a (non-empty) module declaration. Doing so will designate that module as a benchmarking module.
block: An attribute macro used to specify that a block should be the measured portion of the enclosing benchmark function, This attribute is also used as a boundary designating where the benchmark setup code ends, and the benchmark verification code begins.
extrinsic_call: An attribute macro used to specify the extrinsic call inside a benchmark function, and also used as a boundary designating where the benchmark setup code ends, and the benchmark verification code begins.
instance_benchmarks: An attribute macro that can be attached to a (non-empty) module declaration. Doing so will designate that module as an instance benchmarking module.