BenchBox reads configuration from three layers, highest precedence first:
- CLI options - flags supplied to
benchbox run,benchbox export, etc. - Environment variables - primarily tuning overrides (see below).
- Configuration files -
benchbox.yamlin the working directory or~/.benchbox/config.yaml.
If no file is present, BenchBox uses sensible defaults. You can generate a tuning template with uv run -- benchbox tuning init --platform duckdb.
# benchbox.yaml
benchmarks:
default_scale: 0.1
continue_on_error: false
database:
preferred: duckdb
connection_timeout: 30
output:
directory: ./benchmark_runs/results
formats: [json, console]
execution:
power_run:
iterations: 3
warm_up_iterations: 1
concurrent_queries:
enabled: falseSave the file next to your project and run:
uv run -- benchbox run --benchmark tpch --platform duckdbCLI flags still win. For example --scale 1 overrides benchmarks.default_scale for that invocation only.
BenchBox searches in this order:
./benchbox.yaml~/.benchbox/config.yaml
Files are parsed as YAML and merged with built-in defaults defined in benchbox.cli.config.ConfigManager. Unknown keys are preserved so you can store project metadata alongside official sections (system, database, benchmarks, output, execution, tuning).
Use these helpers when you need to inspect or persist configuration programmatically:
from benchbox.cli.config import ConfigManager
config = ConfigManager() # auto-detects benchbox.yaml
scale = config.get("benchmarks.default_scale")
config.set("execution.power_run.iterations", 5)
config.save_config()benchbox.utils.ExecutionConfigHelper wraps common tuning operations. It works with or without an existing config file.
from benchbox.utils import ExecutionConfigHelper
helper = ExecutionConfigHelper()
# Enable a quick power run profile
helper.enable_power_run_iterations(iterations=3, warm_up_iterations=1)
# Turn on concurrent streams and optimise for hardware
helper.enable_concurrent_queries(max_concurrent=4)
helper.optimize_for_system(cpu_cores=16, memory_gb=64)The helper updates the active configuration provider, so CLI runs pick up the changes once you call config.save_config() or invoke the helper with an explicit ConfigManager instance.
Some tuning settings can be toggled at deploy time without editing files. The default mapping is stored under tuning.environment_overrides:
| Environment variable | Maps to | Typical values |
|---|---|---|
BENCHBOX_TUNING_CONFIG |
tuning.default_config_file |
Path to a YAML file |
Point BENCHBOX_TUNING_CONFIG at a configuration checked into your repo to make it the default whenever --tuning tuned is used (see Tuning Commands for the full --tuning resolution order). To actually enable tuned runs in CI, pass --tuning tuned (or --tuning auto) on the benchbox run command line; there is no environment variable that turns tuning on by itself.
Before running large jobs, dry-run the plan and validate dependencies:
# Render the execution plan without running anything
uv run -- benchbox run --dry-run ./plan --platform duckdb --benchmark tpch
# Check platform requirements declared in the config
uv run -- benchbox check-deps --matrixbenchbox run respects values from benchbox.yaml, so you can set project defaults once and execute repeatable runs with only a few flags.
uv run -- benchbox tuning init- scaffold a tuning YAML file for a specific platform.uv run -- benchbox validate --config benchbox.yaml- ensure configuration syntax and schema are valid.uv run -- benchbox platforms setup- interactively enable adapters defined in your config.
See the CLI reference for detailed command usage and the examples library for advanced automation patterns.