This guide provides information for developers who want to contribute to BenchBox or understand its internal architecture.
- Python 3.10+
uv(recommended for environment management)git
-
Clone the repository:
git clone https://github.com/joeharris76/benchbox.git cd BenchBox -
Create a virtual environment:
uv venv source .venv/bin/activate -
Install dependencies:
uv pip install -e .[dev,docs]
The
[dev]extra installs testing, linting, and typing tools. Combine it with[docs]when you plan to build the Sphinx documentation locally.
BenchBox uses pytest for testing. Run tests using either make commands or direct pytest:
# Fast tests for quick feedback
make test
# or
uv run -- python -m pytest -m fast
# Full test suite
make test-all
# or
uv run -- python -m pytest
# Unit tests only
make test-unit
# or
uv run -- python -m pytest -m unit
# Integration tests
make test-integration
# or
uv run -- python -m pytest -m "integration and not live_integration"
# With coverage (fast tests only - quick feedback)
make coverage-fast
# or full suite
make coverage-all
# or
uv run -- python -m pytest --cov=benchbox --cov-report=term-missingLinting and formatting run through Ruff:
make format
# or
uv run ruff format .
make lint
# or
uv run ruff check .Type checking is available via:
make typecheck
# or
uv run ty checkWe welcome contributions! Please see the CONTRIBUTING.md file in the root of the project for details on our development process, coding standards, and how to submit a pull request.
Maintainers (and AI agents working in this repo) use a retained pool of 10 git worktrees for parallel branch work. New work claims a free slot, runs there until merge, then releases it back. See the worktree-pool guide for common commands, slot states, and recovery scenarios. External contributors working from a fork do not need the pool.
See the release guide for the full
maintainer workflow (version-branch flow on a single repo with
develop and main).
BenchBox exposes a CLI-independent validation workflow through
benchbox.core.validation.ValidationService. The service orchestrates preflight,
manifest, database, and platform capability checks and returns structured
ValidationResult objects that mirror the data surfaced by the CLI.
Programmatic consumers can run comprehensive validation with:
from benchbox.core.validation import ValidationService
service = ValidationService()
results = service.run_comprehensive(
benchmark_type="tpcds",
scale_factor=1.0,
output_dir=output_path,
manifest_path=manifest_path,
connection=db_connection,
platform_adapter=adapter,
)
summary = service.summarize(results)This enables benchmarks, adapters, and external automation to reuse the same validation logic without importing CLI modules.
The CLI mirrors these capabilities via the benchbox run command. Use
--enable-preflight-validation, --enable-postgen-manifest-validation, and
--enable-postload-validation to toggle each stage while the core lifecycle
runner captures the resulting validation metadata.
Benchmarks use a lightweight lazy-loading system so the core package can start
quickly and only load optional dependencies when needed. See
docs/development/import-patterns.md for guidance on adding new benchmarks to
the registry, writing tests for lazy imports, and troubleshooting missing
dependency errors.