Pr/84 - #87
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Pr/84#87
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- SimulationEngine.from_asset_system(asset_system): Pydantic → DuckDB - SimulationEngine.from_parquet(path): Parquet file → DuckDB - SimulationEngine.load_from_asset_system(): load existing results into engine - SimulationEngine.to_asset_states(): DuckDB → list of AssetState objects - AssetSystem.from_engine(engine): DuckDB → full Pydantic AssetSystem
- New CLI commands: erad engine run|convert|query|info - engine run: run simulation via DuckDB, export to parquet/sqlite/csv - engine convert: convert between result formats - engine query: SQL queries against result files - engine info: summary statistics for result files - New docs page: simulation/engine.ipynb - Added wind_gust to docs TOC
…ies) - Updated org name in README, docs/intro.md - Updated author/maintainer emails to @nlr.gov - Updated badge links from NREL/erad to NLR-Distribution-Suite/erad - Package name remains NREL-erad on PyPI for backward compatibility
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This pull request introduces a major feature: a new DuckDB-powered simulation engine for ERAD, which enables high-performance, scalable simulations and flexible data export. It also adds a comprehensive command-line interface (CLI) for running, converting, querying, and summarizing simulation results, and updates the documentation to reflect these enhancements. Several minor fixes and improvements are included as well.
Simulation Engine and CLI Enhancements:
src/erad/engine/core.py,src/erad/cli.py,docs/simulation/engine.ipynb). [1] [2] [3]erad enginewith subcommands for running simulations, converting between formats, querying results with SQL, and displaying summary statistics (src/erad/cli.py). [1] [2]docs/_toc.yml,docs/simulation/engine.ipynb). [1] [2]Project and Metadata Updates:
0.1.14to reflect the new features (src/erad/__init__.py).pyproject.toml).Documentation and Branding:
README.md). [1] [2]These changes significantly improve ERAD's scalability, usability for large datasets, and user experience via both Python and the CLI.