Update the exports to rely on the bulk endpoint for speed #74
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* Custom curves to and from dataframe * Upload custom curves runner, scenario methods and validation on the model * Custom curves: tests for runner, scenario and validation
* Start from excel bulk * Improved styling for packer * Unpack for inputs and metadata first implementation no tests * Unpack for sortables and custom curves early commit before playing around * From dataset for sortables * Parse options from main sheet to enable repeating submodels across all scenarios listed in main * Added gqueries * WIP refactoring packer to suite new input format - partially working * New excel format working pre-clean up * Split packer into individual packs * Simplify query processing * Tests for query pack and custom curves pack * Fix tests for multi-index * Simplifying normalisation * Simplifying inputs pack * Improved tests * refining notebooks --------- Co-authored-by: Nora Schinkel <ncschinkel@gmail.com>
* Export output curves to a separate file by default on to_excel * Swap from pipenv to poetry * Clean up Jupyter notebooks
* Updating how you handle title in meta
* Clearing notebooks, updating poetry and handling setting environment not base url * Update readme and input excel * Tidying output format in Jupyter Notebooks * PARAMETERS to SLIDER_SETTINGS * Min max once at the start of slider_settings * Fix metadata output and refine scenario to_dataframe * Fix custom curve handling and avoid double caching issue
* Updated tests * Added fetching a scenario directly in the Jupyter notebook to the example * Convert from yml settings to .env * Separated inputs and outputs into their own folders at root
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noracato
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| df = pd.read_csv(io.StringIO(csv_text), index_col=0) | ||
| except Exception as e: | ||
| return ServiceResult.fail([f"Failed to parse bulk CSV: {e}"]) | ||
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| results: Dict[str, io.StringIO] = {} | ||
| warnings: list[str] = [] | ||
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| groups: Dict[str, list[str]] = {} | ||
| for col in df.columns: | ||
| base = str(col) | ||
| for sep in (":", "/"): | ||
| if sep in base: | ||
| base = base.split(sep, 1)[0] | ||
| break | ||
| groups.setdefault(base, []).append(col) | ||
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| for base, cols in groups.items(): | ||
| try: | ||
| sub = df[cols].dropna(how="all") | ||
| buf = io.StringIO() | ||
| sub.to_csv(buf, index=True) | ||
| buf.seek(0) | ||
| results[base] = buf | ||
| except Exception as e: | ||
| warnings.append(f"{base}: Failed to prepare CSV: {e}") | ||
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There was a problem hiding this comment.
This logic does not belong here unfortunately. But we can fix it later.
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@noracato I think with the new async approach this is an unnecessary change - it is 5 seconds slower than the async approach. If you agree I would close this PR and the Engine one as they are unnecessary. |
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Goes with this PR for ETEngine