perf(viewer): share one mtime-keyed cache for the trends CSV and dir listing - #555
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| return None | ||
|
|
||
| logging.info(f"Loaded {len(df)} rows from trends cache.") | ||
| _TRENDS_DF_CACHE = (mtime, df) |
| d for d in os.listdir(results_dir) | ||
| if os.path.isdir(os.path.join(results_dir, d)) | ||
| ] | ||
| _RUN_DIRS_CACHE = (mtime, dirs) |
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…listing trends_cache.csv was reparsed on every render by the Status tab, the Charts tab and the run detail view, and the results directory was relisted three times per page load. On the GCS FUSE mount each listing costs one stat per run directory, so both scaled with the number of runs and ran on interactions that needed neither. Add load_trends_df and list_run_dirs, keyed on mtime, and route every caller through them. load_summaries now builds on load_trends_df so the CSV is parsed once rather than twice. The frame is now shared, so the Charts filter chain uses assign() rather than an in-place column write, which would otherwise have welded product_dataset onto the cached object.
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trends_cache.csv was reparsed on every render by the Status tab, the
Charts tab and the run detail view, and the results directory was
relisted three times per page load. On the GCS FUSE mount each listing
costs one stat per run directory, so both scaled with the number of runs
and ran on interactions that needed neither.
Add load_trends_df and list_run_dirs, keyed on mtime, and route every
caller through them. load_summaries now builds on load_trends_df so the
CSV is parsed once rather than twice.
The frame is now shared, so the Charts filter chain uses assign() rather
than an in-place column write, which would otherwise have welded
product_dataset onto the cached object.
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