Add --gzip-large-csvs flag to compress large result CSVs#117
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…hold After all *Results() writers finish but before the run-status sentinel JSON is written, scan the output directory and rewrite every oT_Result_*.csv whose uncompressed size is at least --gzip-threshold-mb (default 5 MB) as .csv.gz. Pandas reads .csv.gz transparently with compression='infer', so downstream tooling needs no change. Opt-in: default behaviour is bit-for-bit identical to before. The sentinel JSON gains three new fields (gzip_threshold_mb, gzip_files, gzip_mb_saved) reporting what the pass did. Verified on the bundled 9n case: 2 of 87 CSVs cleared the 5 MB threshold and shrank ~6x (6.46 -> 1.05 MB, 6.98 -> 1.11 MB); pandas read-back parity matches shape and frame equality with the plain-CSV baseline. EOF
Changes:
- Drop --gzip-threshold-mb; add --gzip-patterns (comma-separated
name-prefixes, applied after the leading 'oT_Result_').
- Default pattern set: Generation, Consumption, Balance, MarketResults,
Network — exposed as openTEPES.DEFAULT_GZIP_PATTERNS for reuse.
- Help text now flags the Excel caveat explicitly (.csv.gz cannot be
opened directly in Excel).
- Sentinel JSON: gzip_threshold_mb -> gzip_patterns.
Verified on bundled 9n: under default patterns, 49 of 87 oT_Result_*.csv
files compress, saving 31 MB (56 MB -> 25 MB total). Read-back parity
passes on the largest tables (shape + frame equality).
EOF
arght
approved these changes
May 25, 2026
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Summary
--gzip-large-csvs(+--gzip-threshold-mb,default 5) for
openTEPES_Main.openTEPES_runrewritesoT_Result_*.csvfilesat or above the threshold as
.csv.gz. Pandas reads the resultnatively; downstream tooling unchanged.
gzip_threshold_mb,gzip_files,gzip_mb_savedfor batch monitoring.Behaviour
writer has finished. Pure rename pass, no chained-DataFrame churn.
Test plan
baseline (sentinel reports
gzip_files: 0).--gzip-large-csvsat default 5 MB → 2/87 CSVscompressed (~6x shrink); pandas read-back parity passes
(
shape,.equals()).