Scope, stated in the card because it was only ever implicit: this dataset stops
at the unit. Dimensions, volumes, capacity, nesting, naming and standards
conformance for the tote itself; pallet builds, container loads and shelving
layouts are out. The one deliberate exception is eur1_pallet_per_layer, which is
the last figure that is purely a property of the box — everything past it depends
on build height and pallet standard, which are decisions rather than dimensions.
The card now also says what the thing is for: pallet, shelving and consolidation
calculations, and comparison on cost per usable litre.
Both unit systems on every row, in both tables, plus capacity in US gallons. The
comparison this dataset exists for is cross-market and one of the four vendors
designs in inches, so making half the readers convert before they can compare two
rows is where mistakes happen. listings.csv gains native_unit — which side is the
vendor's own figure and which is the conversion — because the de…
Eight pages, rendered from containers.csv and listings.csv rather than typed:
a family per section, each footprint's sizes with typical internal dimensions,
external volume, usable capacity and the vendor range, then the per-vendor
internal figures that range was computed from. Sources and naming pages at the
back.
container_stats.py now holds the per-vendor statistics that build.py and the
PDF both state as fact — same numbers, one definition. build.py output is
unchanged by that refactor, verified byte-for-byte.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
