- config.yaml: remove ambiguousorinvalidcolumn linter rule (false positives on read_csv TVFs) - fct_cot_positioning: use TRY_CAST throughout — CFTC uses '.' as null in many columns - raw/cot_disaggregated: add columns() declaration for 33 varchar cols - dim_commodity: switch from SEED to FULL model with SQL VALUES to preserve leading zeros Pandas auto-converts '083' → 83 even with varchar column declarations in SEED models - seeds/dim_commodity.csv: correct cftc_commodity_code from '083731' (contract market code) to '083' (3-digit CFTC commodity code); add CSV quoting - test_cot_foundation.yaml: fix output key name, vars for time range, partial: true, and correct cftc_commodity_code to '083' - analytics.py: COFFEE_CFTC_CODE '083731' → '083' to match actual data Result: serving.cot_positioning has 685 rows (2013-01-08 to 2026-02-17), 23/23 tests pass. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
24 lines
1012 B
SQL
24 lines
1012 B
SQL
-- Commodity dimension: conforms identifiers across source systems.
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--
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-- This is the ontology. Each row is a commodity tracked by BeanFlows.
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-- As new sources are added (ICO, futures prices, satellite), their
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-- commodity identifiers are added as columns here — not as separate tables.
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-- As new commodities are added (cocoa, sugar), rows are added here.
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--
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-- References:
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-- usda_commodity_code → raw.psd_alldata.commodity_code (numeric string, e.g. '0711100')
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-- cftc_commodity_code → raw.cot_disaggregated.cftc_commodity_code (3-char, e.g. '083')
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--
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-- NOTE: Defined as FULL model (not SEED) to guarantee leading-zero preservation.
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-- Pandas CSV loading converts '083' → 83 even with varchar column declarations.
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MODEL (
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name foundation.dim_commodity,
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kind FULL
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);
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SELECT usda_commodity_code, cftc_commodity_code, commodity_name, commodity_group
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FROM (VALUES
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('0711100', '083', 'Coffee, Green', 'Softs')
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) AS t(usda_commodity_code, cftc_commodity_code, commodity_name, commodity_group)
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