Optimize Large Data Reading in Code

Reviews PostgreSQL and MySQL tables (schema.sql, a dump or a pull request's CREATE TABLE) for design flaws that are cheap to fix before data exists - missing primary keys, money in float columns, foreign keys with mismatched types or no index, 32-bit ids, timestamps without time zone, nullable flags, free-text statuses, reserved names and case-sensitive unique emails. Returns corrected DDL. Includes a stdlib Python linter with --self-test.

Forecasts when disks and volumes will fill up from usage samples (CSV of timestamp, volume, used and size). Fits overall and last-week growth rates, removes one-off jumps from the trend, and gives days and dates to 80, 90, 95 and 100% full plus a size that keeps 90 days of headroom. Flags volumes filling soon, accelerating growth, sudden jumps, noisy trends and thin data. Includes a stdlib Python forecaster with --self-test.