crates.io data-ecosystem download velocity (monthly)

Monthly download-velocity ranking of Rust crates in the data/ML ecosystem. Nine data-relevant crates.io categories (artificial-intelligence, computer-vision, data-structures, database, database-implementations, mathematics, science, simulation, visualization) — the official curator-assigned category listings — are crawled in recent-downloads order into a candidate universe; the keyless crates.io API supplies per-version daily download series, aggregated to trailing-30-day and prior-30-day totals, and the latest non-yanked version's license and publication date. Crates clearing the 10,000-download floor are classified into a curated 9-category taxonomy by a deterministic ordered rule set over their category membership and keywords. The velocity score is the min-max-normalized trailing-30d download count (0-100) and the growth score the min-max-normalized month-over-month growth rate (clipped to -100%/+1000%; new entrants pinned to the +1000% cap and flagged); trend_score is their 50/50 composite (0-100) and trend_rank orders by trend_score descending (ties: trailing-30d downloads desc, then crate name). Columns: month, fetch timestamp, crate name / URL / latest version / description / license id / publication date, categories / taxonomy category, exact source API URL for each row value (daily downloads series, latest-version record — any number is one GET away from its source), trailing-30d and prior-30d downloads, 60d total and per-day average, growth rate, new-entrant flag, velocity/growth/trend scores (0-100), trend rank. fetched_at is the trailing window end (UTC day granularity), so re-ingesting the same window is a no-op. Primary key: (month, crate_name). Cadence: monthly. Nullability: license_id and published_date may be empty when upstream supplies none; scores and ranks are never null. Caveats: crates.io counts CDN downloads (automated and CI traffic included, not just human adoption), so raw velocity favors widely-depended-on infrastructure; the taxonomy is a first-match heuristic over category membership and keywords, not an authoritative classification; per-crate license ids are author-supplied and informational only. Sample use: order by trend_rank for the month's fastest-rising data crates, or filter category = 'machine-learning'.

Les titres et les descriptions proviennent des sources de données, en anglais.