michilis
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import {
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bayesianScore,
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compareMints,
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NEUTRAL_PRIOR_MEAN,
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parseNuts,
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type Health,
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type MintDetail,
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type MintInfo,
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type MintListItem,
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type MintStatus,
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type ProbeSample,
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type RatingDistribution,
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type Stats,
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} from '@cashumints/shared';
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import { config, startedAt } from './config.ts';
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import { getDb, getStateNumber, getState } from './db.ts';
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import { mintByHost, type MintRow } from './mints.ts';
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/**
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* One review per author per mint, newest wins.
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*
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* Kind 38000 is in the addressable range, so a later event from the same author
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* replaces the earlier one. The old site applied the same rule in memory
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* (aggregateReviews, keyed by pubkey); doing it in SQL keeps counts honest and stops
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* one npub from moving a mint's average by re-posting.
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*/
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const LATEST_REVIEWS = `
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SELECT mint_url, pubkey, rating, created_at FROM (
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SELECT mint_url, pubkey, rating, created_at,
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ROW_NUMBER() OVER (
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PARTITION BY mint_url, pubkey ORDER BY created_at DESC, event_id
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) AS rn
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FROM reviews
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) WHERE rn = 1
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`;
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interface AggRow {
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mint_url: string;
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review_count: number;
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rating_avg: number | null;
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last_review_at: number | null;
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}
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function aggregates(): Map<string, AggRow> {
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const rows = getDb()
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.prepare(
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`WITH latest AS (${LATEST_REVIEWS})
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SELECT mint_url,
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COUNT(*) AS review_count,
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AVG(rating) AS rating_avg,
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MAX(created_at) AS last_review_at
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FROM latest GROUP BY mint_url`,
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)
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.all() as AggRow[];
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return new Map(rows.map((r) => [r.mint_url, r]));
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}
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/**
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* C in the Bayesian formula.
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*
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* Defaults to a neutral 3, not the observed global mean: see the long comment in
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* shared/src/score.ts for why the observed mean (about 4.7 here) makes the formula
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* fail its own stated purpose. `SCORE_PRIOR_MEAN=global` restores literal BACKEND.md
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* behaviour, or set any number to pin it.
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*/
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function priorMean(): number {
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const override = process.env['SCORE_PRIOR_MEAN'];
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if (override && override !== 'global') {
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const n = Number.parseFloat(override);
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if (Number.isFinite(n) && n >= 1 && n <= 5) return n;
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}
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if (override === 'global') {
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const row = getDb()
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.prepare(`WITH latest AS (${LATEST_REVIEWS}) SELECT AVG(rating) AS avg FROM latest`)
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.get() as { avg: number | null };
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return row.avg ?? NEUTRAL_PRIOR_MEAN;
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}
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return NEUTRAL_PRIOR_MEAN;
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}
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function iconPath(row: MintRow): string | null {
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return row.icon_file ? `/icons/${row.icon_file}` : null;
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}
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function round1(n: number | null): number | null {
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return n === null ? null : Math.round(n * 10) / 10;
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}
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function toListItem(row: MintRow, agg: AggRow | undefined, mean: number, now: number): MintListItem {
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const base = {
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review_count: agg?.review_count ?? 0,
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rating_avg: agg?.rating_avg ?? null,
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status: row.status,
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last_review_at: agg?.last_review_at ?? null,
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};
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return {
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url: row.url,
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host: row.host,
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name: row.name,
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icon: iconPath(row),
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status: row.status as MintStatus,
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last_online: row.last_online,
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review_count: base.review_count,
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rating_avg: round1(base.rating_avg),
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score: bayesianScore(base, mean, now),
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last_review_at: base.last_review_at,
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version: row.version,
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};
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}
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export function listMints(limit?: number): MintListItem[] {
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const now = Math.floor(Date.now() / 1000);
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const agg = aggregates();
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const mean = priorMean();
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const items = (getDb().prepare('SELECT * FROM mints').all() as MintRow[])
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.map((row) => toListItem(row, agg.get(row.url), mean, now))
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.sort(compareMints);
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return limit && limit > 0 ? items.slice(0, limit) : items;
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}
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function distribution(mintUrl: string): RatingDistribution {
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const rows = getDb()
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.prepare(
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`WITH latest AS (${LATEST_REVIEWS})
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SELECT rating, COUNT(*) AS n FROM latest
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WHERE mint_url = ? AND rating IS NOT NULL GROUP BY rating`,
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)
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.all(mintUrl) as { rating: number; n: number }[];
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const dist: RatingDistribution = { '1': 0, '2': 0, '3': 0, '4': 0, '5': 0 };
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for (const r of rows) {
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const key = String(r.rating) as keyof RatingDistribution;
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if (key in dist) dist[key] = r.n;
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}
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return dist;
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}
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function reviews90d(mintUrl: string): number {
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const cutoff = Math.floor(Date.now() / 1000) - 90 * 24 * 60 * 60;
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const row = getDb()
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.prepare(
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`WITH latest AS (${LATEST_REVIEWS})
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SELECT COUNT(*) AS n FROM latest WHERE mint_url = ? AND created_at >= ?`,
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)
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.get(mintUrl, cutoff) as { n: number };
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return row.n;
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}
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function uptime30d(mintUrl: string): number | null {
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const cutoff = Math.floor(Date.now() / 1000) - 30 * 24 * 60 * 60;
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const row = getDb()
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.prepare('SELECT AVG(ok) AS up, COUNT(*) AS n FROM probes WHERE mint_url = ? AND ts >= ?')
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.get(mintUrl, cutoff) as { up: number | null; n: number };
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if (!row.n || row.up === null) return null;
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return Math.round(row.up * 1000) / 1000;
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}
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function recentProbes(mintUrl: string): ProbeSample[] {
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const cutoff = Math.floor(Date.now() / 1000) - 48 * 60 * 60;
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return getDb()
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.prepare(
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'SELECT ts, ok, latency_ms FROM probes WHERE mint_url = ? AND ts >= ? ORDER BY ts ASC',
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)
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.all(mintUrl, cutoff) as ProbeSample[];
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}
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function parseInfo(json: string | null): MintInfo | null {
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if (!json) return null;
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try {
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return JSON.parse(json) as MintInfo;
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} catch {
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return null;
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}
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}
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export function getMintDetail(host: string): MintDetail | null {
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const row = mintByHost(host);
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if (!row) return null;
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const now = Math.floor(Date.now() / 1000);
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const agg = aggregates().get(row.url);
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const item = toListItem(row, agg, priorMean(), now);
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const info = parseInfo(row.info_json);
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let nuts: string[] = [];
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if (row.nuts_json) {
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try {
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nuts = JSON.parse(row.nuts_json) as string[];
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} catch {
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nuts = [];
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}
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}
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if (nuts.length === 0 && info) nuts = parseNuts(info.nuts);
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return {
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...item,
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description: row.description,
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pubkey: row.pubkey,
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info,
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nuts,
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first_seen: row.first_seen,
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last_probe: row.last_probe,
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updated_at: row.updated_at,
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rating_distribution: distribution(row.url),
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reviews_90d: reviews90d(row.url),
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uptime_30d: uptime30d(row.url),
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probes_recent: recentProbes(row.url),
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};
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}
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let statsCache: { at: number; value: Stats } | null = null;
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const STATS_TTL_S = 60;
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export function getStats(): Stats {
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const now = Math.floor(Date.now() / 1000);
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if (statsCache && now - statsCache.at < STATS_TTL_S) return statsCache.value;
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const db = getDb();
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const counts = db
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.prepare(
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`SELECT
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COUNT(*) AS total,
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SUM(status = 'online') AS online,
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SUM(status = 'offline') AS offline,
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SUM(status = 'degraded') AS degraded
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FROM mints`,
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)
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.get() as { total: number; online: number | null; offline: number | null; degraded: number | null };
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const reviews = db
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.prepare(`WITH latest AS (${LATEST_REVIEWS}) SELECT COUNT(*) AS n, MAX(created_at) AS last FROM latest`)
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.get() as { n: number; last: number | null };
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const value: Stats = {
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mints_total: counts.total,
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mints_online: counts.online ?? 0,
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mints_offline: counts.offline ?? 0,
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mints_degraded: counts.degraded ?? 0,
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reviews_total: reviews.n,
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last_review_at: reviews.last,
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updated_at: now,
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};
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statsCache = { at: now, value };
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return value;
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}
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/** Health bypasses the stats cache: it is the endpoint you page on. */
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export function getHealth(): Health {
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const now = Math.floor(Date.now() / 1000);
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const lastProbe = getStateNumber('last_probe_at');
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const lastDiscovery = getStateNumber('last_discovery_at');
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const discoveryOk = getState('last_discovery_ok') !== '0';
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const tracked = (getDb().prepare('SELECT COUNT(*) AS n FROM mints').get() as { n: number }).n;
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const staleAfter = config.probeIntervalMin * 60 * 3;
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const probeStale = lastProbe === null || now - lastProbe > staleAfter;
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return {
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status: probeStale || !discoveryOk ? 'degraded' : 'ok',
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uptime_s: now - startedAt,
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last_probe_at: lastProbe,
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last_discovery_at: lastDiscovery,
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mints_tracked: tracked,
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updated_at: now,
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};
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}
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Reference in New Issue
Block a user