176 lines
6.5 KiB
JavaScript
176 lines
6.5 KiB
JavaScript
const cloud = require('wx-server-sdk')
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cloud.init({ env: cloud.DYNAMIC_CURRENT_ENV })
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const db = cloud.database()
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const _ = db.command
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// Only people within this radius are "nearby". Online = location reported recently.
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const RADIUS_METERS = 5000
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const ONLINE_WINDOW_MS = 5 * 60 * 1000
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// How many visible locations to scan in memory. No geo index is required this way
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// (geoNear would need a manually-created index in the cloud console); fine for an
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// early-stage user base. Switch to geoNear on `locations.geo` if this grows large.
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const MAX_SCAN = 500
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const MAX_RESULTS = 50
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// In WeChat 云开发, querying a collection that was never created throws
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// ("collection not exists"). Treat that as an empty result so an unused
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// collection (e.g. follows/matches before anyone follows/likes) can't break
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// the whole nearby query.
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function isMissingCollection(e) {
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if (!e) return false
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const msg = String(e.errMsg || e.message || '')
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return e.errCode === -502005 || /not exist/i.test(msg) || /CollectionNotExists/i.test(msg)
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}
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async function safeGet(query) {
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try {
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return await query.get()
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} catch (e) {
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if (isMissingCollection(e)) return { data: [] }
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throw e
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}
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}
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async function fetchByChunks(collection, field, values) {
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const out = []
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for (let i = 0; i < values.length; i += 100) {
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const chunk = values.slice(i, i + 100)
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const res = await safeGet(db.collection(collection).where({ [field]: _.in(chunk) }).limit(100))
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out.push(...res.data)
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}
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return out
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}
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// Great-circle distance in metres between two {latitude, longitude} points.
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function distanceMeters(a, b) {
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if (!a || !b || typeof a.latitude !== 'number' || typeof b.latitude !== 'number') return Infinity
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const R = 6371000
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const dLat = ((b.latitude - a.latitude) * Math.PI) / 180
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const dLon = ((b.longitude - a.longitude) * Math.PI) / 180
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const s =
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Math.sin(dLat / 2) ** 2 +
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Math.cos((a.latitude * Math.PI) / 180) *
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Math.cos((b.latitude * Math.PI) / 180) *
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Math.sin(dLon / 2) ** 2
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return R * 2 * Math.atan2(Math.sqrt(s), Math.sqrt(1 - s))
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}
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function distanceText(meters) {
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if (!isFinite(meters)) return null
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const m = Math.round(meters)
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if (m < 1000) return `${m}m`
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return `${(m / 1000).toFixed(1)}km`
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}
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exports.main = async event => {
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const { OPENID } = cloud.getWXContext()
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const filter = event.filters?.type || 'all'
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const userLoc = event.location || null
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// No usable origin → nothing to anchor "nearby" to.
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if (!userLoc || typeof userLoc.latitude !== 'number' || typeof userLoc.longitude !== 'number') {
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return { list: [] }
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}
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// Identify the caller and their follow graph (for friend/following badges).
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let meId = ''
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let followingSet = new Set()
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let followerSet = new Set()
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if (OPENID) {
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const meRes = await safeGet(db.collection('users').where({ openid: OPENID }).limit(1))
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const me = meRes.data[0]
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if (me) {
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meId = me._id
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const [followingRes, followerRes] = await Promise.all([
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safeGet(db.collection('follows').where({ followerId: meId }).limit(500)),
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safeGet(db.collection('follows').where({ followeeId: meId }).limit(500))
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])
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followingSet = new Set(followingRes.data.map(f => f.followeeId))
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followerSet = new Set(followerRes.data.map(f => f.followerId))
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}
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}
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// 1) Scan visible locations (paginated) and keep those inside the radius.
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const near = []
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let scanned = 0
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for (let skip = 0; skip < MAX_SCAN; skip += 100) {
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const res = await safeGet(db.collection('locations').where({ visible: true }).skip(skip).limit(100))
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scanned += res.data.length
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if (!res.data.length) break
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for (const rec of res.data) {
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if (!rec.openid || !rec.location) continue
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const dist = distanceMeters(userLoc, rec.location)
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if (dist <= RADIUS_METERS) near.push({ rec, dist })
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}
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if (res.data.length < 100) break
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}
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near.sort((a, b) => a.dist - b.dist)
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const top = near.slice(0, MAX_RESULTS)
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console.log('[nearbyPets] origin=', userLoc, 'visibleScanned=', scanned, 'inRadius=', near.length, 'nearestKm=', near[0] ? (near[0].dist / 1000).toFixed(2) : 'n/a')
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if (!top.length) return { list: [] }
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const distByOpenid = new Map()
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const recByOpenid = new Map()
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const openids = []
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top.forEach(({ rec, dist }) => {
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if (recByOpenid.has(rec.openid)) return
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distByOpenid.set(rec.openid, dist)
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recByOpenid.set(rec.openid, rec)
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openids.push(rec.openid)
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})
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// 2) Resolve those openids to user records.
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const users = await fetchByChunks('users', 'openid', openids)
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const userByOpenid = new Map(users.map(u => [u.openid, u]))
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const openidByUserId = new Map(users.map(u => [u._id, u.openid]))
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const ownerIds = users.map(u => u._id)
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if (!ownerIds.length) return { list: [] }
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// 3) Their pets (optionally narrowed by species).
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let pets = await fetchByChunks('pets', 'ownerId', ownerIds)
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if (filter === 'dog' || filter === 'cat') pets = pets.filter(p => p.species === filter)
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// 4) Which of these pets the caller already liked.
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const likedSet = new Set()
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const petIds = pets.map(p => p._id).filter(Boolean)
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if (OPENID && petIds.length) {
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const liked = await fetchByChunks('matches', 'petId', petIds).then(rows =>
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rows.filter(m => m.fromOpenid === OPENID)
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)
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liked.forEach(m => likedSet.add(m.petId))
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}
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const now = Date.now()
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const list = pets
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.map(pet => {
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const ownerOpenid = openidByUserId.get(pet.ownerId)
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const rec = ownerOpenid ? recByOpenid.get(ownerOpenid) : null
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const coord = rec && rec.location ? rec.location : null
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const dist = ownerOpenid != null && distByOpenid.has(ownerOpenid) ? distByOpenid.get(ownerOpenid) : Infinity
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const owner = userByOpenid.get(ownerOpenid)
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const isFollowing = followingSet.has(pet.ownerId)
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const isFollowedBy = followerSet.has(pet.ownerId)
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return {
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...pet,
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ownerName: owner?.nickname || '',
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isMine: Boolean(meId && pet.ownerId === meId),
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isFollowing,
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isFriend: isFollowing && isFollowedBy,
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likedByMe: likedSet.has(pet._id),
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latitude: coord ? coord.latitude : undefined,
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longitude: coord ? coord.longitude : undefined,
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distanceText: distanceText(dist),
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online: rec ? now - (rec.updatedAt || 0) < ONLINE_WINDOW_MS : false,
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_dist: dist
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}
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})
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.sort((a, b) => a._dist - b._dist)
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list.forEach(p => delete p._dist)
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const finalList = filter === 'online' ? list.filter(p => p.online) : list
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console.log('[nearbyPets] nearbyUsers=', openids.length, 'matchedUsers=', users.length, 'pets=', pets.length, 'returned=', finalList.length)
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return { list: finalList }
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}
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