users/lib/mock-users.ts

export type Status = "活跃" | "沉睡" | "已封禁"

export type UserBase = {
  id: string
  name: string
  phone: string
  email: string
  tags: string[]
  rfmScore: number
  lastActivity: string
  status: Status
}

export type UserDetail = UserBase & {
  avatar?: string
  company?: string
  position?: string
  recency: number
  frequency: number
  monetary: number
  interactions: { id: string; type: string; time: string; note?: string }[]
  purchaseHistory: { id: string; amount: number; time: string; item: string }[]
  wechatAccounts: { id: string; nickname: string; avatar?: string }[]
}

/* helpers */
const NOW = Date.now()
const rand = (min: number, max: number) => Math.floor(Math.random() * (max - min + 1)) + min
const maskPhone = (p: string) => p.replace(/^(\d{3})\d{4}(\d{4})$/, "$1****$2")
const pick = <T,>(arr: T[]) => arr[rand(0, arr.length - 1)]

const TAGS = [
  "高价值用户", "活跃用户", "潜在客户", "价格敏感", "科技爱好者",
  "内容创作者", "一线城市", "二线城市", "iPhone", "Android",
  "社群成员", "低活跃", "沉睡风险", "新用户", "忠诚用户",
]

const COMPANIES = ["合星科技", "云杉数智", "万像互动", "星远数科", "数研云", "青瓦科技"]
const POSITIONS = ["产品经理", "运营经理", "市场总监", "技术负责人", "销售", "数据分析师"]

const AVATARS = [
  "/user-avatar-zhangsan.png",
  "/user-avatar-lisi.png",
  "/wechat-avatar-1.png",
  "/wechat-avatar-2.png",
  "/wechat-avatar-3.png",
]

/* seed users */
const baseNames = [
  "王磊","刘婷","张三","李四","赵六","钱七","周敏","孙悦","吴迪","郑航",
  "冯晨","褚野","卫国","蒋楠","沈静","韩睿","唐奕","曹越","彭博","鲁洋",
  "韦东","昌华","顾诚","孟辉","尹雪","谭清","严杰","霍宇","龚一","程远",
]

const USERS: UserDetail[] = baseNames.slice(0, 24).map((name, idx) => {
  const n = idx + 1
  const rawPhone = `1${rand(3,9)}${rand(0,9)}${rand(0,9)}${rand(10000000, 99999999)}`
  const email = `${pinyinLike(name)}${n}@example.com`.toLowerCase()
  const tagCount = rand(2, 5)
  const tags = Array.from(new Set(Array.from({ length: tagCount }, () => pick(TAGS))))
  const status: Status = ["活跃","活跃","活跃","沉睡","已封禁"][rand(0,4)]
  const rfm = rand(45, 95)
  const lastActivity = new Date(NOW - rand(0, 7) * 86400_000 - rand(0, 12) * 3600_000).toISOString()

  const interactions = Array.from({ length: rand(1, 4) }).map((_, i) => ({
    id: `i_${n}_${i}`,
    type: pick(["咨询", "浏览", "下载白皮书", "提交表单", "聊天"]),
    time: new Date(NOW - rand(0, 14) * 86400_000 - rand(0, 20) * 3600_000).toISOString(),
    note: pick(["", "询价", "对比竞品", "需要发票", "待回访"]),
  }))

  const purchaseHistory = rand(0, 1)
    ? [{ id: `o_${n}_1`, amount: rand(299, 9999), time: new Date(NOW - rand(0, 30) * 86400_000).toISOString(), item: pick(["标准版SaaS","高级版SaaS","增值模块"]) }]
    : []

  const wechatAccounts = Array.from({ length: rand(1, 2) }).map((_, i) => ({
    id: `wx_${n}_${i}`,
    nickname: `${name}-微信${i+1}`,
    avatar: pick(AVATARS),
  }))

  return {
    id: `user_${1000 + n}`,
    name,
    phone: maskPhone(rawPhone),
    email,
    tags,
    rfmScore: rfm,
    lastActivity,
    status,
    avatar: pick(AVATARS),
    company: pick(COMPANIES),
    position: pick(POSITIONS),
    recency: rand(1, 10),
    frequency: rand(1, 30),
    monetary: rand(0, 20000),
    interactions,
    purchaseHistory,
    wechatAccounts,
  }
})

function pinyinLike(name: string) {
  // super simple fake pinyin-ish
  const map: Record<string, string> = {
    "王":"wang","张":"zhang","李":"li","刘":"liu","赵":"zhao","钱":"qian","孙":"sun","周":"zhou",
    "吴":"wu","郑":"zheng","冯":"feng","褚":"chu","卫":"wei","蒋":"jiang","沈":"shen","韩":"han",
    "唐":"tang","曹":"cao","彭":"peng","鲁":"lu","韦":"wei","昌":"chang","顾":"gu","孟":"meng",
    "尹":"yin","谭":"tan","严":"yan","霍":"huo","龚":"gong","程":"cheng",
  }
  const first = map[name[0]] || "user"
  const rest = "abcxyz"
  return `${first}${rest[Math.floor(Math.random()*rest.length)]}${rest[Math.floor(Math.random()*rest.length)]}`
}

/* public APIs */
export type FilterOptions = {
  q?: string
  tags?: string[]
  status?: Status[]
  rfmMin?: number
  rfmMax?: number
  page?: number
  pageSize?: number
}

export function getUsers(): UserBase[] {
  return USERS.map(({ interactions, purchaseHistory, wechatAccounts, recency, frequency, monetary, company, position, avatar, ...u }) => u)
}

export function getUserDetail(id: string): UserDetail | null {
  return USERS.find((u) => u.id === id) ?? null
}

export function getDistinctTags(): string[] {
  const s = new Set<string>()
  USERS.forEach((u) => u.tags.forEach((t) => s.add(t)))
  return Array.from(s)
}

export function filterUsers(opts: FilterOptions) {
  const {
    q = "",
    tags = [],
    status = [],
    rfmMin = 0,
    rfmMax = 100,
    page = 1,
    pageSize = 20,
  } = opts

  let list = getUsers()

  if (q) {
    const ql = q.toLowerCase()
    list = list.filter(
      (u) =>
        u.name.toLowerCase().includes(ql) ||
        u.phone.includes(q) ||
        u.email.toLowerCase().includes(ql) ||
        u.tags.some((t) => t.toLowerCase().includes(ql)),
    )
  }

  if (tags.length) {
    list = list.filter((u) => tags.some((t) => u.tags.includes(t)))
  }

  if (status.length) {
    list = list.filter((u) => status.includes(u.status))
  }

  list = list.filter((u) => u.rfmScore >= rfmMin && u.rfmScore <= rfmMax)

  const total = list.length
  const start = (page - 1) * pageSize
  const end = start + pageSize
  const items = list.slice(start, end)
  return { items, total, page, pageSize }
}

export function addUser(payload: { name: string; phone: string; email: string; tags?: string[] }): UserDetail {
  const n = USERS.length + 1000
  const u: UserDetail = {
    id: `user_${n}`,
    name: payload.name,
    phone: maskPhone(payload.phone),
    email: payload.email,
    tags: payload.tags ?? [],
    rfmScore: 60 + (n % 40),
    lastActivity: new Date().toISOString(),
    status: "活跃",
    avatar: pick(AVATARS),
    company: pick(COMPANIES),
    position: pick(POSITIONS),
    recency: rand(1, 5),
    frequency: rand(1, 10),
    monetary: rand(0, 5000),
    interactions: [],
    purchaseHistory: [],
    wechatAccounts: [],
  }
  USERS.unshift(u)
  return u
}