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data-transformers

data-transformers

github.com/dadbodgeoff数据与数据库79240 次安装10 周前更新
代码仓库

关于 data-transformers

用于集中管理 API 路由和仪表盘数据整形逻辑的技能,涵盖聚合、排名、趋势计算和清理,便于复用与测试。

主要功能

  1. 01分类与数量聚合
  2. 02Top-N 排名
  3. 03跨周期趋势计算
  4. 04数据清理
  5. 05可复用的纯函数

适用场景

  1. 01统一 API 响应格式
  2. 02生成仪表盘聚合数据
  3. 03在多个路由间复用转换逻辑
  4. 04单独测试数据整形逻辑

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/dadbodgeoff/drift --skill data-transformers

安装后在 Claude Code 中输入/data-transformers确认已加载。

详细介绍

数据转换器

集中管理转换逻辑,确保 API 路由中的数据整形保持一致。

何时使用此技能

  • 数据转换逻辑分散在各个路由中
  • 需要在各个端点间保持输出格式一致
  • 希望转换函数可测试且可复用
  • 构建包含聚合数据的仪表板

核心概念

将所有转换逻辑集中在一处:

  • 聚合器(类别总计、计数)
  • 排名器(按分数选出前 N 项)
  • 趋势计算器(比较不同时间段)
  • 清理器(验证并清理数据)
┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│  Raw Data   │────▶│ Transformers │────▶│  API Output │
└─────────────┘     └──────────────┘     └─────────────┘

实现

TypeScript
// lib/transformers.ts

// ============================================
// Category Aggregation
// ============================================

interface CategoryTotals {
  [category: string]: number;
}

function aggregateCategories(
  items: Array<{ category: string; count?: number }>
): CategoryTotals {
  const totals: CategoryTotals = {};

  for (const item of items) {
    const category = item.category?.toUpperCase() || 'OTHER';
    totals[category] = (totals[category] || 0) + (item.count ?? 1);
  }

  return totals;
}

function categoriesToBreakdown(
  totals: CategoryTotals,
  previousTotals?: CategoryTotals
): Array<{ category: string; count: number; percentage: number; trend: string }> {
  const total = Object.values(totals).reduce((sum, count) => sum + count, 0);
  
  return Object.entries(totals)
    .map(([category, count]) => {
      let trend: 'increasing' | 'stable' | 'decreasing' = 'stable';
      
      if (previousTotals) {
        const prevCount = previousTotals[category] ?? 0;
        const change = count - prevCount;
        if (change > prevCount * 0.1) trend = 'increasing';
        else if (change < -prevCount * 0.1) trend = 'decreasing';
      }

      return {
        category,
        count,
        percentage: total > 0 ? count / total : 0,
        trend,
      };
    })
    .sort((a, b) => b.count - a.count);
}

// ============================================
// Ranking
// ============================================

interface Rankable {
  score: number;
  count: number;
}

function rankItems<T extends Rankable>(
  items: T[], 
  limit = 5
): (T & { rank: number })[] {
  return items
    .sort((a, b) => {
      if (b.score !== a.score) return b.score - a.score;
      return b.count - a.count;
    })
    .slice(0, limit)
    .map((item, index) => ({ ...item, rank: index + 1 }));
}

// ============================================
// Trend Calculation
// ============================================

type SimpleTrend = 'increasing' | 'stable' | 'decreasing';

function calculateTrend(current: number, previous: number): SimpleTrend {
  if (previous === 0) return 'stable';
  const change = (current - previous) / previous;
  
  if (change > 0.1) return 'increasing';
  if (change < -0.1) return 'decreasing';
  return 'stable';
}

function calculateRollingAverage(values: number[], window = 7): number {
  if (values.length === 0) return 0;
  const slice = values.slice(-window);
  return slice.reduce((sum, v) => sum + v, 0) / slice.length;
}

function calculatePercentChange(current: number, previous: number): number {
  if (previous === 0) return current > 0 ? 100 : 0;
  return ((current - previous) / previous) * 100;
}

// ============================================
// Data Sanitization
// ============================================

interface Hotspot {
  country: string;
  countryCode: string;
  lat: number;
  lon: number;
  riskScore: number;
  eventCount: number;
}

function sanitizeHotspot(raw: Partial<Hotspot>): Hotspot | null {
  if (!raw.country || !raw.countryCode) return null;
  
  return {
    country: raw.country,
    countryCode: raw.countryCode,
    lat: raw.lat ?? 0,
    lon: raw.lon ?? 0,
    riskScore: Math.min(100, Math.max(0, raw.riskScore ?? 0)),
    eventCount: Math.max(0, raw.eventCount ?? 0),
  };
}

function filterValidHotspots(hotspots: Partial<Hotspot>[]): Hotspot[] {
  return hotspots
    .map(sanitizeHotspot)
    .filter((h): h is Hotspot => h !== null);
}

// ============================================
// String Utilities
// ============================================

function truncate(str: string, maxLen: number): string {
  if (!str) return '';
  return str.length > maxLen ? str.slice(0, maxLen - 3) + '...' : str;
}

function slugify(str: string): string {
  return str
    .toLowerCase()
    .replace(/[^\w\s-]/g, '')
    .replace(/\s+/g, '-')
    .replace(/-+/g, '-')
    .trim();
}

// ============================================
// Date Utilities
// ============================================

function formatRelativeTime(date: Date): string {
  const now = new Date();
  const diffMs = now.getTime() - date.getTime();
  const diffMins = Math.floor(diffMs / 60000);
  const diffHours = Math.floor(diffMs / 3600000);
  const diffDays = Math.floor(diffMs / 86400000);

  if (diffMins < 1) return 'just now';
  if (diffMins < 60) return `${diffMins}m ago`;
  if (diffHours < 24) return `${diffHours}h ago`;
  if (diffDays < 7) return `${diffDays}d ago`;
  return date.toLocaleDateString();
}

export {
  aggregateCategories,
  categoriesToBreakdown,
  rankItems,
  calculateTrend,
  calculateRollingAverage,
  calculatePercentChange,
  sanitizeHotspot,
  filterValidHotspots,
  truncate,
  slugify,
  formatRelativeTime,
};

使用示例

API 路由
// api/dashboard/route.ts
import { 
  aggregateCategories, 
  rankItems, 
  filterValidHotspots 
} from '@/lib/transformers';

export async function GET() {
  const rawData = await fetchFromDatabase();
  
  return Response.json({
    categories: aggregateCategories(rawData.predictions),
    topHotspots: rankItems(filterValidHotspots(rawData.hotspots), 5),
    trend: calculateTrend(rawData.todayCount, rawData.yesterdayCount),
  });
}
仪表板组件
const breakdown = categoriesToBreakdown(
  currentTotals,
  previousTotals
);

// Returns:
// [
//   { category: 'MILITARY', count: 150, percentage: 0.45, trend: 'increasing' },
//   { category: 'POLITICAL', count: 100, percentage: 0.30, trend: 'stable' },
//   ...
// ]

最佳实践

  1. 将所有转换器放在一个文件中,便于查找和测试
  2. 使用纯函数,不产生副作用,输出可预测
  3. 处理边缘情况,包括空数组、缺失字段和 null 值
  4. 确保类型安全,适当使用 TypeScript 泛型
  5. 从 types 包导出,以便在前端和后端共享

常见错误

  • 将转换逻辑分散在各个路由中
  • 未处理边缘情况(空数组、null 值)
  • 修改输入数据,而不是返回新对象
  • 对可空返回值缺少类型守卫
  • 未对转换器进行独立测试

相关模式

  • api-client - 在 API 响应中使用转换器
  • validation-quarantine - 转换前进行验证
  • snapshot-aggregation - 为仪表板聚合数据

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