从 IC 到 EM 再到 IC 的思考 is becoming increasingly widespread in frontend development. This article dives into its core principles and best practices from real projects.

Basic Usage

Building on this foundation, we can further optimize:

type UnwrapPromise<T> = T extends Promise<infer U> ? U : T

async function fetchUser(id: string) {
  const res = await fetch(`/api/users/${id}`)
  return res.json() as Promise<{ id: string; name: string; email: string }>
}

type User = UnwrapPromise<ReturnType<typeof fetchUser>>

// 类型安全的事件系统
interface EventMap {
  login: { userId: string; timestamp: number }
  logout: { userId: string }
}

class TypedEmitter<T extends Record<string, any>> {
  private handlers = new Map<keyof T, Set<Function>>()
  on<K extends keyof T>(event: K, handler: (payload: T[K]) => void) {
    if (!this.handlers.has(event)) this.handlers.set(event, new Set())
    this.handlers.get(event)!.add(handler)
  }
  emit<K extends keyof T>(event: K, payload: T[K]) {
    this.handlers.get(event)?.forEach(h => h(payload))
  }
}

This pattern is very practical in large projects and can significantly reduce maintenance costs.

Advanced Usage

Usage in real projects tends to be more complex:

const express = require('express')
const app = express()

app.use(express.json())

class AppError extends Error {
  constructor(status, message) {
    super(message); this.statusCode = status
  }
}

const asyncHandler = (fn) => (req, res, next) =>
  Promise.resolve(fn(req, res, next)).catch(next)

app.get('/api/users/:id', asyncHandler(async (req, res) => {
  const user = await User.findById(req.params.id)
  if (!user) throw new AppError(404, '用户不存在')
  res.json({ data: user })
}))

Through this approach, both the testability and scalability of the code are improved.

Practical Cases

Here is a complete example:

import { useReducer, useCallback } from 'react'

const initialState = { items: [], filter: '', sort: 'date' }

function reducer(state, action) {
  switch (action.type) {
    case 'SET_ITEMS': return { ...state, items: action.payload }
    case 'SET_FILTER': return { ...state, filter: action.payload }
    case 'ADD_ITEM': return { ...state, items: [...state.items, action.payload] }
    case 'REMOVE_ITEM': return { ...state, items: state.items.filter(i => i.id !== action.payload) }
    default: throw new Error(`Unknown: ${action.type}`)
  }
}

Pay attention to boundary condition handling, which is critical in production.

Performance Optimization

The key lies in understanding the core logic:

type UnwrapPromise<T> = T extends Promise<infer U> ? U : T

async function fetchUser(id: string) {
  const res = await fetch(`/api/users/${id}`)
  return res.json() as Promise<{ id: string; name: string; email: string }>
}

type User = UnwrapPromise<ReturnType<typeof fetchUser>>

// 类型安全的事件系统
interface EventMap {
  login: { userId: string; timestamp: number }
  logout: { userId: string }
}

class TypedEmitter<T extends Record<string, any>> {
  private handlers = new Map<keyof T, Set<Function>>()
  on<K extends keyof T>(event: K, handler: (payload: T[K]) => void) {
    if (!this.handlers.has(event)) this.handlers.set(event, new Set())
    this.handlers.get(event)!.add(handler)
  }
  emit<K extends keyof T>(event: K, payload: T[K]) {
    this.handlers.get(event)?.forEach(h => h(payload))
  }
}

Performance optimization should be tailored to specific scenarios; not all cases require over-optimization.

Common Pitfalls

We can improve it in the following ways:

const express = require('express')
const app = express()

app.use(express.json())

class AppError extends Error {
  constructor(status, message) {
    super(message); this.statusCode = status
  }
}

const asyncHandler = (fn) => (req, res, next) =>
  Promise.resolve(fn(req, res, next)).catch(next)

app.get('/api/users/:id', asyncHandler(async (req, res) => {
  const user = await User.findById(req.params.id)
  if (!user) throw new AppError(404, '用户不存在')
  res.json({ data: user })
}))

This approach has been running stably in production for over six months and has been practically validated.

Summary

• Understanding underlying principles is more important than memorizing APIs
• Always verify compatibility before using in production
• In team collaboration, conventions and documentation are more important than the technology itself
• Stay updated with the community; technical solutions need continuous iteration