关于前端 Monorepo 实践，: many developers only stay at the API call level. This article discusses real-world problems and solutions from a production perspective.

Basic Principles

Building on this foundation, we can further optimize:

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}`)
  }
}

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

Advanced Features

实际项目中的用法会更复杂一些：

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))
  }
}

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

Project Practice

Here is a complete example:

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 })
}))

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

Best Practices

The key lies in understanding the core logic:

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}`)
  }
}

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

Common Pitfalls

We can improve it in the following ways:

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

Summary

• 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
• Don't adopt new technology just for the sake of it