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⚠️ This article was written in 2020. Some content may be outdated.

React Component Performance Analysis in Practice

React component performance analysis is being used more and more widely in frontend development. Starting from real projects, this post digs into the core principles and best practices.

Getting Started ​

The key is understanding the core logic:

javascript
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 has to fit the context; not every case needs over-optimization.

Source Code Analysis ​

Here's how we can improve it:

javascript
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 half a year and is proven in practice.

Real-World Applications ​

Let's start with the basic approach:

javascript
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 snippet shows the basic usage. In real projects you'll also need to handle errors and edge cases.

Optimization Tips ​

Building on this, we can take it further:

javascript
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 useful in large projects and noticeably cuts maintenance cost.

Summary ​

  • React component performance analysis isn't a silver bullet — pick what fits your project's size and stack
  • Understanding the underlying principles matters more than memorizing APIs
  • Always validate compatibility before using it in production
  • In a team, conventions and docs matter more than the tech itself

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