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⚠️ This article was written in 2022. Some content may be outdated.

Getting Started with Web3 Frontend DApp Development

In daily development, Web3 frontend DApp development is becoming increasingly common. This article systematically covers its usage, principles, and optimization strategies.

Quick Start ​

Building on this foundation, we can further optimize:

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

Internal Principles ​

Real-world usage in projects is more complex:

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}`)
  }
}

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

Real-World Practice ​

Here is a complete example:

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>>

// Type-safe event system
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))
  }
}

Pay attention to edge case handling, which is critical in production environments.

Performance Comparison ​

The key is understanding the core logic:

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 })
}))

Performance optimization should be tailored to specific scenarios—not all situations require over-optimization.

Troubleshooting ​

We can improve through the following 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 approach is reliable and well-validated in production environments.

Summary ​

  • Always perform compatibility verification before using in production
  • In team collaboration, conventions and documentation are more important than the technology itself
  • Follow community trends—technical solutions require continuous iteration
  • Don't use new technology just for the sake of using new technology

MIT Licensed