Rspack 2.0 Complete Guide is becoming increasingly widespread in frontend development. This article dives deep into its core principles and best practices from real projects.

Getting Started

Here is a complete example:

import { useState, useEffect, useCallback } from 'react'

function DataList({ endpoint, pageSize = 20 }) {
  const [data, setData] = useState([])
  const [page, setPage] = useState(1)
  const [loading, setLoading] = useState(false)

  const fetchData = useCallback(async () => {
    setLoading(true)
    try {
      const res = await fetch(`${endpoint}?page=${page}&size=${pageSize}`)
      setData(await res.json())
    } finally { setLoading(false) }
  }, [endpoint, page, pageSize])

  useEffect(() => { fetchData() }, [fetchData])

  return <div>{loading ? <Spinner /> : <List items={data} />}</div>
}

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

Source Code Analysis

The key lies in understanding the core logic:

type DeepPartial<T> = T extends object ? { [P in keyof T]?: DeepPartial<T[P]> } : T

interface AppConfig {
  api: { baseUrl: string; timeout: number; retries: number }
  ui: { theme: 'light' | 'dark'; language: string; pageSize: number }
}

type PartialConfig = DeepPartial<AppConfig>

function mergeConfig(defaults: AppConfig, overrides: PartialConfig): AppConfig {
  const result = { ...defaults }
  for (const key of Object.keys(overrides) as (keyof AppConfig)[]) {
    if (overrides[key] && typeof overrides[key] === 'object') {
      result[key] = { ...defaults[key], ...overrides[key] } as any
    }
  }
  return result
}

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

Real-World Applications

We can improve it in the following ways:

:root {
  --bg: light-dark(#fff, #1a1a2e);
  --text: light-dark(#333, #e0e0e0);
  --accent: light-dark(#2563eb, #60a5fa);
  color-scheme: light dark;
}

.carousel {
  display: flex; gap: 1rem; overflow-x: auto;
  scroll-snap-type: x mandatory;
  scroll-padding: 1rem;
}

.carousel__item {
  flex: 0 0 80%; scroll-snap-align: start;
  border-radius: 12px; transition: scale 0.3s ease;
}

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

Optimization Tips

Let's start with the basic implementation:

import { useState, useEffect, useCallback } from 'react'

function DataList({ endpoint, pageSize = 20 }) {
  const [data, setData] = useState([])
  const [page, setPage] = useState(1)
  const [loading, setLoading] = useState(false)

  const fetchData = useCallback(async () => {
    setLoading(true)
    try {
      const res = await fetch(`${endpoint}?page=${page}&size=${pageSize}`)
      setData(await res.json())
    } finally { setLoading(false) }
  }, [endpoint, page, pageSize])

  useEffect(() => { fetchData() }, [fetchData])

  return <div>{loading ? <Spinner /> : <List items={data} />}</div>
}

This code demonstrates the basic usage. In real projects, you also need to consider error handling and edge cases.

Pitfall Guide

Building on this foundation, we can further optimize:

type DeepPartial<T> = T extends object ? { [P in keyof T]?: DeepPartial<T[P]> } : T

interface AppConfig {
  api: { baseUrl: string; timeout: number; retries: number }
  ui: { theme: 'light' | 'dark'; language: string; pageSize: number }
}

type PartialConfig = DeepPartial<AppConfig>

function mergeConfig(defaults: AppConfig, overrides: PartialConfig): AppConfig {
  const result = { ...defaults }
  for (const key of Object.keys(overrides) as (keyof AppConfig)[]) {
    if (overrides[key] && typeof overrides[key] === 'object') {
      result[key] = { ...defaults[key], ...overrides[key] } as any
    }
  }
  return result
}

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

Summary

• Don't adopt new technology just for the sake of it
• Code examples are for reference only and need to be adjusted according to your business scenario
• Rspack 2.0 Complete Guide is not a silver bullet; choose based on your project scale and tech stack