关于TanStack Query v4 重大更新,很多开发者只停留在 API 调用层面。本文试图从生产环境的角度,讨论实际中会遇到的问题和解决方案。
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
Usage in real projects tends to be more complex:
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 the testability and scalability of the code are improved.
Project Practice
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.
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:
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 has been running stably in production for over six months and has been practically validated.
Summary
- TanStack Query v4 重大更新 is not a silver bullet; choose based on your project scale and tech stack
- 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