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tRPC End-to-End Type Safe APIs · Pelajaran

Mengimplementasikan Pembaruan Optimistis

Pelajari cara memberikan pengalaman pengguna yang instan dengan mengimplementasikan pembaruan optimistis menggunakan tRPC dan cache sisi klien.

Mengimplementasikan Pembaruan Optimistis adalah pelajaran tRPC End-to-End Type Safe APIs gratis di CoddyKit. Ini adalah pelajaran 2 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar tRPC End-to-End Type Safe APIs, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus tRPC End-to-End Type Safe APIs mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

Instant Feedback with Optimistic Updates

Imagine clicking 'Like' on a post. You expect it to show 'Liked' instantly, right? That's the magic of Optimistic Updates!

Optimistic updates make your app feel incredibly fast and responsive. They improve the user experience by giving immediate feedback.

What Are Optimistic Updates?

An optimistic update means updating the user interface (UI) before the server has confirmed the change. You 'optimistically' assume the server request will succeed.

  • Instant UI update: The user sees their action immediately reflected.
  • Background server call: The actual data change is sent to the backend.
  • Rollback on error: If the server fails, the UI reverts to its previous state.

Why Use Them with tRPC?

tRPC, combined with a client-side caching library like React Query (or TanStack Query), provides powerful tools for managing server state and implementing optimistic updates.

React Query's useMutation hook is central to this. It allows you to define callbacks for when a mutation starts, succeeds, or fails, enabling precise control over the UI.

The `onMutate` Callback

When you trigger a mutation, React Query calls the onMutate function before sending the request to the server. This is where you perform the optimistic UI update.

Inside onMutate, you typically:

  • Cancel any ongoing fetches for the data you're about to change.
  • Snapshot the current data so you can roll back if needed.
  • Update the cache with the new, optimistic data.

Setting Up `onMutate`

Let's look at a simplified example for 'liking' a post. We'll use queryClient.setQueryData to update the cache optimistically.

import { trpc } from '../utils/trpc';
import { useQueryClient } from '@tanstack/react-query';

function PostLikeButton({ postId }: { postId: string }) {
  const queryClient = useQueryClient();
  const likeMutation = trpc.post.like.useMutation({
    onMutate: async (newLike) => {
      // 1. Cancel any outgoing refetches
      await queryClient.cancelQueries(['post', postId]);

      // 2. Snapshot the previous value
      const previousPost = queryClient.getQueryData(['post', postId]);

      // 3. Optimistically update to the new value
      queryClient.setQueryData(['post', postId], (old: any) => {
        if (old) {
          return { ...old, likes: old.likes + 1, isLiked: true };
        }
        return old;
      });

      return { previousPost }; // Context for onError
    },
  });

  return (
    <button onClick={() => likeMutation.mutate({ postId })}>Like</button>
  );
}

The `onError` Callback

If the server mutation fails, you need to revert the UI to its previous state. This is handled in the onError callback.

Here, you use the context object returned from onMutate (which holds your snapshot of previousPost) to restore the cache to its original value.

Implementing `onError` (Rollback)

Adding the onError handler to our useMutation setup:

import { trpc } from '../utils/trpc';
import { useQueryClient } from '@tanstack/react-query';

function PostLikeButton({ postId }: { postId: string }) {
  const queryClient = useQueryClient();
  const likeMutation = trpc.post.like.useMutation({
    onMutate: async (newLike) => {
      // ... (same as before)
      const previousPost = queryClient.getQueryData(['post', postId]);
      queryClient.setQueryData(['post', postId], (old: any) => {
        if (old) return { ...old, likes: old.likes + 1, isLiked: true };
        return old;
      });
      return { previousPost };
    },
    onError: (err, newLike, context) => {
      // Rollback the cache to the previousPost
      queryClient.setQueryData(['post', postId], context?.previousPost);
      // Optionally show an error toast
      console.error("Failed to like post: ", err.message);
    },
  });

  return (
    <button onClick={() => likeMutation.mutate({ postId })}>Like</button>
  );
}

The `onSuccess` Callback

Once the server successfully processes the mutation, the onSuccess callback is triggered. At this point, your optimistic UI update is correct, but you still want to ensure data consistency.

The best practice here is to invalidate relevant queries. This tells React Query to refetch the data in the background, ensuring your client-side cache is perfectly in sync with the server.

Completing the Optimistic Flow

Here's the full useMutation with onSuccess to invalidate and refetch data after a successful server response:

import { trpc } from '../utils/trpc';
import { useQueryClient } from '@tanstack/react-query';

function PostLikeButton({ postId }: { postId: string }) {
  const queryClient = useQueryClient();
  const likeMutation = trpc.post.like.useMutation({
    onMutate: async (newLike) => {
      await queryClient.cancelQueries(['post', postId]);
      const previousPost = queryClient.getQueryData(['post', postId]);
      queryClient.setQueryData(['post', postId], (old: any) => {
        if (old) return { ...old, likes: old.likes + 1, isLiked: true };
        return old;
      });
      return { previousPost };
    },
    onError: (err, newLike, context) => {
      queryClient.setQueryData(['post', postId], context?.previousPost);
      console.error("Failed to like post: ", err.message);
    },
    onSuccess: () => {
      // Invalidate and refetch the post data to ensure consistency
      queryClient.invalidateQueries(['post', postId]);
    },
  });

  return (
    <button onClick={() => likeMutation.mutate({ postId })}>Like</button>
  );
}

Benefits and Considerations

Optimistic updates are fantastic for user experience, but they add complexity:

  • Pro: Instant UI feedback, perceived performance boost.
  • Pro: Reduces loading spinners and waiting times.
  • Con: Requires careful rollback logic for errors.
  • Con: Can be complex for operations that depend on server-generated IDs or complex data transformations.

Use them thoughtfully, especially for actions where immediate feedback is critical and conflicts are rare.

Check Your Understanding

Consider an optimistic update for adding an item to a shopping cart. Which of the following actions are typically performed within the onMutate callback?

Recap: Optimistic Updates

In this lesson, we explored optimistic updates, a powerful technique to enhance user experience by providing instant feedback.

  • We learned how onMutate is used to optimistically update the UI and prepare for potential rollbacks.
  • We saw how onError handles reverting the UI to its previous state if the server request fails.
  • Finally, we covered how onSuccess ensures data consistency by invalidating and refetching data after a successful server response.

Mastering optimistic updates helps you build highly responsive and user-friendly tRPC applications!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Mengimplementasikan Pembaruan Optimistis” gratis?

Ya — teks lengkap “Mengimplementasikan Pembaruan Optimistis” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus tRPC End-to-End Type Safe APIs, upgrade ke CoddyKit PRO. Kursus tRPC End-to-End Type Safe APIs mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Mengimplementasikan Pembaruan Optimistis”?

Pelajari cara memberikan pengalaman pengguna yang instan dengan mengimplementasikan pembaruan optimistis menggunakan tRPC dan cache sisi klien. Kamu berlatih tRPC End-to-End Type Safe APIs dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai tRPC End-to-End Type Safe APIs?

Tidak diperlukan pengalaman sebelumnya. tRPC End-to-End Type Safe APIs di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 2 dari 4.

Berapa lama pelajaran “Mengimplementasikan Pembaruan Optimistis” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran tRPC End-to-End Type Safe APIs ini?

Ya. Setiap pelajaran tRPC End-to-End Type Safe APIs menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

  1. Pengelompokan Permintaan yang Efisien
  2. Mengimplementasikan Pembaruan Optimistis
  3. Pengunggahan Berkas dengan tRPC
  4. Query Tak Terbatas dan Pagination Berbasis Cursor
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