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tRPC End-to-End Type Safe APIs · Lesson

Implementing Optimistic Updates

Learn to provide an instant user experience by implementing optimistic updates with tRPC and a client-side cache.

Implementing Optimistic Updates is a free tRPC End-to-End Type Safe APIs lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the tRPC End-to-End Type Safe APIs learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

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!

Frequently asked questions

Is the “Implementing Optimistic Updates” lesson free?

Yes — the full text of “Implementing Optimistic Updates” is free to read here on the web, and the tRPC End-to-End Type Safe APIs course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the tRPC End-to-End Type Safe APIs course, upgrade to CoddyKit PRO.

What will I learn in “Implementing Optimistic Updates”?

Learn to provide an instant user experience by implementing optimistic updates with tRPC and a client-side cache. You practise tRPC End-to-End Type Safe APIs with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start tRPC End-to-End Type Safe APIs?

No prior experience is required. tRPC End-to-End Type Safe APIs on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Implementing Optimistic Updates” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this tRPC End-to-End Type Safe APIs lesson?

Yes. Every tRPC End-to-End Type Safe APIs lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. Efficient Batching Requests
  2. Implementing Optimistic Updates
  3. File Uploads with tRPC
  4. Infinite Queries and Cursor-Based Pagination
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