tRPC End-to-End Type Safe APIs · 课时

实现查询过程

使用带有输入和输出类型的 tRPC 查询过程，创建只读数据获取端点。

实现查询过程 是 CoddyKit 上的免费 tRPC End-to-End Type Safe APIs 课时。这是第 2 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 tRPC End-to-End Type Safe APIs 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 tRPC End-to-End Type Safe APIs 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

What are tRPC Queries?

Queries are like asking a question to your server. They are designed for fetching data, not changing it. Think of them as the "GET" requests in a traditional REST API.

Read-only: Queries should never change data on your server.
Idempotent: Running a query multiple times should produce the same result.
Cached: Clients can often cache query results for better performance.

They are the foundation for retrieving information in your tRPC application.

Defining a Simple Query

In tRPC, you define queries within a router using .query(). Let's look at the basic structure.

First, you need to initialize tRPC (usually done once in your server setup):

const t = initTRPC.create();

Then, define your router and add a query:

import { initTRPC } from '@trpc/server';

// 1. Initialize tRPC
const t = initTRPC.create();

// 2. Create a router
const appRouter = t.router({
  // 3. Define a query named 'hello'
  hello: t.procedure.query(() => {
    return 'Hello from tRPC!';
  }),
});
// This snippet shows the core definition.
// A full server setup is needed to run it.

Your First Runnable Query (Server)

Let's put it all together into a minimal, runnable tRPC server. This server will host our hello query.

Save this as server.ts and run with ts-node server.ts (after npm install @trpc/server @trpc/server-adapters ts-node typescript).

import { initTRPC } from '@trpc/server';
import { createHTTPServer } from '@trpc/server/adapters/standalone';

const t = initTRPC.create();

const appRouter = t.router({
  hello: t.procedure.query(() => {
    console.log('Hello query called on server!');
    return 'Hello from tRPC!';
  }),
});

export type AppRouter = typeof appRouter;

const server = createHTTPServer({
  router: appRouter,
});

server.listen(2025);
console.log('tRPC server listening on http://localhost:2025');

Calling a Query from the Client

Now that our server is running, let's call the hello query from a client application. We'll use @trpc/client to create a proxy that mirrors our server's API.

Save this as client.ts. You'll need the server.ts running first.

import { createTRPCProxyClient, httpBatchLink } from '@trpc/client';

// Simplified AppRouter type for this example
type AppRouter = {
  hello: {
    _def: {
      _input_in: undefined;
      _input_out: undefined;
      _output_in: string;
      _output_out: string;
    };
  };
};

const trpc = createTRPCProxyClient<AppRouter>({
  links: [
    httpBatchLink({
      url: 'http://localhost:2025',
    }),
  ],
});

async function callHello() {
  try {
    const greeting = await trpc.hello.query();
    console.log(greeting); // Expected: Hello from tRPC!
  } catch (error) {
    console.error('Error calling hello query:', error);
  }
}

callHello();

Passing Data to Queries

Often, you need to send data to your queries, for example, to fetch a specific user by ID. tRPC handles this beautifully with input schemas.

You define the expected input using a validation library like Zod. This ensures your input is always type-safe and valid, both on the client and server.

Use .input() after t.procedure.
Provide a Zod schema to define the shape of your input.
The input will be available in the input property of the resolve function's arguments.

Querying with an ID (Server)

Let's modify our server to fetch a "user" by their ID. We'll use Zod to validate that the input is a number.

Update your server.ts with this new procedure:

import { initTRPC } from '@trpc/server';
import { createHTTPServer } from '@trpc/server/adapters/standalone';
import { z } from 'zod'; // Import Zod

const t = initTRPC.create();

const appRouter = t.router({
  getUserById: t.procedure
    .input(z.object({ id: z.number() })) // Define input schema
    .query(({ input }) => { // Access input here
      console.log(`Fetching user with ID: ${input.id}`);
      // In a real app, you'd fetch from a database
      const users = [{ id: 1, name: 'Alice' }, { id: 2, name: 'Bob' }];
      return users.find(user => user.id === input.id) || null;
    }),
});

export type AppRouter = typeof appRouter;

const server = createHTTPServer({
  router: appRouter,
});

server.listen(2025);
console.log('tRPC server listening on http://localhost:2025');

Calling Query with Input (Client)

Now, from the client, we can call our getUserById query and pass the required id. tRPC will ensure the input matches the Zod schema defined on the server, giving you type safety from end-to-end.

Update your client.ts to call this new query:

import { createTRPCProxyClient, httpBatchLink } from '@trpc/client';

// Simplified AppRouter for example
type AppRouter = {
  getUserById: {
    _def: {
      _input_in: { id: number };
      _input_out: { id: number };
      _output_in: { id: number; name: string } | null;
      _output_out: { id: number; name: string } | null;
    };
  };
};

const trpc = createTRPCProxyClient<AppRouter>({
  links: [
    httpBatchLink({
      url: 'http://localhost:2025',
    }),
  ],
});

async function callGetUser() {
  try {
    const user1 = await trpc.getUserById.query({ id: 1 });
    console.log('User 1:', user1); // Expected: User 1: { id: 1, name: 'Alice' }

    const user3 = await trpc.getUserById.query({ id: 3 });
    console.log('User 3:', user3); // Expected: User 3: null
  } catch (error) {
    console.error('Error calling getUserById query:', error);
  }
}

callGetUser();

Type Safety in Query Outputs

One of tRPC's biggest advantages is its end-to-end type safety. When you define a query, tRPC automatically infers the output type based on what your resolve function returns.

No need to manually define response interfaces.
If your server's return type changes, your client code will automatically show a TypeScript error.
This catches bugs early, before runtime!

For our getUserById query, tRPC correctly infers the return type as { id: number; name: string } | null.

Query Best Practices

As you build more queries, keep these tips in mind:

Keep it Read-Only: Never perform side effects (like database writes) in a query.
Clear Naming: Name your queries descriptively (e.g., getUserById, listPosts).
Granular Inputs: Use specific Zod schemas for inputs to ensure strict validation.
Error Handling: While tRPC propagates errors, consider specific error types for better client feedback (more on this in a later lesson!).

Queries are fundamental for fetching data. Next, we'll look at Mutations for changing data.

Query Procedure Check

You've learned how to define and use tRPC query procedures. Let's test your understanding.

Recap: Query Procedures

Great job! In this lesson, you learned about tRPC Query procedures.

Queries are for fetching read-only data from your server.
You define them using t.procedure.query(...) within your router.
You can add input validation using .input(z.object(...)) with Zod.
tRPC provides end-to-end type safety by inferring output types automatically.

You now have the tools to build powerful, type-safe data fetching endpoints! Next, we'll explore Mutations for data manipulation.

常见问题解答

「实现查询过程」课时是免费的吗？

是的 — 「实现查询过程」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 tRPC End-to-End Type Safe APIs 课程的其余内容，请升级到 CoddyKit PRO。 tRPC End-to-End Type Safe APIs 课程共包含 4 节课。

「实现查询过程」这节课中我会学到什么？

使用带有输入和输出类型的 tRPC 查询过程，创建只读数据获取端点。你通过在浏览器中直接运行的动手代码来练习 tRPC End-to-End Type Safe APIs，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 tRPC End-to-End Type Safe APIs 需要有经验吗？

无需任何先前经验。CoddyKit 上的 tRPC End-to-End Type Safe APIs 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 2 节课，共 4 节。

「实现查询过程」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 tRPC End-to-End Type Safe APIs 课中编写并运行代码吗？

能。每节 tRPC End-to-End Type Safe APIs 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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