</div>

## 建立只有單一模型的應用 { #create-the-app-with-a-single-model }

我們先用單一 SQLModel 模型建立這個應用的最簡版。

接著我們會在下方用多個模型來提升安全性與彈性。🤓

### 建立模型 { #create-models }

匯入 `SQLModel` 並建立一個資料庫模型：

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

`Hero` 類別與 Pydantic 模型非常相似（事實上，在底層它就是一個 Pydantic 模型）。

有幾點差異：

* `table=True` 告訴 SQLModel 這是一個「資料表模型」（table model），它應該代表 SQL 資料庫中的一個資料表，而不僅僅是「資料模型」（就像一般的 Pydantic 類別）。

            <option value="$PROJECT_DIR$/platforms/core-configuration/kotlin-dsl-tooling-models" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-core" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-groovy" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-reflect" />

<div class="termy">

```console
$ pip install sqlmodel
---> 100%
```

</div>

## 创建含有单一模型的应用 { #create-the-app-with-a-single-model }

我们先创建应用的最简单的第一个版本，只有一个 **SQLModel** 模型。

稍后我们将通过下面的**多个模型**提高其安全性和多功能性。🤓

### 创建模型 { #create-models }

导入 `SQLModel` 并创建一个数据库模型：

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

				})
			}
		}
	})

	var models []User
	if err := DB.Where("name in (?)", []string{"find"}).Find(&models).Error; err != nil || len(models) != 3 {
		t.Errorf("errors happened when query find with in clause: %v, length: %v", err, len(models))
	} else {
		for idx, user := range users {
			t.Run("FindWithInClause#"+strconv.Itoa(idx+1), func(t *testing.T) {
				CheckUser(t, models[idx], user)
			})
		}
	}

import java.io.IOException
import okhttp3.Headers
import okhttp3.internal.delimiterOffset
import okhttp3.internal.trimSubstring
import org.codehaus.mojo.animal_sniffer.IgnoreJRERequirement

/**
 * Models the contents of a `Sec-WebSocket-Extensions` response header. OkHttp honors one extension
 * `permessage-deflate` and four parameters, `client_max_window_bits`, `client_no_context_takeover`,

 * under the License.
 */
package org.apache.maven.model.building;

import java.io.File;
import java.util.ArrayList;
import java.util.Date;
import java.util.List;
import java.util.Properties;

import org.apache.maven.model.Model;
import org.apache.maven.model.Profile;
import org.apache.maven.model.resolution.ModelResolver;
import org.apache.maven.model.resolution.WorkspaceModelResolver;

/**

 * <ol>
 * <li>success - in which case only the model field is set
 * <li>success with warnings - model field + non-error model problems
 * <li>error - no model, but diagnostics
 * <li>error - (partial) model and diagnostics
 * </ol>
 * Could encode these variants as subclasses, but kept in one for now
 *
 * @param <T> the model type
 * @deprecated use {@code org.apache.maven.api.services.ModelBuilder} instead

{* ../../docs_src/first_steps/tutorial001_py310.py hl[8] *}

You can return a `dict`, `list`, singular values as `str`, `int`, etc.

You can also return Pydantic models (you'll see more about that later).

There are many other objects and models that will be automatically converted to JSON (including ORMs, etc). Try using your favorite ones, it's highly probable that they are already supported.

/// info

Note that the `TestClient` receives data that can be converted to JSON, not Pydantic models.

If you have a Pydantic model in your test and you want to send its data to the application during testing, you can use the `jsonable_encoder` described in [JSON Compatible Encoder](encoder.md).

///

## Run it { #run-it }

├── request/
│   ├── suggest/               # Suggestion queries
│   └── popularwords/          # Popular word queries
├── settings/                   # Configuration management
├── entity/                     # Domain models (SuggestItem, etc.)
├── normalizer/                 # Text normalizers
├── converter/                  # Reading converters (katakana, romaji)
├── concurrent/                 # Async patterns (Deferred/Promise)