return new ToolchainFactory() {
            @Override
            public ToolchainPrivate createToolchain(ToolchainModel model) throws MisconfiguredToolchainException {
                try {
                    org.apache.maven.api.Toolchain v4Toolchain = v4Factory.createToolchain(model.getDelegate());
                    return getToolchainV3(v4Toolchain);
                } catch (ToolchainFactoryException e) {

 */
package org.apache.maven.repository.internal;

import java.net.MalformedURLException;
import java.util.Arrays;

import org.apache.maven.model.Dependency;
import org.apache.maven.model.Parent;
import org.apache.maven.model.resolution.ModelResolver;
import org.apache.maven.model.resolution.UnresolvableModelException;
import org.codehaus.plexus.component.repository.exception.ComponentLookupException;

	return execG[T]{g: &g[T]{
		db: c.db,
		ops: append(c.ops, func(db *DB) *DB {
			var r T
			return db.Model(r).Raw(sql, values...)
		}),
	}}
}

func (c *g[T]) Exec(ctx context.Context, sql string, values ...interface{}) error {
	var r T
	return c.apply(ctx).Model(r).Exec(sql, values...).Error
}

type createG[T any] struct {
	chainG[T]
}

{* ../../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.

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;

/**

如果你宣告了 [回應模型](../tutorial/response-model.md)，FastAPI 會用 Pydantic 將資料序列化為 JSON。

如果你沒有宣告回應模型，FastAPI 會使用在[JSON 相容編碼器](../tutorial/encoder.md)中說明的 `jsonable_encoder`，並把它放進 `JSONResponse`。

但你也可以直接從路徑操作回傳 `JSONResponse`。

/// tip

通常使用 [回應模型](../tutorial/response-model.md) 會有更好的效能，因為那樣會在 Rust 端使用 Pydantic 來序列化資料，而不是直接回傳 `JSONResponse`。

///

/// 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 }

Verwenden Sie base64 nur, wenn Sie Binärdaten unbedingt in JSON einbetten müssen und dafür keine Dateien verwenden können.

## Pydantic `bytes` { #pydantic-bytes }

Aynı şekilde bu veritabanı bir Pydantic model'i (attribute'lara sahip bir obje) de kabul etmez; yalnızca bir `dict` kabul eder.

Bunun için `jsonable_encoder` kullanabilirsiniz.

Bir Pydantic model gibi bir obje alır ve JSON ile uyumlu bir versiyonunu döndürür:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

Bu örnekte, Pydantic model'i bir `dict`'e, `datetime`'ı da bir `str`'e dönüştürür.