* certificate is issued to `example.com` and the request is to `localhost`, the connection will
     * fail. Use a custom [HostnameVerifier] to ignore such problems.
     *
     * Other TLS features are still used but provide no security benefits in absence of the above
     * gaps. For example, an insecure TLS connection is capable of negotiating HTTP/2 with ALPN and

    "tax": 3.2,
    "tags": [
        "rock",
        "metal",
        "bar"
    ],
    "images": [
        {
            "url": "http://example.com/baz.jpg",
            "name": "The Foo live"
        },
        {
            "url": "http://example.com/dave.jpg",
            "name": "The Baz"
        }
    ]
}
```

/// info | Información

```

就能以如下方式调用：

```Python
user_dict = user_in.dict()
```

现在，变量 `user_dict`中的就是包含数据的**字典**（变量 `user_dict` 是字典，不是 Pydantic 模型对象）。

以如下方式调用：

```Python
print(user_dict)
```

输出的就是 Python **字典**：

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': 'john.doe@example.com',
    'full_name': None,
}
```

    "tax": 3.2,
    "tags": [
        "rock",
        "metal",
        "bar"
    ],
    "images": [
        {
            "url": "http://example.com/baz.jpg",
            "name": "The Foo live"
        },
        {
            "url": "http://example.com/dave.jpg",
            "name": "The Baz"
        }
    ]
}
```

/// info | Інформація

{
    "name": "s3-zip-example",
    "version": "1.0.0",
    "main": "main.js",
    "dependencies": {
        "aws-sdk": "^2.924.0"
    }

    <modelVersion>4.0.0</modelVersion>

    <parent>
        <groupId>org.example</groupId>
        <artifactId>parent</artifactId>
        <version>0.0.1-SNAPSHOT</version>
        <relativePath>./parent-pom.xml</relativePath>
    </parent>

    <artifactId>child</artifactId>

to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate
formats that can be processed by TensorFlow.

    private ReserializedSetGenerator(OneSizeTestContainerGenerator<Collection<E>, E> gen) {
      this.gen = gen;
    }

    @Override
    public SampleElements<E> samples() {
      return gen.samples();
    }

    @Override
    public Set<E> create(Object... elements) {
      return (Set<E>) SerializableTester.reserialize(gen.create(elements));
    }

    @Override

### Build session state

A "build session" represents a single invocation of Gradle, for example when you run `gradlew build`.
A session runs the build one or more times.
For example, when continuous build is enabled, the session may run the build many times, but when it is disabled, the session will run the build once only.

# Debugging { #debugging }

You can connect the debugger in your editor, for example with Visual Studio Code or PyCharm.

## Call `uvicorn` { #call-uvicorn }

In your FastAPI application, import and run `uvicorn` directly:

{* ../../docs_src/debugging/tutorial001_py39.py hl[1,15] *}

### About `__name__ == "__main__"` { #about-name-main }