✋️ 🐍 ⏬ ⏭ 3️⃣.9️⃣ (3️⃣.6️⃣ & 🔛), 👆 🥇 💪 🗄 `List` ⚪️➡️ 🐩 🐍 `typing` 🕹:

```Python hl_lines="1"
{!> ../../../docs_src/body_nested_models/tutorial002.py!}
```

### 📣 `list` ⏮️ 🆎 🔢

📣 🆎 👈 ✔️ 🆎 🔢 (🔗 🆎), 💖 `list`, `dict`, `tuple`:

* 🚥 👆 🐍 ⏬ 🔅 🌘 3️⃣.9️⃣, 🗄 👫 🌓 ⏬ ⚪️➡️ `typing` 🕹
* 🚶‍♀️ 🔗 🆎(Ⓜ) "🆎 🔢" ⚙️ ⬜ 🗜: `[` & `]`

🐍 3️⃣.9️⃣ ⚫️ 🔜:

```Python

```Python hl_lines="2  15-21"
{!../../../docs_src/extending_openapi/tutorial001.py!}
```

### Modify the OpenAPI schema

Now you can add the ReDoc extension, adding a custom `x-logo` to the `info` "object" in the OpenAPI schema:

```Python hl_lines="22-24"
{!../../../docs_src/extending_openapi/tutorial001.py!}
```

### Cache the OpenAPI schema

1. The `caClient` will be configured to use either JWT or mTLS authentication. For JWT authentication, gRPC's `PerRPCCredentials`
   is configured with a `TokenProvider` which handles the logic of adding the proper JWT to each request. mTLS is configured
   by a tls.Config that points to files on disk.

It should be noted there is a circular dependency with mTLS authentication; in order to fetch a certificate we need

하지만 파이썬은 내부의 타입이나 "타입 매개변수"를 선언할 수 있는 특정 방법이 있습니다:

### typing의 `List` 임포트

먼저, 파이썬 표준 `typing` 모듈에서 `List`를 임포트합니다:

```Python hl_lines="1"
{!../../../docs_src/body_nested_models/tutorial002.py!}
```

### 타입 매개변수로 `List` 선언

`list`, `dict`, `tuple`과 같은 타입 매개변수(내부 타입)를 갖는 타입을 선언하려면:

* `typing` 모듈에서 임포트
* 대괄호를 사용하여 "타입 매개변수"로 내부 타입 전달: `[` 및 `]`

```Python
from typing import List

my_list: List[str]
```

numpy ~= 1.23.5 ; python_version <= "3.11"
numpy ~= 1.26.0 ; python_version >= "3.12"
wheel ~= 0.41.2
h5py >= 3.10.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0

# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

But Python has a specific way to declare lists with internal types, or "type parameters":

### Import typing's `List`

In Python 3.9 and above you can use the standard `list` to declare these type annotations as we'll see below. 💡

But in Python versions before 3.9 (3.6 and above), you first need to import `List` from standard Python's `typing` module:

```Python hl_lines="1"
{!> ../../../docs_src/body_nested_models/tutorial002.py!}
```

      val newSize = deflatedBytes.size - LAST_OCTETS_COUNT_TO_REMOVE_AFTER_DEFLATION
      deflatedBytes.readAndWriteUnsafe().use { cursor ->
        cursor.resizeBuffer(newSize)
      }
    } else {
      // Same as adding EMPTY_DEFLATE_BLOCK and then removing 4 bytes.
      deflatedBytes.writeByte(0x00)
    }

    buffer.write(deflatedBytes, deflatedBytes.size)
  }

  @Throws(IOException::class)

Instance is now accessible on the host at port 9000, proceed to access the Web browser at <http://127.0.0.1:9000/>

## Explore Further

- [MinIO Erasure Code Overview](https://min.io/docs/minio/linux/operations/concepts/erasure-coding.html)
- [Use `mc` with MinIO Server](https://min.io/docs/minio/linux/reference/minio-mc.html)
- [Use `aws-cli` with MinIO Server](https://min.io/docs/minio/linux/integrations/aws-cli-with-minio.html)

                withFirEntry("fir", firFunctionSymbol.firSymbol.fir)
            }
        else firFunctionSymbol.valueParameters[valueParameterReference.parameterIndex]
    )

    // Util function to avoid hard coding names of the classes. Type inference will do a better job figuring out the best type to cast to.
    // This visitor isn't type-safe anyway
    private inline fun <reified T> ConeContractDescriptionElement.accept() =

3.  Pull requests are not merged directly into the master branch.
4.  Code contributions require signing a Google CLA.

API changes
-----------

We make changes to Guava's public [APIs][], including adding new APIs, very
carefully. Because of this, if you're interested in seeing a new feature in
Guava, the best approach is to create an [issue][] (or comment on an existing