* `tax: float = 10.5` has a default of `10.5`.
* `tags: List[str] = []` has a default of an empty list: `[]`.

but you might want to omit them from the result if they were not actually stored.

For example, if you have models with many optional attributes in a NoSQL database, but you don't want to send very long JSON responses full of default values.

!!! info
    你还可以使用：

    * `response_model_exclude_defaults=True`
    * `response_model_exclude_none=True`

    参考 <a href="https://docs.pydantic.dev/latest/concepts/serialization/#modeldict" class="external-link" target="_blank">Pydantic 文档</a> 中对 `exclude_defaults` 和 `exclude_none` 的描述。

#### 默认值字段有实际值的数据

但是，如果你的数据在具有默认值的模型字段中有实际的值，例如 ID 为 `bar` 的项：

!!! info "情報"
    以下も使用することができます:

    * `response_model_exclude_defaults=True`
    * `response_model_exclude_none=True`

    `exclude_defaults`と`exclude_none`については、<a href="https://docs.pydantic.dev/latest/concepts/serialization/#modeldict" class="external-link" target="_blank">Pydanticのドキュメント</a>で説明されている通りです。

This utility function will:

* Connect to a **Couchbase** cluster (that might be a single machine).
    * Set defaults for timeouts.
* Authenticate in the cluster.
* Get a `Bucket` instance.
    * Set defaults for timeouts.
* Return it.

```Python hl_lines="12-21"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

## Create Pydantic models

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

!!! info
    Sie können auch:

    * `response_model_exclude_defaults=True`
    * `response_model_exclude_none=True`

    verwenden, wie in der <a href="https://docs.pydantic.dev/1.10/usage/exporting_models/#modeldict" class="external-link" target="_blank">Pydantic Dokumentation</a> für `exclude_defaults` und `exclude_none` beschrieben.

#### Daten mit Werten für Felder mit Defaultwerten

    "B",  # flake8-bugbear
    "C4",  # flake8-comprehensions
    "UP",  # pyupgrade
]
ignore = [
    "E501",  # line too long, handled by black
    "B008",  # do not perform function calls in argument defaults
    "C901",  # too complex
    "W191",  # indentation contains tabs
]

[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F401"]
"docs_src/dependencies/tutorial007.py" = ["F821"]

!!! info
    👆 💪 ⚙️:

    * `response_model_exclude_defaults=True`
    * `response_model_exclude_none=True`

    🔬 <a href="https://docs.pydantic.dev/latest/concepts/serialization/#modeldict" class="external-link" target="_blank">Pydantic 🩺</a> `exclude_defaults` &amp; `exclude_none`.

#### 📊 ⏮️ 💲 🏑 ⏮️ 🔢

✋️ 🚥 👆 📊 ✔️ 💲 🏷 🏑 ⏮️ 🔢 💲, 💖 🏬 ⏮️ 🆔 `bar`:

## Overriding the defaults

Using the information above, you can use the same utility function to generate the OpenAPI schema and override each part that you need.

For example, let's add <a href="https://github.com/Rebilly/ReDoc/blob/master/docs/redoc-vendor-extensions.md#x-logo" class="external-link" target="_blank">ReDoc's OpenAPI extension to include a custom logo</a>.

### Normal **FastAPI**

Peewee was not designed for async frameworks, or with them in mind.

Peewee has some heavy assumptions about its defaults and about how it should be used.

If you are developing an application with an older non-async framework, and can work with all its defaults, **it can be a great tool**.