Therefore, if you run a `tf.train.Server` in your network, anybody with access
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

Each section gradually builds on the previous ones, but it's structured to separate topics, so that you can go directly to any specific one to solve your specific API needs.

It is also built to work as a future reference so you can come back and see exactly what you need.

## Run the code { #run-the-code }

All the code blocks can be copied and used directly (they are actually tested Python files).

# Declare Request Example Data { #declare-request-example-data }

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models { #extra-json-schema-data-in-pydantic-models }

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

# Configure Swagger UI { #configure-swagger-ui }

You can configure some extra <a href="https://swagger.io/docs/open-source-tools/swagger-ui/usage/configuration/" class="external-link" target="_blank">Swagger UI parameters</a>.

To configure them, pass the `swagger_ui_parameters` argument when creating the `FastAPI()` app object or to the `get_swagger_ui_html()` function.

`swagger_ui_parameters` receives a dictionary with the configurations passed to Swagger UI directly.

MinIO supports two ways of encrypting IAM and configuration data.
You can either use KES - together with an external KMS - or, much simpler,
set the env. variable `MINIO_KMS_SECRET_KEY` and start/restart the MinIO server. For more details about KES and how
to set it up refer to our [KMS Guide](https://github.com/minio/minio/blob/master/docs/kms/README.md).

Instead of configuring an external KMS you can start with a single key by

# Response Status Code { #response-status-code }

The same way you can specify a response model, you can also declare the HTTP status code used for the response with the parameter `status_code` in any of the *path operations*:

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* etc.

{* ../../docs_src/response_status_code/tutorial001_py39.py hl[6] *}

/// note

/// warning

This is a more or less advanced section. If you are just starting, you can skip it.

You don't necessarily need OAuth2 scopes, and you can handle authentication and authorization however you want.

But OAuth2 with scopes can be nicely integrated into your API (with OpenAPI) and your API docs.

## Overview

MinIO supports two storage classes, Reduced Redundancy class and Standard class. These classes can be defined using environment variables
set before starting MinIO server. After the data and parity drives for each storage class are defined using environment variables,
you can set the storage class of an object via request metadata field `x-amz-storage-class`. MinIO server then honors the storage class by

But this way we can focus on how the **Dependency Injection** system works.

### Create a dependency, or "dependable" { #create-a-dependency-or-dependable }

Let's first focus on the dependency.

It is just a function that can take all the same parameters that a *path operation function* can take:

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[8:9] *}

It is possible to receive duplicate headers. That means, the same header with multiple values.

You can define those cases using a list in the type declaration.

You will receive all the values from the duplicate header as a Python `list`.

For example, to declare a header of `X-Token` that can appear more than once, you can write:

{* ../../docs_src/header_params/tutorial003_an_py310.py hl[9] *}