price: float
    tax: float | None = None
    tags: set[str] = set()


@app.post("/items/", response_model=Item, summary="Create an item")
async def create_item(item: Item):
    """
    Create an item with all the information:

    - **name**: each item must have a name
    - **description**: a long description
    - **price**: required
    - **tax**: if the item doesn't have tax, you can omit this

)

// BaseChecksumTypes is a list of all the base checksum types.
var BaseChecksumTypes = []ChecksumType{ChecksumSHA256, ChecksumSHA1, ChecksumCRC32, ChecksumCRC64NVME, ChecksumCRC32C}

// Checksum is a type and base 64 encoded value.
type Checksum struct {
	Type      ChecksumType
	Encoded   string
	Raw       []byte
	WantParts int
}

// Is returns if c is all of t.
func (c ChecksumType) Is(t ChecksumType) bool {

    private static final int INCOMPARABLE = 2;

    /**
     * Keep track of all methods with the same name.
     */
    private final Map<String, List<Method>> methodByNameMap = new Hashtable<>();

    /**
     * Add a method to a list of methods by name.
     * For a particular class we are keeping track
     * of all the methods with the same name.
     *
     * @param method The method
     */

~~ specific language governing permissions and limitations
~~ under the License.

 -----
 Super POM
 -----
 Hervé Boutemy
 -----
 2011-09-12
 -----

Super POM

 All models implicitly inherit from a super-POM:

# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

# All required CUDA packages
cuda-compat-13-0
cuda-command-line-tools-13-0
cuda-cudart-dev-13-0
cuda-nvcc-13-0
cuda-cupti-13-0
cuda-nvprune-13-0
cuda-libraries-13-0
cuda-libraries-dev-13-0
cuda-nvml-dev-13-0
libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0

```

##### Node (optional)

Optionally you can also collect per node metrics. This needs to be done on a per server instance.
The scrape configurations should use all the servers under `targets` so that graphing systems like
grafana can visualize them for all the nodes

```yaml
scrape_configs:
- job_name: minio-job
  metrics_path: /minio/v2/metrics/node
  scheme: http
  static_configs:

 * <ol>
 *   <li>File model - The raw model as read directly from the file</li>
 *   <li>Raw model - The model after inheritance has been applied</li>
 *   <li>Effective model - The fully processed model with all interpolation and inheritance applied</li>
 * </ol>
 * <p>
 * Implementations of this interface will be discovered through the Java ServiceLoader mechanism
 * and will be called in sequence during model building.
 * <p>

  of the code that references this method, since the container should provide
  some way of recontextualizing the mojo, and all we would need to do is inject
  POM configuration via the lookup method or something.

* PluginDescriptorBuilder

  s/getMojoConfiguration()/getConfiguration()/g

  That should be all there is to it.

* MojoDescriptor

  Remove set/getMojoConfiguration(..), as it will become obsolete.

* MavenSession

        this(projects, projects);
    }

    /**
     * Creates a new project dependency graph based on the specified projects.
     *
     * @param allProjects All collected projects.
     * @param projects    The projects to create the dependency graph with.
     * @throws DuplicateProjectException
     * @throws CycleDetectedException
     * @since 3.5.0