- Choice of erasure set size is automatic based on the number of drives available, let's say for example if there are 32 servers and 32 drives which is a total of 1024 drives. In this scenario 16 becomes the erasure set size. This is decided based on the greatest common divisor (GCD) of acceptable erasure set sizes ranging from *4 to 16*.

async def update_item(
    *,
    item_id: int,
    item: Annotated[
        Item,
        Body(
            openapi_examples={
                "normal": {
                    "summary": "A normal example",
                    "description": "A **normal** item works correctly.",
                    "value": {
                        "name": "Foo",
                        "description": "A very nice Item",

certs-dir: '/home/user/.minio/certs/'
pools: # Specify the nodes and drives with pools
  -
        - 'https://server-example-pool1:9000/mnt/disk{1...4}/'
        - 'https://server1-pool1:9000/mnt/disk{1...4}/'
        - 'https://server3-pool1:9000/mnt/disk{1...4}/'
        - 'https://server4-pool1:9000/mnt/disk{1...4}/'
  -
        - 'https://server-example-pool2:9000/mnt/disk{1...4}/'
        - 'https://server1-pool2:9000/mnt/disk{1...4}/'

           --log-format=json-pretty \
           --log-level=debug \
           --set=decision_logs.console=true
```

### 2. Create a sample OPA Policy

In another terminal, create a policy that allows root user all access and for all other users denies `PutObject`:

```sh
cat > example.rego <<EOF
package httpapi.authz

import input

default allow = false

# Allow the root user to perform any action.
allow {

                **Example**

                ```python
                from fastapi import FastAPI

                app = FastAPI(
                    servers=[
                        {"url": "https://stag.example.com", "description": "Staging environment"},
                        {"url": "https://prod.example.com", "description": "Production environment"},
                    ]

* Convert the copied model to something that can be stored in your DB (for example, using the `jsonable_encoder`).
    * This is comparable to using the model's `.model_dump()` method again, but it makes sure (and converts) the values to data types that can be converted to JSON, for example, `datetime` to `str`.
* Save the data to your DB.
* Return the updated model.

//// tab | Python 3.10+

                </mxCell>
                <mxCell id="29" value="&lt;font face=&quot;Roboto&quot; data-font-src=&quot;https://fonts.googleapis.com/css?family=Roboto&quot; style=&quot;font-size: 24px&quot;&gt;https://someapp.example.com&lt;/font&gt;" style="rounded=0;whiteSpace=wrap;html=1;fontStyle=1;strokeWidth=4;" parent="33" vertex="1">
                    <mxGeometry x="60" y="27" width="380" height="250" as="geometry"/>
                </mxCell>

        "Access-Control-Request-Headers": "X-Example",
    }
    response = client.options("/", headers=headers)
    assert response.status_code == 200, response.text
    assert response.text == "OK"
    assert (
        response.headers["access-control-allow-origin"]
        == "https://localhost.tiangolo.com"
    )
    assert response.headers["access-control-allow-headers"] == "X-Example"

    # Test standard response

This includes, for example:

* Email notifications sent after performing an action:
    * As connecting to an email server and sending an email tends to be "slow" (several seconds), you can return the response right away and send the email notification in the background.
* Processing data:

  optional string type = 1;

  // object refers to a metric describing a single kubernetes object
  // (for example, hits-per-second on an Ingress object).
  // +optional
  optional ObjectMetricSource object = 2;

  // pods refers to a metric describing each pod in the current scale target
  // (for example, transactions-processed-per-second).  The values will be
  // averaged together before being compared to the target value.