### Usage

```
minio server --config config.yaml
```

Lets you start MinIO server with all inputs to start MinIO server provided via this configuration file, once the configuration file is provided all other pre-existing values on disk for configuration are overridden by the new values set in this configuration file.

                                                        data-href="${contextPath}/admin/dict/synonym/details/${f:u(dictId)}/4/${f:u(data.id)}">
                                                    <td>${f:h(data.inputs)}</td>
                                                    <td>${f:h(data.outputs)}</td>
                                                </tr>
                                            </c:forEach>

        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

import (
	"testing"
)

func TestEvalSQLLike(t *testing.T) {
	dropCases := []struct {
		input, resultExpected string
		matchExpected         bool
	}{
		{"", "", false},
		{"a", "", true},
		{"ab", "b", true},
		{"தமிழ்", "மிழ்", true},
	}

	for i, tc := range dropCases {
		res, ok := dropRune(tc.input)
		if res != tc.resultExpected || ok != tc.matchExpected {
			t.Errorf("DropRune Case %d failed", i)
		}

    validations:
      required: true
  - type: input
    id: gradle-version
    attributes:
      label: Gradle version
      description: What version of Gradle are you running?
    validations:
      required: true
  - type: input
    id: build-scan-url
    attributes:
      label: Build scan URL (optional)
      description: |

        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

                        updater.write("# " + line);
                    }
                    continue;
                }

                final String input = m.group(1).trim();
                final String output = m.group(2).trim();

                if (input == null || output == null) {
                    logger.warn("Failed to parse {} to {}", line, path);
                    if (updater != null) {

# Response Model - Return Type

You can declare the type used for the response by annotating the *path operation function* **return type**.

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

//// tab | Python 3.10+

```Python hl_lines="16  21"
{!> ../../docs_src/response_model/tutorial001_01_py310.py!}
```