line, col int
	Key       string `yaml:"key" json:"key"`
	Value     string `yaml:"value" json:"value"`
}

var _ yaml.Unmarshaler = &BatchJobKV{}

// UnmarshalYAML - BatchJobKV extends default unmarshal to extract line, col information.
func (kv *BatchJobKV) UnmarshalYAML(val *yaml.Node) error {
	type jobKV BatchJobKV
	var tmp jobKV
	err := val.Decode(&tmp)
	if err != nil {
		return err
	}
	*kv = BatchJobKV(tmp)

        ByteBuffer bb = ByteBuffer.wrap(result).order(java.nio.ByteOrder.LITTLE_ENDIAN);

        long mostSig = guid.getMostSignificantBits();
        long leastSig = guid.getLeastSignificantBits();

        // Extract GUID components from UUID
        int data1 = (int) (mostSig >>> 32); // first 4 bytes
        short data2 = (short) (mostSig >>> 16); // next 2 bytes
        short data3 = (short) mostSig; // next 2 bytes

Declare the **query parameters** that you need in a **Pydantic model**, and then declare the parameter as `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

**FastAPI** will use that *temporal* response to extract the status code (also cookies and headers), and will put them in the final response that contains the value you returned, filtered by any `response_model`.

        with:
          name: maven-distributions
          path: maven-dist

      - name: List downloaded files
        shell: bash
        run: ls -la maven-dist

      - name: Extract Maven distribution
        shell: bash
        run: |
          mkdir -p maven-local
          if [ "${{ runner.os }}" = "Windows" ]; then
            unzip maven-dist/apache-maven-*-bin.zip -d maven-local

}

func extractMetadata(ctx context.Context, mimesHeader ...textproto.MIMEHeader) (metadata map[string]string, err error) {
	metadata = make(map[string]string)

	for _, hdr := range mimesHeader {
		// Extract all query values.
		err = extractMetadataFromMime(ctx, hdr, metadata)
		if err != nil {
			return nil, err
		}
	}

	// Set content-type to default value if it is not set.

{* ../../docs_src/request_form_models/tutorial001_an_py39.py hl[9:11,15] *}

**FastAPI** will **extract** the data for **each field** from the **form data** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can verify it in the docs UI at `/docs`:

But a variable like `user-agent` is invalid in Python.

So, by default, `Header` will convert the parameter names characters from underscore (`_`) to hyphen (`-`) to extract and document the headers.

Also, HTTP headers are case-insensitive, so, you can declare them with standard Python style (also known as "snake_case").

And you could do this even if the data type in the request is not JSON.

For example, in this application we don't use FastAPI's integrated functionality to extract the JSON Schema from Pydantic models nor the automatic validation for JSON. In fact, we are declaring the request content type as YAML, not JSON:

//// tab | Pydantic v2

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

**FastAPI** will use that *temporal* response to extract the headers (also cookies and status code), and will put them in the final response that contains the value you returned, filtered by any `response_model`.