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`:

var ErrOverread = errors.New("input provided more bytes than specified")

// HardLimitReader returns a Reader that reads from r
// but returns an error if the source provides more data than allowed.
// This means the source *will* be overread unless EOF is returned prior.
// The underlying implementation is a *HardLimitedReader.
// This will ensure that at most n bytes are returned and EOF is reached.

    @VisibleForTesting
    data class AcceptedApiChange(
        val type: String?,
        val member: String?,
        val acceptation: String?,
        val changes: List<String>?
    ) {
        override fun toString(): String = "Type: '$type', Member: '$member'"
    }

    @VisibleForTesting
    data class AcceptedApiChanges(
        val acceptedApiChanges: List<AcceptedApiChange>?

post() {
    local endpoint="$1"
    local data="$2"

    local response=$(curl -X POST \
        -H "Authorization: token $GITHUB_TOKEN" \
        -H "Accept: application/vnd.github.v3+json" \
        -H "Content-Type: application/json" \
        "https://api.github.com/repos/gradle/gradle$endpoint" \
        -d "$data" \
        -w "\n%{http_code}" \
        2>/dev/null)

labels.crawling_info_DataCrawlExecTime=Crawl Execution Time (Data Store)
labels.crawling_info_DataCrawlStartTime=Crawl Start Time (Data Store)
labels.crawling_info_DataCrawlEndTime=Crawl End Time (Data Store)
labels.crawling_info_DataIndexExecTime=Indexing Execution Time (Data Store)
labels.crawling_info_DataIndexSize=Index Size (Data Store)
labels.webauth_configuration=Web Authentication

# WebSockets

When defining WebSockets, you normally declare a parameter of type `WebSocket` and with it you can read data from the client and send data to it.

It is provided directly by Starlette, but you can import it from `fastapi`:

```python
from fastapi import WebSocket
```

/// tip

    }

    @Override
    public void send(ByteBuffer data, RdmaMemoryRegion region) throws IOException {
        if (state != RdmaConnectionState.ESTABLISHED && state != RdmaConnectionState.CONNECTED) {
            throw new IOException("Connection not established");
        }

        try {
            while (data.hasRemaining()) {
                socketChannel.write(data);
            }
        } catch (IOException e) {

 * Provides RESTful API endpoints for managing file crawling configuration settings in the Fess search engine.
 * File configurations define settings for crawling file systems, FTP servers, and other file-based data sources.
 *
 */
public class ApiAdminFileconfigAction extends FessApiAdminAction {

    private static final Logger logger = LogManager.getLogger(ApiAdminFileconfigAction.class);

{* ../../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`:

<div class="screenshot">

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

data class Subproject(
    val name: String,
    val size: Int,
)

interface SubprojectBucket

data class SmallSubprojectCombination(
    val subprojects: List<Subproject>,
) : SubprojectBucket

data class LargeSubprojectSplit(
    val subproject: Subproject,
    val split: Int,
) : SubprojectBucket