# Extra Data Types

Up to now, you have been using common data types, like:

* `int`
* `float`
* `str`
* `bool`

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

## Other data types

    ```Python hl_lines="1  3  12-16"
    {!> ../../../docs_src/extra_data_types/tutorial001_an_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="1  3  12-16"
    {!> ../../../docs_src/extra_data_types/tutorial001_an_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="1  3  13-17"
    {!> ../../../docs_src/extra_data_types/tutorial001_an.py!}
    ```

=== "Python 3.10+ non-Annotated"

=== "Python 3.8 и выше"

    ```Python hl_lines="1  3  12-16"
    {!> ../../../docs_src/extra_data_types/tutorial001.py!}
    ```

=== "Python 3.10 и выше"

    ```Python hl_lines="1  2  11-15"
    {!> ../../../docs_src/extra_data_types/tutorial001_py310.py!}
    ```

```Python hl_lines="1  3  12-16"
{!../../../docs_src/extra_data_types/tutorial001.py!}
```

Note que os parâmetros dentro da função tem seu tipo de dados natural, e você pode, por exemplo, realizar manipulações normais de data, como:

```Python hl_lines="18-19"
{!../../../docs_src/extra_data_types/tutorial001.py!}

    callback.assertTextMessage("Hello")
  }

  @Test fun clientTwoFrameHelloWithPongs() {
    data.write("010348656c".decodeHex()) // Hel
    data.write("8a00".decodeHex()) // Pong
    data.write("8a00".decodeHex()) // Pong
    data.write("8a00".decodeHex()) // Pong
    data.write("8a00".decodeHex()) // Pong
    data.write("80026c6f".decodeHex()) // lo
    clientReader.processNextFrame()
    callback.assertPong(EMPTY)

  @Test
  fun largeRead() {
    val data = randomByteString(1000000)
    write(data)
    val operator =
      FileOperator(
        randomAccessFile!!.getChannel(),
      )
    val buffer = Buffer()
    operator.read(0, buffer, data.size.toLong())
    assertThat(buffer.readByteString()).isEqualTo(data)
  }

  @Test
  fun largeWrite() {
    val data = randomByteString(1000000)
    val operator =

Lambda

MinIO's Object Lambda implementation allows for transforming your data to serve unique data format requirements for each application. For example, a dataset created by an ecommerce application might include personally identifiable information (PII). When the same data is processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing campaign, you might need to enrich the data with additional details, such as information from the customer loyalty database....

    drainCancelQueue(eventSource)
  }

  override fun onEvent(
    eventSource: EventSource,
    id: String?,
    type: String?,
    data: String,
  ) {
    get().log("[ES] onEvent", Platform.INFO, null)
    events.add(Event(id, type, data))
    drainCancelQueue(eventSource)
  }

  override fun onClosed(eventSource: EventSource) {
    get().log("[ES] onClosed", Platform.INFO, null)

Traditional retrieval of objects is always as whole entities, i.e GetObject for a 5 GiB object, will always return 5 GiB of data. S3 Select API allows us to retrieve a subset of data by using simple SQL expressions. By using Select API to retrieve only the data needed by the application, drastic performance improvements can be achieved.

You can use the Select API to query objects with following features:

      """
      |--AaB03x
      |Content-Disposition: form-data; name="field with spaces"; filename="filename with spaces.txt"
      |Content-Type: text/plain; charset=utf-8
      |
      |okay
      |--AaB03x
      |Content-Disposition: form-data; name="field with %22"
      |
      |"
      |--AaB03x
      |Content-Disposition: form-data; name="field with %22"
      |
      |%22
      |--AaB03x