* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")
* tip: Consejo (do not translate to "tip")

    assertThat(reader.readLine()).isEqualTo("hello world")
    val request = server.takeRequest()
    assertThat(request.requestLine).isEqualTo(
      "GET /a/deep/path?key=foo%20bar HTTP/1.1",
    )
    assertThat(request.path).isEqualTo("/a/deep/path?key=foo%20bar")
    val requestUrl = request.requestUrl
    assertThat(requestUrl!!.scheme).isEqualTo("http")
    assertThat(requestUrl.host).isEqualTo(server.hostName)

    /**
     * Path or URL to be crawled by this configuration.
     */
    @Required
    @Size(max = 1000)
    public String crawlingConfigPath;

    /**
     * Maximum depth for crawling (how many levels deep to follow links).
     */
    @Min(value = 0)
    @Max(value = 2147483647)
    @ValidateTypeFailure
    public Integer depth;

    /**
     * Maximum number of pages/documents to access during crawling.
     */

///

/// tip | Tips

"AlxexNet", "ResNet", dan "LeNet" adalah nama <abbr title="Secara teknis, arsitektur model Deep Learning">model</abbr> *Machine Learning*.

///

### Mendeklarasikan *parameter path*

Kemudian buat *parameter path* dengan tipe anotasi menggunakan *class* enum dari (`ModelName`)

        assertFalse(a.equals("not a blob"), "equals(other type) should be false");
    }

    // Ensures clone() returns a deep copy; mutations are independent across instances
    @Test
    @DisplayName("clone: returns deep copy and independent state")
    void clone_returnsDeepCopy() {
        // Arrange
        byte[] data = new byte[] { 10, 20, 30 };

///

/// tip | Tipp

Falls Sie sich fragen, was „AlexNet“, „ResNet“ und „LeNet“ ist, das sind Namen von <abbr title="Genau genommen, Deep-Learning-Modellarchitekturen">Modellen</abbr> für maschinelles Lernen.

///

### Deklarieren Sie einen *Pfad-Parameter*

///

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

///

/// tip | Consejo

Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.

///

### Declarar un *path parameter*

Luego crea un *path parameter* con una anotación de tipo usando la clase enum que creaste (`ModelName`):

    assertThat(request.requestLine).isEqualTo(
      "GET /a/deep/path?key=foo%20bar HTTP/1.1",
    )
    val requestUrl = request.url
    assertThat(requestUrl.scheme).isEqualTo("http")
    assertThat(requestUrl.host).isEqualTo(server.hostName)
    assertThat(requestUrl.port).isEqualTo(server.port)
    assertThat(requestUrl.encodedPath).isEqualTo("/a/deep/path")
    assertThat(requestUrl.queryParameter("key")).isEqualTo("foo bar")

# Sub-dependencies { #sub-dependencies }

You can create dependencies that have **sub-dependencies**.

They can be as **deep** as you need them to be.

**FastAPI** will take care of solving them.

## First dependency "dependable" { #first-dependency-dependable }

You could create a first dependency ("dependable") like:

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[8:9] *}