* <strong>Performance</strong>).
 *
 * <p><strong>Cycle Detection</strong>
 *
 * <p>Deadlocks can arise when locks are acquired in an order that forms a cycle. In a simple
 * example involving two locks and two threads, deadlock occurs when one thread acquires Lock A, and
 * then Lock B, while another thread acquires Lock B, and then Lock A:
 *
 * <pre>

-sm .select2-container--default .select2-selection--single,select.form-control-sm~.select2-container--default .select2-selection--single{height:calc(1.8125rem + 2px)}.text-sm .select2-container--default .select2-selection--single .select2-selection__rendered,select.form-control-sm~.select2-container--default .select2-selection--single .select2-selection__rendered{margin-top:-.4rem}.text-sm .select2-container--default .select2-selection--single .select2-selection__arrow,select.form-control-sm~.se...

$ python main.py

I solemnly swear 🐺
```

</div>

## Alternativas { #alternatives }

Esta es una guía simple para comenzar y enseñarte cómo funciona todo **por debajo**.

Hay muchas **alternativas** para gestionar entornos virtuales, dependencias de paquetes (requisitos), proyectos.

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

.select2-container--default {\n  font-size: 75%;\n}\n\n.text-sm .select2-container--default .select2-selection--single,\nselect.form-control-sm ~ .select2-container--default .select2-selection--single {\n  height: calc(1.8125rem + 2px);\n}\n\n.text-sm .select2-container--default .select2-selection--single .select2-selection__rendered,\nselect.form-control-sm ~ .select2-container--default .select2-selection--single .select2-selection__rendered {\n  margin-top: -.4rem;\n}\n\n.text-sm .select2-container--default ...

    checkArgument(is6to4Address(ip), "Address '%s' is not a 6to4 address.", toAddrString(ip));

    return getInet4Address(Arrays.copyOfRange(ip.getAddress(), 2, 6));
  }

  /**
   * A simple immutable data class to encapsulate the information to be found in a Teredo address.
   *
   * <p>All of the fields in this class are encoded in various portions of the IPv6 address as part

Pero también puedes explotar los beneficios del paralelismo y la multiprocesamiento (tener múltiples procesos ejecutándose en paralelo) para cargas de trabajo **CPU bound** como las de los sistemas de Machine Learning.

Eso, más el simple hecho de que Python es el lenguaje principal para **Data Science**, Machine Learning y especialmente Deep Learning, hacen de FastAPI una muy buena opción para APIs web de Data Science / Machine Learning y aplicaciones (entre muchas otras).

as in <code>'x'</code> or <code>'\n'</code>.
Within the quotes, any character may appear except newline and unescaped single
quote. A single quoted character represents the Unicode value
of the character itself,
while multi-character sequences beginning with a backslash encode
values in various formats.
</p>

<p>

   * serialized with XML 1.0.
   *
   * <p>For SOAP 1.1 messages, see {@code XML_UTF_8} per <a
   * href="http://www.w3.org/TR/2000/NOTE-SOAP-20000508/">W3C Note on Simple Object Access Protocol
   * (SOAP) 1.1</a>
   *
   * @since 20.0
   */
  public static final MediaType SOAP_XML_UTF_8 = createConstantUtf8(APPLICATION_TYPE, "soap+xml");

        * [Microservice in Python using FastAPI](https://dev.to/paurakhsharma/microservice-in-python-using-fastapi-24cc)  by [Paurakh Sharma Humagain](https://x.com/PaurakhSharma).
        * [Build simple API service with Python FastAPI — Part 1](https://dev.to/cuongld2/build-simple-api-service-with-python-fastapi-part-1-581o) by [cuongld2](https://dev.to/cuongld2).