# How To - Recipes { #how-to-recipes }

Here you will see different recipes or "how to" guides for **several topics**.

Most of these ideas would be more or less **independent**, and in most cases you should only need to study them if they apply directly to **your project**.

If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.

/// tip

   *     are processed in FIFO order; if {@code false} the access order is unspecified.
   * @param c the collection of elements to initially contain
   * @throws IllegalArgumentException if {@code capacity} is less than {@code c.size()}, or less
   *     than 1.
   * @throws NullPointerException if the specified collection or any of its elements are null
   */

   *
   * @param a the first unsigned {@code long} to compare
   * @param b the second unsigned {@code long} to compare
   * @return a negative value if {@code a} is less than {@code b}; a positive value if {@code a} is
   *     greater than {@code b}; or zero if they are equal
   */
  @SuppressWarnings("InlineMeInliner") // Integer.compare unavailable under GWT+J2CL

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### Allowed values for REDUCED_REDUNDANCY storage class

`REDUCED_REDUNDANCY` implies lesser parity than `STANDARD` class. So,`REDUCED_REDUNDANCY` parity drives should be

- Less than N/2, if `STANDARD` parity is not set.
- Less than `STANDARD` Parity, if it is set.

Default value for `REDUCED_REDUNDANCY` storage class is `1`.

## Get started with Storage Class

### Set storage class

   * world. Figure out what sort of space-time tradeoff we're actually going to get here with the
   * *Map variants. This class is particularly hard to benchmark, because the benefit is not only in
   * less allocation, but also having the GC do less work to scan the heap because of fewer
   * references, which is particularly hard to quantify.
   */

  /** Creates an empty {@code CompactHashMap} instance. */

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

/// note

`PATCH` is less commonly used and known than `PUT`.

And many teams use only `PUT`, even for partial updates.

You are **free** to use them however you want, **FastAPI** doesn't impose any restrictions.

But this guide shows you, more or less, how they are intended to be used.

///

Mas você não precisa memorizar o que cada um desses códigos significa.

Você pode usar as variáveis de conveniência de `fastapi.status`.

{* ../../docs_src/response_status_code/tutorial002_py310.py hl[1,6] *}

Eles são apenas uma conveniência, eles possuem o mesmo número, mas dessa forma você pode usar o preenchimento automático do editor para encontrá-los:

<img src="/img/tutorial/response-status-code/image02.png">

/// note | Detalhes Técnicos

* `write(data)`: Escribe `data` (`str` o `bytes`) en el archivo.
* `read(size)`: Lee `size` (`int`) bytes/caracteres del archivo.
* `seek(offset)`: Va a la posición de bytes `offset` (`int`) en el archivo.
    * Por ejemplo, `await myfile.seek(0)` iría al inicio del archivo.
    * Esto es especialmente útil si ejecutas `await myfile.read()` una vez y luego necesitas leer el contenido nuevamente.
* `close()`: Cierra el archivo.