</ul>
<p>
Some memory operations are <i>read-like</i>, including read, atomic read, mutex lock, and channel receive.
Other memory operations are <i>write-like</i>, including write, atomic write, mutex unlock, channel send, and channel close.
Some, such as atomic compare-and-swap, are both read-like and write-like.
</p>

<p>

# Help FastAPI - Get Help { #help-fastapi-get-help }

Do you like **FastAPI**?

Would you like to help FastAPI, other users, and the author?

Or would you like to get help with **FastAPI**?

There are very simple ways to help (several involve just one or two clicks).

And there are several ways to get help too.

## Subscribe to the newsletter { #subscribe-to-the-newsletter }

 *
 * @since 4.0.0
 */
@Experimental
public interface UpgradeOptions extends Options {
    /**
     * Returns the list of upgrade goals to be executed.
     * These goals can include operations like "check", "dependencies", "plugins", etc.
     *
     * @return an {@link Optional} containing the list of goals, or empty if not specified
     */
    @Nonnull
    Optional<List<String>> goals();

    /**

## Pydantic Models for Input and Output { #pydantic-models-for-input-and-output }

Let's say you have a Pydantic model with default values, like this one:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### Model for Input { #model-for-input }

If you use this model as an input like here:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

is not about just retrofitting monolithic applications onto modern container based compute environment. A cloud-native application is portable and resilient by design, and can scale horizontally by simply replicating. Modern orchestration platforms like Kubernetes, DC/OS make replicating and managing containers in huge clusters easier than ever.

While containers provide isolated application execution environment, orchestration platforms allow seamless scaling by helping replicate and manage...

/// tip

Integrating other authentication/authorization providers like Google, Facebook, X (Twitter), GitHub, etc. is also possible and relatively easy.

The most complex problem is building an authentication/authorization provider like those, but **FastAPI** gives you the tools to do it easily, while doing the heavy lifting for you.

///

- Do not add trailing punctuation to headings.

### Quotes and punctuation

- Keep punctuation style consistent with existing Traditional Chinese docs (they often mix English terms like “FastAPI” with Chinese text).
- Never change punctuation inside inline code, code blocks, URLs, or file paths.

* They are not synced with the code to reflect the eventual solution that is committed
* Google Docs is not a "code-oriented" tool, like Markdown can be
* Review in Google Docs is not as simple as a PR code review in GitHub

## Decision

The *Build Tool Team* has decided to use Architectural Decision Records (aka ADR) to track decisions we want to follow.

 * Open the Named Pipe foo for reading and writing. The pipe will behave like the <code>CallNamedPipe</code> interface.
 * </td></tr>
 * <tr><td ><pre>
 * new SmbNamedPipe( "smb1://server/IPC$/foo",
 *         SmbNamedPipe.PIPE_TYPE_RDWR |
 *         SmbNamedPipe.PIPE_TYPE_TRANSACT );
 * </pre></td><td>
 * Open the Named Pipe foo for reading and writing. The pipe will behave like the <code>TransactNamedPipe</code> interface.
 * </td></tr>

		t.Fatalf("got error: %v", err)
	}

	if len(users) != 4 {
		t.Errorf("Four users should be found, instead found %d", len(users))
	}

	DB.Select("*").Where("name LIKE ?", "subquery%").Where("age >= (?)", DB.
		Select("AVG(age)").Table("users").Where("name LIKE ?", "subquery%")).Find(&users)