In GitHub, the template will guide you to write the right question so that you can more easily get a good answer, or even solve the problem yourself even before asking. And in GitHub I can make sure I always answer everything, even if it takes some time. I can't personally do that with the chat systems. 😅

    * Check that it has an optional attribute `is_offer`, that should be a `bool`, if present.
    * All this would also work for deeply nested JSON objects.
* Convert from and to JSON automatically.
* Document everything with OpenAPI, that can be used by:
    * Interactive documentation systems.
    * Automatic client code generation systems, for many languages.
* Provide 2 interactive documentation web interfaces directly.

---

But even if you never use **FastAPI**, you would benefit from learning a bit about them.

/// note

If you are a Python expert, and you already know everything about type hints, skip to the next chapter.

///

## Motivation { #motivation }

Let's start with a simple example:

{* ../../docs_src/python_types/tutorial001.py *}

Calling this program outputs:

          // caught and forwarded to the service the task would stop executing but the service would
          // have no idea.
          // TODO(lukes): consider building everything in terms of ListenableScheduledFuture then
          // the AbstractService could monitor the future directly. Rescheduling is still hard...
          // but it would help with some of these lock ordering issues.

///

### <a href="https://github.com/encode/apistar" class="external-link" target="_blank">APIStar</a> (<= 0.5) { #apistar-0-5 }

Right before deciding to build **FastAPI** I found **APIStar** server. It had almost everything I was looking for and had a great design.

Concurrency is different than parallelism. And it is better on **specific** scenarios that involve a lot of waiting. Because of that, it generally is a lot better than parallelism for web application development. But not for everything.

So, to balance that out, imagine the following short story:

> You have to clean a big, dirty house.

*Yep, that's the whole story*.

---

	partial func(entries metaCacheEntries, errs []error)

	// finished will be called when all streams have finished and
	// more than one disk returned an error.
	// Will not be called if everything operates as expected.
	finished func(errs []error)
}

// listPathRaw will list a path on the provided drives.
// See listPathRawOptions on how results are delivered.
// Directories are always returned.

          // caught and forwarded to the service the task would stop executing but the service would
          // have no idea.
          // TODO(lukes): consider building everything in terms of ListenableScheduledFuture then
          // the AbstractService could monitor the future directly. Rescheduling is still hard...
          // but it would help with some of these lock ordering issues.

    * Check that it has an optional attribute `is_offer`, that should be a `bool`, if present.
    * All this would also work for deeply nested JSON objects.
* Convert from and to JSON automatically.
* Document everything with OpenAPI, that can be used by:
    * Interactive documentation systems.
    * Automatic client code generation systems, for many languages.
* Provide 2 interactive documentation web interfaces directly.

---

  /** http://tools.ietf.org/html/draft-ietf-httpbis-http2-17#section-5.1.1 */
  internal var nextStreamId = if (builder.client) 3 else 2

  private var isShutdown = false

  /** For scheduling everything asynchronous. */
  private val taskRunner = builder.taskRunner

  /** Asynchronously writes frames to the outgoing socket. */
  private val writerQueue = taskRunner.newQueue()