* Then check that the tests **pass** after the PR. ✅

* Many PRs don't have tests, you can **remind** them to add tests, or you can even **suggest** some tests yourself. That's one of the things that consume most time and you can help a lot with that.

* Then also comment what you tried, that way I'll know that you checked it. 🤓

## Create a Pull Request

    ```

The last `CommonQueryParams`, in:

```Python
... Depends(CommonQueryParams)
```

...is what **FastAPI** will actually use to know what is the dependency.

From it is that FastAPI will extract the declared parameters and that is what FastAPI will actually call.

---

In this case, the first `CommonQueryParams`, in:

=== "Python 3.8+"

    ```Python

This decoupling of parts, and being a "microframework" that could be extended to cover exactly what is needed was a key feature that I wanted to keep.

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

!!! check "Inspired **FastAPI** to"

      description: Tell us what happens
    validations:
      required: true
  - type: textarea
    id: expected-behavior
    attributes:
      label: Expected Behavior
      description: Tell us what should happen
    validations:
      required: true
  - type: textarea
    id: context
    attributes:
      label: Context (optional)
      description: |
        How has this issue affected you? What are you trying to accomplish?

This can be very useful for setting up **resources** that you need to use for the whole app, and that are **shared** among requests, and/or that you need to **clean up** afterwards. For example, a database connection pool, or loading a shared machine learning model.

## Use Case

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

For any non-trivial change, we need to be able to answer these questions:

* Why is this change done? What's the use case?
* For user facing features, what will the API look like?
* What test cases should it have? What could go wrong?
* How will it roughly be implemented? We'll happily provide code pointers to save you time.

## Containers and Processes

A **container image** normally includes in its metadata the default program or command that should be run when the **container** is started and the parameters to be passed to that program. Very similar to what would be if it was in the command line.

When a **container** is started, it will run that command/program (although you can override it and make it run a different command/program).

    // Verify the peer received what was expected.
    assertThat(peer.takeFrame().type).isEqualTo(Http2.TYPE_HEADERS)
    assertThat(peer.takeFrame().type).isEqualTo(Http2.TYPE_RST_STREAM)
  }

  /**
   * Confirm that the client times out if the server stalls after 3 bytes. After the timeout the
   * connection is still considered healthy while we await the degraded pong. When that doesn't

You could create an API with a *path operation* that could trigger a request to an *external API* created by someone else (probably the same developer that would be *using* your API).

The process that happens when your API app calls the *external API* is named a "callback". Because the software that the external developer wrote sends a request to your API and then your API *calls back*, sending a request to an *external API* (that was probably created by the same developer).

#### JVM platform

This is a platform that builds on the core and software platforms to add support for developing software that runs on the JVM.
This includes software that is implemented using Java, Kotlin or some other JVM language.

This platform provides specific support for Java, Groovy and Scala, and includes the foojay toolchain plugin. 

#### Extensibility platform