* **FastAPI**:
    * The same way that Starlette uses Uvicorn and cannot be faster than it, **FastAPI** uses Starlette, so it cannot be faster than it.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).

It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.

With it, you can use <a href="https://docs.pytest.org/" class="external-link" target="_blank">pytest</a> directly with **FastAPI**.

```Python hl_lines="8-13"
{!../../../docs_src/sql_databases/sql_app/tests/test_sql_app.py!}
```

!!! tip
    You could reduce duplication in that code by putting it in a function and using it from both `database.py` and `tests/test_sql_app.py`.

    For simplicity and to focus on the specific testing code, we are just copying it.

## Create the database

    # to support it as a first class "feature"
    assert is_bytes_sequence_annotation(Union[List[str], List[bytes]])


def test_is_uploadfile_sequence_annotation():
    # For coverage
    # TODO: in theory this would allow declaring types that could be lists of UploadFile
    # and other types, but I'm not even sure it's a good idea to support it as a first
    # class "feature"

# GraphQL

As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.

You can combine normal FastAPI *path operations* with GraphQL on the same application.

!!! tip
    **GraphQL** solves some very specific use cases.

    It has **advantages** and **disadvantages** when compared to common **web APIs**.

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.

So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation

## Details

The first `"/static"` refers to the sub-path this "sub-application" will be "mounted" on. So, any path that starts with `"/static"` will be handled by it.

The `directory="static"` refers to the name of the directory that contains your static files.

The `name="static"` gives it a name that can be used internally by **FastAPI**.

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```