* its runtime check.
   *
   * <p>An example use case for this method is in implementing an {@code Iterator<T>} whose {@code
   * next} field is lazily initialized. The type of that field would be {@code @Nullable T}, and the
   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a

   * its runtime check.
   *
   * <p>An example use case for this method is in implementing an {@code Iterator<T>} whose {@code
   * next} field is lazily initialized. The type of that field would be {@code @Nullable T}, and the
   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a

        )


class OAuth2(SecurityBase):
    """
    This is the base class for OAuth2 authentication, an instance of it would be used
    as a dependency. All other OAuth2 classes inherit from it and customize it for
    each OAuth2 flow.

    You normally would not create a new class inheriting from it but use one of the
    existing subclasses, and maybe compose them if you want to support multiple flows.

{* ../../docs_src/openapi_webhooks/tutorial001_py310.py hl[9:12,15:20] *}

The webhooks that you define will end up in the **OpenAPI** schema and the automatic **docs UI**.

/// info

The `app.webhooks` object is actually just an `APIRouter`, the same type you would use when structuring your app with multiple files.

But every time we do:

```Python
Settings()
```

a new `Settings` object would be created, and at creation it would read the `.env` file again.

If the dependency function was just like:

```Python
def get_settings():
    return Settings()
```

we would create that object for each request, and we would be reading the `.env` file for each request. ⚠️

```python
from main import app
```

If your code was structured like:

```
.
├── backend
│   ├── main.py
│   ├── __init__.py
```

Then you would set the `entrypoint` as:

```toml
[tool.fastapi]
entrypoint = "backend.main:app"
```

which would be equivalent to:

```python
from backend.main import app
```

### `fastapi dev` with path { #fastapi-dev-with-path }

For example, you could want to **return a dictionary** or a database object, but **declare it as a Pydantic model**. This way the Pydantic model would do all the data documentation, validation, etc. for the object that you returned (e.g. a dictionary or database object).

#### A "professional" attack { #a-professional-attack }

Of course, the attackers would not try all this by hand, they would write a program to do it, possibly with thousands or millions of tests per second. And they would get just one extra correct letter at a time.

But doing that, in some minutes or hours the attackers would have guessed the correct username and password, with the "help" of our application, just using the time taken to answer.

To work with FastAPI you need to install [Python](https://www.python.org/).

After that, you would need to **install** FastAPI and any other **packages** you want to use.

To install packages you would normally use the `pip` command that comes with Python (or similar alternatives).

Nevertheless, if you just use `pip` directly, the packages would be installed in your **global Python environment** (the global installation of Python).

/// note

A path parameter is always required as it has to be part of the path. Even if you declared it with `None` or set a default value, it would not affect anything, it would still be always required.

///

## Order the parameters as you need { #order-the-parameters-as-you-need }

/// tip

This is probably not as important or necessary if you use `Annotated`.

///