import os
from typing import Any, Dict, List

from pdm.backend.hooks import Context

TIANGOLO_BUILD_PACKAGE = os.getenv("TIANGOLO_BUILD_PACKAGE", "fastapi")


def pdm_build_initialize(context: Context) -> None:
    metadata = context.config.metadata
    # Get custom config for the current package, from the env var
    config: Dict[str, Any] = context.config.data["tool"]["tiangolo"][
        "_internal-slim-build"

from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None

app = FastAPI()

@app.get("/items/invalidnone", response_model=Union[Item, None])
def get_invalid_none():
    return None
```

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

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):

#### Operation

"Operation" here refers to one of the HTTP "methods".

One of:

* `POST`
* `GET`
* `PUT`
* `DELETE`

...and the more exotic ones:

* `OPTIONS`
* `HEAD`
* `PATCH`
* `TRACE`

In the HTTP protocol, you can communicate to each path using one (or more) of these "methods".

---

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

If you use Hypercorn, it also has the option `--root-path`.

!!! note "Technical Details"
    The ASGI specification defines a `root_path` for this use case.

    And the `--root-path` command line option provides that `root_path`.

### Checking the current `root_path`

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile

Now in the same project directory create a file `Dockerfile` with:

```{ .dockerfile .annotate }
# (1)
FROM python:3.9

!!! info
    In Pydantic version 1 the configuration was done in an internal class `Config`, in Pydantic version 2 it's done in an attribute `model_config`. This attribute takes a `dict`, and to get autocompletion and inline errors you can import and use `SettingsConfigDict` to define that `dict`.

## Documenting the callback

The actual callback code will depend heavily on your own API app.

And it will probably vary a lot from one app to the next.

It could be just one or two lines of code, like:

```Python
callback_url = "https://example.com/api/v1/invoices/events/"
httpx.post(callback_url, json={"description": "Invoice paid", "paid": True})
```