passing a pointer to a field in a struct, the Go memory in question is
the memory occupied by the field, not the entire struct. When passing a
pointer to an element in an array or slice, the Go memory in question is
the entire array or the entire backing array of the slice.

C code may keep a copy of a Go pointer only as long as the memory it
points to is pinned.

C code may not keep a copy of a Go pointer after the call returns,

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


app = FastAPI()


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, q: str | None = None):
    result = {"item_id": item_id, **item.dict()}
    if q:
        result.update({"q": q})

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
    results = {"item_id": item_id, "item": item}

from typing import List, Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: List[str] = []


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

from typing import Set, Union

from fastapi import FastAPI, status
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: Set[str] = set()


@app.post("/items/", response_model=Item, status_code=status.HTTP_201_CREATED)
async def create_item(item: Item):

	readCloser  io.ReadCloser   // raw input
	buf         *bufio.Reader   // input to the splitter
	current     []jstream.KVS   // current block of results to be returned
	recordsRead int             // number of records read in current slice
	input       chan *queueItem // input for workers
	queue       chan *queueItem // output from workers in order
	err         error           // global error state, only touched by Reader.Read

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel


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


app = FastAPI()


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

 *
 * <p>This class should not be assumed to be universally superior to {@code java.util.HashSet}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Dimitris Andreou
 * @author Jon Noack
 */

	}
	return fmt.Sprintf("%s.%s", schema.ModelType.PkgPath(), schema.ModelType.Name())
}

func (schema Schema) MakeSlice() reflect.Value {
	slice := reflect.MakeSlice(reflect.SliceOf(reflect.PointerTo(schema.ModelType)), 0, 20)
	results := reflect.New(slice.Type())
	results.Elem().Set(slice)

	return results
}

func (schema Schema) LookUpField(name string) *Field {
	if field, ok := schema.FieldsByDBName[name]; ok {
		return field

from fastapi import Body, FastAPI
from pydantic import BaseModel
from typing_extensions import Annotated

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
    results = {"item_id": item_id, "item": item}