from fastapi import FastAPI
from fastapi.testclient import TestClient

app = FastAPI(swagger_ui_oauth2_redirect_url=None)


@app.get("/items/")
async def read_items():
    return {"id": "foo"}


client = TestClient(app)


def test_swagger_ui():
    response = client.get("/docs")
    assert response.status_code == 200, response.text
    assert response.headers["content-type"] == "text/html; charset=utf-8"

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",
    response_description="The created item",
)
async def create_item(item: Item):
    """

from typing import Annotated

from fastapi import Depends, FastAPI, HTTPException

app = FastAPI()


data = {
    "plumbus": {"description": "Freshly pickled plumbus", "owner": "Morty"},
    "portal-gun": {"description": "Gun to create portals", "owner": "Rick"},
}


class OwnerError(Exception):
    pass


def get_username():
    try:
        yield "Rick"
    except OwnerError as e:

        }
    }

    /**
     * Reloads the character mapping items from the provided input stream.
     * Parses mapping rules in the format: input1,input2,... => output
     *
     * @param updater the mapping updater to use for writing changes, or null for read-only reload
     * @param in the input stream to read the mapping data from
     */
    protected void reload(final MappingUpdater updater, final InputStream in) {

     */
    @IgnoreJRERequirement // Only programs that already have Instant will use this.
    operator fun set(name: String, value: Instant) = set(name, Date.from(value))

    /**
     * Add a field with the specified value without any validation. Only appropriate for headers
     * from the remote peer or cache.
     */
    internal fun addLenient(
      name: String,
      value: String,
    ) = commonAddLenient(name, value)

      configurations.findByName("friendsApi")?.let {
        friendPaths.from(it.incoming.artifactView { }.files)
      }
      configurations.findByName("friendsImplementation")?.let {
        friendPaths.from(it.incoming.artifactView { }.files)
      }
      configurations.findByName("friendsTestImplementation")?.let {
        friendPaths.from(it.incoming.artifactView { }.files)
      }
    }
}

#### Shared reader thread

///

## Import Pydantic's `BaseModel` { #import-pydantics-basemodel }

First, you need to import `BaseModel` from `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model { #create-your-data-model }

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

    }

    return empty
        ? new EmptyContiguousSet<C>(domain)
        : new RegularContiguousSet<C>(effectiveRange, domain);
  }

  /**
   * Returns a nonempty contiguous set containing all {@code int} values from {@code lower}
   * (inclusive) to {@code upper} (inclusive). (These are the same values contained in {@code
   * Range.closed(lower, upper)}.)
   *

processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing campaign, you might need to enrich the data with additional details, such as information from the customer loyalty database.

MinIO's Object Lambda, enables application developers to process data retrieved from MinIO before returning it to an application. You can register a Lambda Function target on MinIO, once successfully registered it can be used to transform the data for application GET requests...