* Werkt goed samen met je **<abbr title=“Integrated Development Environment, vergelijkbaar met een code editor”>IDE</abbr>/<abbr title=“Een programma dat controleert op fouten in de code”>linter</abbr>/hersenen**:
    * Doordat pydantic's datastructuren enkel instanties zijn van klassen, die je definieert, werkt automatische aanvulling, linting, mypy en je intuïtie allemaal goed met je gevalideerde data.

    * Nếu bạn biết kiểu dữ liệu Python, bạn biết cách sử dụng Pydantic.
* Sử dụng tốt với **<abbr title="Môi trường phát triển tích hợp, tương tự như một trình soạn thảo code">IDE</abbr>/<abbr title="Một chương trình kiểm tra code lỗi">linter</abbr>/não của bạn**:

    * Bởi vì các cấu trúc dữ liệu của Pydantic chỉ là các instances của class bạn định nghĩa; auto-completion, linting, mypy và trực giác của bạn nên làm việc riêng biệt với những dữ liệu mà bạn đã validate.

Ahora usamos `response_model=HeroPublic` en lugar de la **anotación de tipo de retorno** `-> HeroPublic` porque el valor que estamos devolviendo en realidad *no* es un `HeroPublic`.

Si hubiéramos declarado `-> HeroPublic`, tu editor y linter se quejarían (con razón) de que estás devolviendo un `Hero` en lugar de un `HeroPublic`.

* **更簡單**：
    * 不需要學習新的 micro-language 來定義結構。
    * 如果你知道 Python 型別，你就知道如何使用 Pydantic。
* 和你的 **<abbr title="Integrated Development Environment，和程式碼編輯器類似">IDE</abbr>/<abbr title="一個檢查程式碼錯誤的工具">linter</abbr>/brain** 都能好好配合：
    * 因為 Pydantic 的資料結構其實就是你自己定義的類別實例，所以自動補齊、linting、mypy 以及你的直覺都能很好地在經過驗證的資料上發揮作用。
* 驗證**複雜結構**：
    * 使用 Pydantic 模型時，你可以把資料結構分層設計，並且用 Python 的 `List` 和 `Dict` 等型別來定義。

Now we use `response_model=HeroPublic` instead of the **return type annotation** `-> HeroPublic` because the value that we are returning is actually *not* a `HeroPublic`.

If we had declared `-> HeroPublic`, your editor and linter would complain (rightfully so) that you are returning a `Hero` instead of a `HeroPublic`.

name: Linters and Tests

on:
  pull_request:
    branches:
      - master

# This ensures that previous jobs for the PR are canceled when the PR is
# updated.
concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref }}
  cancel-in-progress: true

permissions:
  contents: read

jobs:
  build:
    name: Go ${{ matrix.go-version }} on ${{ matrix.os }}
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:

lint: getdeps ## runs golangci-lint suite of linters
	@echo "Running $@ check"
	@$(GOLANGCI) run --build-tags kqueue --timeout=10m --config ./.golangci.yml
	@command typos && typos ./ || echo "typos binary is not found.. skipping.."

lint-fix: getdeps ## runs golangci-lint suite of linters with automatic fixes
	@echo "Running $@ check"

     */
    PERSISTENT,

    /**
     * Data should be retained for the duration of the current Maven session.
     * Suitable for:
     * - Build-wide configuration
     * - Project model caching
     * - Inter-module metadata
     */
    SESSION_SCOPED,

    /**
     * Data should only be retained for the current build request.
     * Suitable for:
     * - Plugin execution results
     * - Temporary build artifacts

## Performanz

Unabhängige TechEmpower-Benchmarks zeigen **FastAPI**-Anwendungen, die unter Uvicorn laufen, als <a href="https://www.techempower.com/benchmarks/#section=test&runid=7464e520-0dc2-473d-bd34-dbdfd7e85911&hw=ph&test=query&l=zijzen-7" class="external-link" target="_blank">eines der schnellsten verfügbaren Python-Frameworks</a>, nur noch hinter Starlette und Uvicorn selbst (intern von FastAPI verwendet).

			return
		}
	}

	rulesMap := event.NewRulesMap(eventNames, pattern, event.TargetID{ID: mustGetUUID()})

	setEventStreamHeaders(w)

	// Listen Publisher and peer-listen-client uses nonblocking send and hence does not wait for slow receivers.
	// Use buffered channel to take care of burst sends or slow w.Write()