The **server** program (for example **Uvicorn** via **FastAPI CLI**) is capable of interpreting these headers, and then passing that information to your application.

* Kullandığın geliştirme araçları ile iyi çalışır **<abbr title="Integrated Development Environment, kod editörüne benzer">IDE</abbr>/<abbr title="Code errorlarınızı inceleyen program">linter</abbr>/brain**:
    * Pydantic'in veri yapıları aslında sadece senin tanımladığın classlar; Bu yüzden doğrulanmış dataların ile otomatik tamamlama, linting ve mypy'ı kullanarak sorunsuz bir şekilde çalışabilirsin

    * Jeśli znasz adnotacje typów Pythona to wiesz jak używać Pydantic.
* Dobrze współpracuje z Twoim **<abbr title='Skrót od "Integrated Development Environment", podobne do edytora kodu'>IDE</abbr>/<abbr title="Program, który sprawdza Twój kod pod kątem błędów">linterem</abbr>/mózgiem**:

    * If you know Python types you know how to use Pydantic.
* Plays nicely with your **<abbr title="Integrated Development Environment, similar to a code editor">IDE</abbr>/<abbr title="A program that checks for code errors">linter</abbr>/brain**:
    * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.

* **🙅‍♂ 🔠**:
    * 🙅‍♂ 🆕 🔗 🔑 ◾-🇪🇸 💡.
    * 🚥 👆 💭 🐍 🆎 👆 💭 ❔ ⚙️ Pydantic.
* 🤾 🎆 ⏮️ 👆 **<abbr title="Integrated Development Environment, similar to a code editor">💾</abbr>/<abbr title="A program that checks for code errors">🧶</abbr>/🧠**:
    * ↩️ Pydantic 📊 📊 👐 🎓 👆 🔬; 🚘-🛠️, 🧽, ✍ &amp; 👆 🤔 🔜 🌐 👷 ☑ ⏮️ 👆 ✔ 💽.
* ✔ **🏗 📊**:
    * ⚙️ 🔗 Pydantic 🏷, 🐍 `typing`'Ⓜ `List` &amp; `Dict`, ♒️.

* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

For example, if you have a function:

```Python
@lru_cache
def say_hi(name: str, salutation: str = "Ms."):
    return f"Hello {salutation} {name}"
```

your program could execute like this:

```mermaid
sequenceDiagram

participant code as Code
participant function as say_hi()
participant execute as Execute function

    rect rgba(0, 255, 0, .1)

     * constructing a {@link java.util.Date} object (i.e. seconds since Epoch
     * 1970). Times should be the same as those reported using the properties
     * dialog of the Windows Explorer program.
     *
     * @return The number of milliseconds since the 00:00:00 GMT, January 1,
     *         1970 as a <code>long</code> value
     * @throws CIFSException if an error occurs accessing the resource
     */

```console
$ mkdocs serve --dev-addr 127.0.0.1:8008
```

///

#### Typer CLI (optional)

The instructions here show you how to use the script at `./scripts/docs.py` with the `python` program directly.

But you can also use <a href="https://typer.tiangolo.com/typer-cli/" class="external-link" target="_blank">Typer CLI</a>, and you will get autocompletion in your terminal for the commands after installing completion.

Most applications should call `new OkHttpClient()` exactly once, configure it with their cache, and use that same instance everywhere. Otherwise the two cache instances will stomp on each other, corrupt the response cache, and possibly crash your program.

Response caching uses HTTP headers for all configuration. You can add request headers like `Cache-Control: max-stale=3600` and OkHttp's cache will honor them. Your webserver configures how long responses are cached with its own response...