if not settings.github_event_path.is_file():
        raise RuntimeError(
            f"No github event file available at: {settings.github_event_path}"
        )
    contents = settings.github_event_path.read_text()
    github_event = PartialGitHubEvent.parse_raw(contents)

    # Avoid race conditions with multiple labels
    sleep_time = random.random() * 10  # random number between 0 and 10 seconds
    logging.info(

Zum Beispiel können Sie innerhalb einer `async` *Pfadoperation-Funktion* den Inhalt wie folgt auslesen:

```Python
contents = await myfile.read()
```

Wenn Sie sich innerhalb einer normalen `def`-*Pfadoperation-Funktion* befinden, können Sie direkt auf `UploadFile.file` zugreifen, zum Beispiel:

```Python
contents = myfile.file.read()
```

!!! note "Technische Details zu `async`"

But you can also declare the `Response` that you want to be used, in the *path operation decorator*.

The contents that you return from your *path operation function* will be put inside of that `Response`.

```yaml
INHERIT: ../en/mkdocs.yml
```

!!! tip
    You could also simply create that file with those contents manually.

That command also created a dummy file `docs/ht/index.md` for the main page, you can start by translating that one.

You can continue with the previous instructions for an "Existing Language" for that process.

In contrast to a "**container image**" that is the stored static contents, a "**container**" normally refers to the running instance, the thing that is being **executed**.

```
John Doe
```

The function does the following:

* Takes a `first_name` and `last_name`.
* Converts the first letter of each one to upper case with `title()`.
* <abbr title="Puts them together, as one. With the contents of one after the other.">Concatenates</abbr> them with a space in the middle.

```Python hl_lines="2"
{!../../../docs_src/python_types/tutorial001.py!}
```

### Edit it

It's a very simple program.

### Memory per Process

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

Underneath, the `open("./somefile.txt")` creates an object that is called a "Context Manager".

When the `with` block finishes, it makes sure to close the file, even if there were exceptions.

Например, внутри `async` *функции операции пути* можно получить содержимое с помощью:

```Python
contents = await myfile.read()
```

Если вы находитесь внутри обычной `def` *функции операции пути*, можно получить прямой доступ к файлу `UploadFile.file`, например:

```Python
contents = myfile.file.read()
```

!!! note "Технические детали `async`"

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

Im Hintergrund erstellt das `open("./somefile.txt")` ein Objekt, das als „Kontextmanager“ bezeichnet wird.