* `close()`: 🔐 📁.

🌐 👫 👩‍🔬 `async` 👩‍🔬, 👆 💪 "⌛" 👫.

🖼, 🔘 `async` *➡ 🛠️ 🔢* 👆 💪 🤚 🎚 ⏮️:

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

🚥 👆 🔘 😐 `def` *➡ 🛠️ 🔢*, 👆 💪 🔐 `UploadFile.file` 🔗, 🖼:

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

!!! note "`async` 📡 ℹ"
    🕐❔ 👆 ⚙️ `async` 👩‍🔬, **FastAPI** 🏃 📁 👩‍🔬 🧵 & ⌛ 👫.

!!! note "💃 📡 ℹ"

)
```

Or more exactly, using `user_dict` directly, with whatever contents it might have in the future:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### A Pydantic model from the contents of another

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.

Let's say you only have a single `item` body parameter from a Pydantic model `Item`.

By default, **FastAPI** will then expect its body directly.

But if you want it to expect a JSON with a key `item` and inside of it the model contents, as it does when you declare extra body parameters, you can use the special `Body` parameter `embed`:

```Python
item: Item = Body(embed=True)
```

as in:

=== "Python 3.10+"