# i uzyskaj wsparcie edytora wewnątrz funkcji
def main(user_id: str):
    return user_id


# Model Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

A one będą mogły zostać później użyte w następujący sposób:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",

# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

که سپس میتوان به این شکل از آن استفاده کرد:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

⤴️ 👆 💪 🚮 🎏 ✔ 📄 🔠 👫 ⏮️ 🔗 & 🎧-🔗:

```mermaid
graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

You could still use most of the features in **FastAPI** with the knowledge from the main [Tutorial - User Guide](../tutorial/index.md){.internal-link target=_blank}.

And the next sections assume you already read it, and assume that you know those main ideas.

## External Courses

    ```

#### `**user_dict`에 대해

`UserInDB(**user_dict)`는 다음을 의미한다:

*`user_dict`의 키와 값을 다음과 같은 키-값 인수로 직접 전달합니다:*

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

!!! 정보

from pydantic import BaseModel

# 변수를 str로 선언
# 그 후 함수 안에서 편집기 지원을 받으세요
def main(user_id: str):
    return user_id


# Pydantic 모델
class User(BaseModel):
    id: int
    name: str
    joined: date
```

위의 코드는 다음과 같이 사용될 수 있습니다:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

Chroot allows user based namespace isolation on many standard Linux deployments.

## 1. Prerequisites

- Familiarity with [chroot](http://man7.org/linux/man-pages/man2/chroot.2.html)
- Chroot installed on your machine.

## 2. Install MinIO in Chroot

```sh
mkdir -p /mnt/export/${USER}/bin
wget https://dl.min.io/server/minio/release/linux-amd64/minio -O /mnt/export/${USER}/bin/minio

- Click on `Login with SSO`
- User will be redirected to the Keycloak user login page, upon successful login the user will be redirected to MinIO page and logged in automatically,
  the user should see now the buckets and objects they have access to.

## Explore Further

- [MinIO STS Quickstart Guide](https://min.io/docs/minio/linux/developers/security-token-service.html)

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

그 다음 각각에 대해 그저 의존성과 하위 의존성을 사용하여 다른 권한 요구 사항을 추가할 수 있을 겁니다:

```mermaid
graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

# et profitez de l'aide de votre IDE dans cette fonction
def main(user_id: str):
    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```
Qui peuvent ensuite être utilisés comme cela:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}