You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# 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
```

That can then be used like:

```Python

Você escreve Python padrão com tipos:

```Python
from datetime import date

from pydantic import BaseModel

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Que então pode ser usado como:

```Python

Y luego también puedes tener un path `/users/{user_id}` para obtener datos sobre un usuario específico por algún ID de usuario.

Debido a que las *path operations* se evalúan en orden, necesitas asegurarte de que el path para `/users/me` se declara antes que el de `/users/{user_id}`:

{* ../../docs_src/path_params/tutorial003_py310.py hl[6,11] *}

And then you can also have a path `/users/{user_id}` to get data about a specific user by some user ID.

Because *path operations* are evaluated in order, you need to make sure that the path for `/users/me` is declared before the one for `/users/{user_id}`:

{* ../../docs_src/path_params/tutorial003_py310.py hl[6,11] *}

    }

    @ParameterizedTest
    @DisplayName("Test valid usernames")
    @ValueSource(strings = { "user", "user123", "user.name", "user-name", "user_name", "******@****.***" })
    void testValidUsernames(String username) {
        assertDoesNotThrow(() -> InputValidator.validateUsername(username));
    }

    @ParameterizedTest
    @DisplayName("Test invalid usernames")
    @ValueSource(strings = { "user name", // space

	for index := range users {
		g.Go(func() error {
			userName := strings.TrimSuffix(users[index], ".json")
			userMP, err := iamOS.loadMappedPolicyInternal(ctx, userName, userType, isGroup)
			if err != nil && !errors.Is(err, errNoSuchPolicy) {
				return fmt.Errorf("unable to load the user policy map `%s`: %w", userName, err)
			}
			mappedPolicies[index] = userMP
			return nil
		}, index)
	}

型を使った標準的な Python を記述します:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# 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
```

これは次のように使えます:

```Python

                // Invalid value ignored
            }
        }

        // RDMA Configuration
        value = props.getProperty("jcifs.smb.client.useRDMA");
        if (value != null) {
            this.useRDMA = Boolean.parseBoolean(value);
        }

        value = props.getProperty("jcifs.smb.client.rdmaProvider");
        if (value != null) {
            this.rdmaProvider = value;

  PATH_SEPARATOR("path.separator"),

  /** Line separator ("\n" on UNIX). */
  LINE_SEPARATOR("line.separator"),

  /** User's account name. */
  USER_NAME("user.name"),

  /** User's home directory. */
  USER_HOME("user.home"),

  /** User's current working directory. */
  USER_DIR("user.dir");

  private final String key;

  StandardSystemProperty(String key) {

For example, let's say you have 4 API endpoints (*path operations*):

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

then you could add different permission requirements for each of them just with dependencies and sub-dependencies:

```mermaid
graph TB

current_user(["current_user"])