Class swarmauri_base.loggers.LoggerBase.LoggerBase

swarmauri_base.loggers.LoggerBase.LoggerBase

Bases: ILogger, ObserveBase

LoggerBase is an implementation of ILogger that wraps Python's built-in logging module.

It compiles a logger with a specified name and attaches either user-provided or default handlers.

name class-attribute instance-attribute

name = __name__

handlers class-attribute instance-attribute

handlers = []

default_level class-attribute instance-attribute

default_level = INFO

default_format class-attribute instance-attribute

default_format = '[%(name)s][%(levelname)s] %(message)s'

logger class-attribute instance-attribute

logger = Field(exclude=True, default=None)

type class-attribute instance-attribute

type = 'ObserveBase'

model_config class-attribute instance-attribute

model_config = ConfigDict(arbitrary_types_allowed=True)

id class-attribute instance-attribute

id = Field(default_factory=generate_id)

members class-attribute instance-attribute

members = None

owners class-attribute instance-attribute

owners = None

host class-attribute instance-attribute

host = None

version class-attribute instance-attribute

version = '0.1.0'

model_post_init

model_post_init(*args, **kwargs)

Initialize the LoggerBase instance.

This method initializes the logger by compiling a logging.Logger instance with the configured name and handlers.

Parameters

args : any Positional arguments. *kwargs : any Keyword arguments.

Source code in swarmauri_base/loggers/LoggerBase.py

def model_post_init(self, *args, **kwargs):
    """Initialize the LoggerBase instance.

    This method initializes the logger by compiling a logging.Logger instance with the configured name and handlers.

    Parameters
    ----------
    *args : any
        Positional arguments.
    **kwargs : any
        Keyword arguments.
    """
    self.logger = self.compile_logger(logger_name=self.name)

compile_logger

compile_logger(logger_name=__name__)

Source code in swarmauri_base/loggers/LoggerBase.py

def compile_logger(self, logger_name: str = __name__) -> logging.Logger:
    logger = logging.getLogger(logger_name)
    logger.setLevel(self.default_level)

    # Clear existing handlers to avoid stale configurations
    logger.handlers.clear()

    if self.handlers:
        for handler_model in self.handlers:
            handler = handler_model.compile_handler()
            handler.setLevel(self.default_level)
            logger.addHandler(handler)
    else:
        default_handler = logging.StreamHandler()
        default_handler.setLevel(self.default_level)
        default_handler.setFormatter(logging.Formatter(self.default_format))
        logger.addHandler(default_handler)

    logger.propagate = False
    return logger

set_level

set_level(level=20)

Source code in swarmauri_base/loggers/LoggerBase.py

def set_level(self, level: int = 20) -> None:
    self.default_level = level
    self.compile_logger(logger_name=self.name)

set_format

set_format(
    format_string="[%(name)s][%(levelname)s] %(message)s",
)

Source code in swarmauri_base/loggers/LoggerBase.py

def set_format(
    self, format_string: str = "[%(name)s][%(levelname)s] %(message)s"
) -> None:
    self.default_format = format_string
    self.compile_logger(logger_name=self.name)

debug

debug(*args, **kwargs)

Log a debug message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def debug(self, *args, **kwargs) -> None:
    """Log a debug message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.debug(*args, **kwargs)

info

info(*args, **kwargs)

Log an info message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def info(self, *args, **kwargs) -> None:
    """Log an info message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.info(*args, **kwargs)

warning

warning(*args, **kwargs)

Log a warning message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def warning(self, *args, **kwargs) -> None:
    """Log a warning message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.warning(*args, **kwargs)

error

error(*args, **kwargs)

Log an error message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def error(self, *args, **kwargs) -> None:
    """Log an error message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.error(*args, **kwargs)

critical

critical(*args, **kwargs)

Log a critical message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def critical(self, *args, **kwargs) -> None:
    """Log a critical message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.critical(*args, **kwargs)

exception

exception(*args, **kwargs)

Log an exception traceback along with an error message.

Parameters

args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def exception(self, *args, **kwargs) -> None:
    """Log an exception traceback along with an error message.

    Parameters
    ----------
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.exception(*args, **kwargs)

log

log(level, *args, **kwargs)

Log a message with a custom numeric level.

Parameters

level : int The numeric logging level. args : any Positional arguments for the log message. *kwargs : any Keyword arguments for the log message.

Source code in swarmauri_base/loggers/LoggerBase.py

def log(self, level: int, *args, **kwargs) -> None:
    """Log a message with a custom numeric level.

    Parameters
    ----------
    level : int
        The numeric logging level.
    *args : any
        Positional arguments for the log message.
    **kwargs : any
        Keyword arguments for the log message.
    """
    self.logger.log(level, *args, **kwargs)

register_model classmethod

register_model()

Decorator to register a base model in the unified registry.

RETURNS	DESCRIPTION
Callable	A decorator function that registers the model class. TYPE: Callable[[Type[BaseModel]], Type[BaseModel]]

Source code in swarmauri_base/DynamicBase.py

@classmethod
def register_model(cls) -> Callable[[Type[BaseModel]], Type[BaseModel]]:
    """
    Decorator to register a base model in the unified registry.

    Returns:
        Callable: A decorator function that registers the model class.
    """

    def decorator(model_cls: Type[BaseModel]):
        """Register ``model_cls`` as a base model."""
        model_name = model_cls.__name__
        if model_name in cls._registry:
            glogger.warning(
                "Model '%s' is already registered; skipping duplicate.", model_name
            )
            return model_cls

        cls._registry[model_name] = {"model_cls": model_cls, "subtypes": {}}
        glogger.debug("Registered base model '%s'.", model_name)
        DynamicBase._recreate_models()
        return model_cls

    return decorator

register_type classmethod

register_type(resource_type=None, type_name=None)

Decorator to register a subtype under one or more base models in the unified registry.

PARAMETER	DESCRIPTION
resource_type	The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase) are used. TYPE: Optional[Union[Type[T], List[Type[T]]]] DEFAULT: None
type_name	An optional custom type name for the subtype. TYPE: Optional[str] DEFAULT: None

RETURNS	DESCRIPTION
Callable	A decorator function that registers the subtype. TYPE: Callable[[Type[DynamicBase]], Type[DynamicBase]]

Source code in swarmauri_base/DynamicBase.py

@classmethod
def register_type(
    cls,
    resource_type: Optional[Union[Type[T], List[Type[T]]]] = None,
    type_name: Optional[str] = None,
) -> Callable[[Type["DynamicBase"]], Type["DynamicBase"]]:
    """
    Decorator to register a subtype under one or more base models in the unified registry.

    Parameters:
        resource_type (Optional[Union[Type[T], List[Type[T]]]]):
            The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase)
            are used.
        type_name (Optional[str]): An optional custom type name for the subtype.

    Returns:
        Callable: A decorator function that registers the subtype.
    """

    def decorator(subclass: Type["DynamicBase"]):
        """Register ``subclass`` as a subtype."""
        if resource_type is None:
            resource_types = [
                base for base in subclass.__bases__ if base is not cls
            ]
        elif not isinstance(resource_type, list):
            resource_types = [resource_type]
        else:
            resource_types = resource_type

        for rt in resource_types:
            if not issubclass(subclass, rt):
                raise TypeError(
                    f"'{subclass.__name__}' must be a subclass of '{rt.__name__}'."
                )
            final_type_name = type_name or getattr(
                subclass, "_type", subclass.__name__
            )
            base_model_name = rt.__name__

            if base_model_name not in cls._registry:
                cls._registry[base_model_name] = {"model_cls": rt, "subtypes": {}}
                glogger.debug(
                    "Created new registry entry for base model '%s'.",
                    base_model_name,
                )

            subtypes_dict = cls._registry[base_model_name]["subtypes"]
            if final_type_name in subtypes_dict:
                glogger.warning(
                    "Type '%s' already exists under '%s'; skipping duplicate.",
                    final_type_name,
                    base_model_name,
                )
                continue

            subtypes_dict[final_type_name] = subclass
            glogger.debug(
                "Registered '%s' as '%s' under '%s'.",
                subclass.__name__,
                final_type_name,
                base_model_name,
            )

        DynamicBase._recreate_models()
        return subclass

    return decorator

model_validate_yaml classmethod

model_validate_yaml(yaml_data)

Validate a model from a YAML string.

Source code in swarmauri_base/YamlMixin.py

@classmethod
def model_validate_yaml(cls, yaml_data: str):
    """Validate a model from a YAML string."""
    try:
        # Parse YAML into a Python dictionary
        yaml_content = yaml.safe_load(yaml_data)

        # Convert the dictionary to JSON and validate using Pydantic
        return cls.model_validate_json(json.dumps(yaml_content))
    except yaml.YAMLError as e:
        raise ValueError(f"Invalid YAML data: {e}")
    except ValidationError as e:
        raise ValueError(f"Validation failed: {e}")

model_dump_yaml

model_dump_yaml(
    fields_to_exclude=None, api_key_placeholder=None
)

Return a YAML representation of the model.

Source code in swarmauri_base/YamlMixin.py

def model_dump_yaml(self, fields_to_exclude=None, api_key_placeholder=None):
    """Return a YAML representation of the model."""
    if fields_to_exclude is None:
        fields_to_exclude = []

    # Load the JSON string into a Python dictionary
    json_data = json.loads(self.model_dump_json())

    # Function to recursively remove specific keys and handle api_key placeholders
    def process_fields(data, fields_to_exclude):
        """Recursively filter fields and apply placeholders."""
        if isinstance(data, dict):
            return {
                key: (
                    api_key_placeholder
                    if key == "api_key" and api_key_placeholder is not None
                    else process_fields(value, fields_to_exclude)
                )
                for key, value in data.items()
                if key not in fields_to_exclude
            }
        elif isinstance(data, list):
            return [process_fields(item, fields_to_exclude) for item in data]
        else:
            return data

    # Filter the JSON data
    filtered_data = process_fields(json_data, fields_to_exclude)

    # Convert the filtered data into YAML using safe mode
    return yaml.safe_dump(filtered_data, default_flow_style=False)