Skip to content

Class swarmauri_standard.logger_handlers.QueueLoggingHandler.QueueLoggingHandler

swarmauri_standard.logger_handlers.QueueLoggingHandler.QueueLoggingHandler

Bases: HandlerBase

A logging handler that puts log records onto a queue for asynchronous processing.

This handler uses Python's QueueHandler to enqueue log records for processing by a separate listener thread, allowing the logging operation to be non-blocking.

ATTRIBUTE DESCRIPTION
type

The type identifier for this handler.

TYPE: Literal['QueueLoggingHandler']

queue

The queue instance where log records will be placed.

TYPE: Any

level

The logging level for this handler.

TYPE: int

formatter

Optional formatter for formatting log records.

TYPE: Optional[Union[str, FullUnion[FormatterBase]]]

respect_handler_level

Whether to respect the handler's level when enqueuing records.

TYPE: bool

type class-attribute instance-attribute

type = 'QueueLoggingHandler'

queue class-attribute instance-attribute

queue = Field(default_factory=Queue, exclude=True)

level class-attribute instance-attribute

level = INFO

formatter class-attribute instance-attribute

formatter = None

respect_handler_level class-attribute instance-attribute

respect_handler_level = True

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

name class-attribute instance-attribute

name = None

version class-attribute instance-attribute

version = '0.1.0'

compile_handler

compile_handler()

Compiles a QueueHandler using the specified queue, level, and formatter.

RETURNS DESCRIPTION
Handler

logging.Handler: A configured QueueHandler instance.

Source code in swarmauri_standard/logger_handlers/QueueLoggingHandler.py
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
def compile_handler(self) -> logging.Handler:
    """
    Compiles a QueueHandler using the specified queue, level, and formatter.

    Returns:
        logging.Handler: A configured QueueHandler instance.
    """
    # Create a QueueHandler with the specified queue
    handler = QueueHandler(self.queue)
    handler.setLevel(self.level)

    # Configure the formatter
    if self.formatter:
        if isinstance(self.formatter, str):
            handler.setFormatter(logging.Formatter(self.formatter))
        else:
            handler.setFormatter(self.formatter.compile_formatter())
    else:
        # Use a default formatter if none is specified
        default_formatter = logging.Formatter(
            "[%(name)s][%(levelname)s] %(message)s"
        )
        handler.setFormatter(default_formatter)

    # Configure the handler to respect level or not
    handler.respect_handler_level = self.respect_handler_level

    return handler

get_queue

get_queue()

Get the queue used by this handler.

This is useful when setting up a QueueListener to process the log records.

RETURNS DESCRIPTION
Any

The queue instance used by this handler.

TYPE: Any

Source code in swarmauri_standard/logger_handlers/QueueLoggingHandler.py
64
65
66
67
68
69
70
71
72
73
def get_queue(self) -> Any:
    """
    Get the queue used by this handler.

    This is useful when setting up a QueueListener to process the log records.

    Returns:
        Any: The queue instance used by this handler.
    """
    return self.queue

set_queue

set_queue(new_queue)

Set a new queue for this handler.

PARAMETER DESCRIPTION
new_queue

A queue-like object with a put() method.

TYPE: Any

Source code in swarmauri_standard/logger_handlers/QueueLoggingHandler.py
75
76
77
78
79
80
81
82
def set_queue(self, new_queue: Any) -> None:
    """
    Set a new queue for this handler.

    Args:
        new_queue: A queue-like object with a put() method.
    """
    self.queue = new_queue

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
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
@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
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
@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
11
12
13
14
15
16
17
18
19
20
21
22
23
@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
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
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)