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Class swarmauri_standard.logger_handlers.EmailLoggingHandler.EmailLoggingHandler

swarmauri_standard.logger_handlers.EmailLoggingHandler.EmailLoggingHandler

Bases: HandlerBase

A handler that sends log messages via email using SMTP.

This handler extends the HandlerBase class to provide email logging functionality. It uses Python's SMTPHandler to send log records to specified recipients.

type class-attribute instance-attribute 

type = 'EmailLoggingHandler'

mailhost class-attribute instance-attribute 

mailhost = 'localhost'

credentials class-attribute instance-attribute 

credentials = None

secure class-attribute instance-attribute 

secure = None

timeout class-attribute instance-attribute 

timeout = None

fromaddr class-attribute instance-attribute 

fromaddr = 'logger@example.com'

toaddrs class-attribute instance-attribute 

toaddrs = []

subject class-attribute instance-attribute 

subject = 'Logging Message'

mail_from_display_name class-attribute instance-attribute 

mail_from_display_name = None

send_empty_entries class-attribute instance-attribute 

send_empty_entries = False

html class-attribute instance-attribute 

html = False

formatter class-attribute instance-attribute 

formatter = None

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'

level class-attribute instance-attribute 

level = INFO

compile_handler 

compile_handler()

Compiles and returns an SMTPHandler configured with the provided settings.

RETURNS DESCRIPTION
Handler

logging.Handler: A configured SMTPHandler instance.
Source code in swarmauri_standard/logger_handlers/EmailLoggingHandler.py 
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def compile_handler(self) -> logging.Handler:
    """
    Compiles and returns an SMTPHandler configured with the provided settings.

    Returns:
        logging.Handler: A configured SMTPHandler instance.
    """
    # Validate required fields
    if not self.toaddrs:
        raise ValueError("Email recipients (toaddrs) must be specified")

    # Prepare from address with optional display name
    from_addr = self.fromaddr
    if self.mail_from_display_name:
        from_addr = formataddr((self.mail_from_display_name, self.fromaddr))

    # Create the SMTP handler
    handler = logging.handlers.SMTPHandler(
        mailhost=self.mailhost,
        fromaddr=from_addr,
        toaddrs=self.toaddrs,
        subject=self.subject,
        credentials=self.credentials,
        secure=self.secure,
        timeout=self.timeout,
    )

    # Set the log level
    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:
        # Default HTML or plain text formatter
        if self.html:
            default_formatter = logging.Formatter(
                "<html><body><h2>%(levelname)s</h2>"
                "<p><b>Logger:</b> %(name)s<br>"
                "<b>Time:</b> %(asctime)s<br>"
                "<b>Message:</b> %(message)s</p>"
                "</body></html>",
                "%Y-%m-%d %H:%M:%S",
            )
        else:
            default_formatter = logging.Formatter(
                "[%(asctime)s][%(name)s][%(levelname)s] %(message)s",
                "%Y-%m-%d %H:%M:%S",
            )
        handler.setFormatter(default_formatter)

    # Handle HTML content type if needed
    if self.html:
        # Add HTML content type header to emails
        # This is done by monkey patching the getSubject method
        original_get_subject = handler.getSubject

        def get_subject_with_content_type(record):
            subject = original_get_subject(record)
            return f"{subject}\nContent-Type: text/html"

        handler.getSubject = get_subject_with_content_type

    # Configure to not send empty log entries if specified
    if not self.send_empty_entries:
        original_emit = handler.emit

        def emit_if_not_empty(record):
            if record.getMessage().strip():
                original_emit(record)

        handler.emit = emit_if_not_empty

    return handler

get_configuration 

get_configuration()

Returns the configuration of this handler.

RETURNS DESCRIPTION
Dict[str, Any]

Dict[str, Any]: A dictionary containing the configuration.
Source code in swarmauri_standard/logger_handlers/EmailLoggingHandler.py 
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def get_configuration(self) -> Dict[str, Any]:
    """
    Returns the configuration of this handler.

    Returns:
        Dict[str, Any]: A dictionary containing the configuration.
    """
    return {
        "type": self.type,
        "level": self.level,
        "mailhost": self.mailhost,
        "fromaddr": self.fromaddr,
        "toaddrs": self.toaddrs,
        "subject": self.subject,
        "credentials": "***REDACTED***" if self.credentials else None,
        "secure": True if isinstance(self.secure, tuple) else self.secure,
        "html": self.html,
        "mail_from_display_name": self.mail_from_display_name,
        "send_empty_entries": self.send_empty_entries,
        "formatter": str(self.formatter) if self.formatter else None,
    }

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 
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@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 
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@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 
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@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 
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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)