Class swarmauri_state_clipboard.ClipboardState.ClipboardState

swarmauri_state_clipboard.ClipboardState.ClipboardState

Bases: StateBase

A concrete implementation of StateBase that uses the system clipboard to store and retrieve state data.

The class relies on the standard library for subprocess calls to external commands available on each platform. If these commands are missing, a FileNotFoundError or subprocess.CalledProcessError may be raised.

type class-attribute instance-attribute

type = 'ClipboardState'

model_config class-attribute instance-attribute

model_config = ConfigDict(
    extra="forbid", 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

default_logger class-attribute

default_logger = None

logger class-attribute instance-attribute

logger = None

name class-attribute instance-attribute

name = None

resource class-attribute instance-attribute

resource = Field(default=STATE.value, frozen=True)

version class-attribute instance-attribute

version = '0.1.0'

state_data class-attribute instance-attribute

state_data = Field(
    default_factory=dict,
    description="The current state data.",
)

clipboard_paste classmethod

clipboard_paste(text)

Copy the given text to the system clipboard using standard library calls.

text (str): The text to copy to the clipboard. RETURNS (None): This method does not return anything. RAISES (FileNotFoundError, subprocess.CalledProcessError): If the underlying system command is unavailable or fails.

Source code in swarmauri_state_clipboard/ClipboardState.py

@classmethod
def clipboard_paste(cls, text: str) -> None:
    """Copy the given text to the system clipboard using standard library calls.

    text (str): The text to copy to the clipboard.
    RETURNS (None): This method does not return anything.
    RAISES (FileNotFoundError, subprocess.CalledProcessError):
        If the underlying system command is unavailable or fails.
    """
    platform = sys.platform
    if platform.startswith("win"):
        # Windows: uses 'clip' command
        with subprocess.Popen(["clip"], stdin=subprocess.PIPE, text=True) as proc:
            proc.communicate(text)
    elif platform.startswith("darwin"):
        # macOS: uses 'pbcopy'
        with subprocess.Popen(["pbcopy"], stdin=subprocess.PIPE, text=True) as proc:
            proc.communicate(text)
    else:
        # Linux/Unix: uses 'xclip'
        with subprocess.Popen(
            ["xclip", "-selection", "clipboard"], stdin=subprocess.PIPE, text=True
        ) as proc:
            proc.communicate(text)

clipboard_copy classmethod

clipboard_copy()

Retrieve text from the system clipboard using standard library calls.

RETURNS (str): The text contents of the system clipboard. RAISES (FileNotFoundError, subprocess.CalledProcessError): If the underlying system command is unavailable or fails.

Source code in swarmauri_state_clipboard/ClipboardState.py

@classmethod
def clipboard_copy(cls) -> str:
    """Retrieve text from the system clipboard using standard library calls.

    RETURNS (str): The text contents of the system clipboard.
    RAISES (FileNotFoundError, subprocess.CalledProcessError):
        If the underlying system command is unavailable or fails.
    """
    platform = sys.platform
    if platform.startswith("win"):
        # Windows: No direct paste command, so we use PowerShell
        completed = subprocess.run(
            ["powershell", "-command", "Get-Clipboard"],
            capture_output=True,
            text=True,
        )
        return completed.stdout
    elif platform.startswith("darwin"):
        # macOS: uses 'pbpaste'
        completed = subprocess.run(["pbpaste"], capture_output=True, text=True)
        return completed.stdout
    else:
        # Linux/Unix: uses 'xclip'
        completed = subprocess.run(
            ["xclip", "-selection", "clipboard", "-o"],
            capture_output=True,
            text=True,
        )
        return completed.stdout

read

read()

Read the current state from the system clipboard as a dictionary.

RETURNS (Dict[str, str]): The clipboard data parsed as a dictionary. Returns an empty dictionary if clipboard content is empty. RAISES (ValueError): If there is an error reading or parsing the state.

Source code in swarmauri_state_clipboard/ClipboardState.py

def read(self) -> Dict[str, str]:
    """Read the current state from the system clipboard as a dictionary.

    RETURNS (Dict[str, str]): The clipboard data parsed as a dictionary.
        Returns an empty dictionary if clipboard content is empty.
    RAISES (ValueError): If there is an error reading or parsing the state.
    """
    try:
        # Use the class method via the class
        clipboard_content = self.__class__.clipboard_copy()

        # For safety, replace eval with safer alternatives
        if clipboard_content.strip():
            import ast

            # Use ast.literal_eval which is much safer than eval()
            # It only evaluates literals, not arbitrary code
            return ast.literal_eval(clipboard_content)
        return {}
    except Exception as e:
        raise ValueError(f"Failed to read state from clipboard: {e}")

write

write(data)

Replace the current state with the given data by copying it to the clipboard.

data (Dict[str, str]): The state data to write. RETURNS (None): This method does not return anything. RAISES (ValueError): If there is an error writing to the clipboard.

Source code in swarmauri_state_clipboard/ClipboardState.py

def write(self, data: Dict[str, str]) -> None:
    """Replace the current state with the given data by copying it to the clipboard.

    data (Dict[str, str]): The state data to write.
    RETURNS (None): This method does not return anything.
    RAISES (ValueError): If there is an error writing to the clipboard.
    """
    if isinstance(data, str):
        raise ValueError("Must be data must be type Dict.")
    try:
        self.__class__.clipboard_paste(str(data))
    except Exception as e:
        raise ValueError(f"Failed to write state to clipboard: {e}")

update

update(data)

Update the current clipboard state by merging existing state with new data.

data (Dict[str, str]): The new state data to merge into the existing clipboard state. RETURNS (None): This method does not return anything. RAISES (ValueError): If there is an error updating the clipboard state.

Source code in swarmauri_state_clipboard/ClipboardState.py

def update(self, data: Dict[str, str]) -> None:
    """Update the current clipboard state by merging existing state with new data.

    data (Dict[str, str]): The new state data to merge into the existing clipboard state.
    RETURNS (None): This method does not return anything.
    RAISES (ValueError): If there is an error updating the clipboard state.
    """
    try:
        current_state = self.read()
        current_state.update(data)
        self.write(current_state)
    except Exception as e:
        raise ValueError(f"Failed to update state on clipboard: {e}")

reset

reset()

Reset the clipboard state to an empty dictionary.

RETURNS (None): This method does not return anything. RAISES (ValueError): If there is an error resetting the clipboard state.

Source code in swarmauri_state_clipboard/ClipboardState.py

def reset(self) -> None:
    """Reset the clipboard state to an empty dictionary.

    RETURNS (None): This method does not return anything.
    RAISES (ValueError): If there is an error resetting the clipboard state.
    """
    try:
        self.write({})
    except Exception as e:
        raise ValueError(f"Failed to reset clipboard state: {e}")

deep_copy

deep_copy()

Create a deep copy of the current state as a new ClipboardState instance.

RETURNS (ClipboardState): A new ClipboardState instance with the same clipboard data. RAISES (ValueError): If there is an error creating the deep copy of the state.

Source code in swarmauri_state_clipboard/ClipboardState.py

def deep_copy(self) -> "ClipboardState":
    """Create a deep copy of the current state as a new ClipboardState instance.

    RETURNS (ClipboardState): A new ClipboardState instance with the same clipboard data.
    RAISES (ValueError): If there is an error creating the deep copy of the state.
    """
    try:
        current_state = self.read()
        new_instance = ClipboardState()
        new_instance.write(current_state)
        return new_instance
    except Exception as e:
        raise ValueError(
            f"Failed to create a deep copy of the clipboard state: {e}"
        )

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_toml classmethod

model_validate_toml(toml_data)

Validate a model from a TOML string.

Source code in swarmauri_base/TomlMixin.py

@classmethod
def model_validate_toml(cls, toml_data: str):
    """Validate a model from a TOML string."""
    try:
        # Parse TOML into a Python dictionary
        toml_content = tomllib.loads(toml_data)

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

model_dump_toml

model_dump_toml(
    fields_to_exclude=None, api_key_placeholder=None
)

Return a TOML representation of the model.

Source code in swarmauri_base/TomlMixin.py

def model_dump_toml(self, fields_to_exclude=None, api_key_placeholder=None):
    """Return a TOML 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 TOML
    return toml.dumps(filtered_data)

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)

model_post_init

model_post_init(logger=None)

Assign a logger instance after model initialization.

Source code in swarmauri_base/LoggerMixin.py

def model_post_init(self, logger: Optional[FullUnion[LoggerBase]] = None) -> None:
    """Assign a logger instance after model initialization."""

    # Directly assign the provided FullUnion[LoggerBase] or fallback to the
    # class-level default.
    self.logger = self.logger or logger or self.default_logger