ImpactIfNone

Documentation

• Class name: ImpactIfNone
• Category: ImpactPack/Logic
• Output node: False

The ImpactIfNone node is designed to evaluate whether a given input is None and conditionally execute logic based on that evaluation. It abstracts the process of null-checking, allowing for streamlined decision-making in data flows where the presence or absence of data dictates subsequent actions.

Input types

Required

Optional

• signal
  • The 'signal' parameter is an optional input that the node can process alongside 'any_input' to determine the flow of logic based on the presence of data.
  • Comfy dtype: *
  • Python dtype: Any
• any_input
  • The 'any_input' parameter is evaluated to check if it is None. Its presence or absence influences the node's decision-making process and the output generated.
  • Comfy dtype: *
  • Python dtype: Any

Output types

• signal_opt
  • Comfy dtype: *
  • The 'signal_opt' output returns the 'signal' input if 'any_input' is not None, facilitating conditional logic flows.
  • Python dtype: Any
• bool
  • Comfy dtype: BOOLEAN
  • The 'bool' output indicates whether 'any_input' was None (False) or not (True), providing a boolean flag for further decision-making.
  • Python dtype: bool

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ImpactIfNone:
    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(cls):
        return {
            "required": {},
            "optional": {"signal": (any_typ,), "any_input": (any_typ,), }
        }

    RETURN_TYPES = (any_typ, "BOOLEAN")
    RETURN_NAMES = ("signal_opt", "bool")
    FUNCTION = "doit"

    CATEGORY = "ImpactPack/Logic"

    def doit(self, signal=None, any_input=None):
        if any_input is None:
            return (signal, False, )
        else:
            return (signal, True, )