comfyui-node-migration

name	comfyui-node-migration
description	ComfyUI V1 to V3 node migration - converting legacy nodes to the V3 API. Use when migrating existing custom nodes from V1 to V3, understanding differences between API versions, or modernizing node code.

ComfyUI V1 → V3 Migration Guide

Migrate existing V1 nodes to the modern V3 API. V3 uses classmethods, typed inputs/outputs, and ComfyExtension registration.

Migration Checklist

1. Change base class to io.ComfyNode
2. Replace INPUT_TYPES() with define_schema() returning io.Schema
3. Rename execution function to execute and make it a @classmethod
4. Replace return tuples with io.NodeOutput(...)
5. Replace IS_CHANGED with fingerprint_inputs
6. Replace VALIDATE_INPUTS with validate_inputs
7. Convert check_lazy_status to @classmethod
8. Replace NODE_CLASS_MAPPINGS with ComfyExtension + comfy_entrypoint()
9. Access hidden inputs via cls.hidden instead of kwargs
10. Remove __init__ methods (no instance state in V3)

Side-by-Side Comparison

V1 (Before)

import torch

class ImageInvertV1:
    CATEGORY = "image"
    FUNCTION = "invert"
    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("image",)
    OUTPUT_TOOLTIPS = ("The inverted image",)
    DESCRIPTION = "Inverts image colors"

    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "image": ("IMAGE",),
                "strength": ("FLOAT", {
                    "default": 1.0,
                    "min": 0.0,
                    "max": 1.0,
                    "step": 0.01,
                }),
            },
            "optional": {
                "mask": ("MASK",),
            },
            "hidden": {
                "unique_id": "UNIQUE_ID",
            },
        }

    @classmethod
    def IS_CHANGED(s, image, strength, mask=None, unique_id=None):
        return strength

    @classmethod
    def VALIDATE_INPUTS(s, image, strength, mask=None, unique_id=None):
        if strength < 0:
            return "Strength must be non-negative"
        return True

    def invert(self, image, strength, mask=None, unique_id=None):
        inverted = 1.0 - image
        result = image * (1 - strength) + inverted * strength
        if mask is not None:
            result = image * (1 - mask.unsqueeze(-1)) + result * mask.unsqueeze(-1)
        return (result,)

NODE_CLASS_MAPPINGS = {"ImageInvertV1": ImageInvertV1}
NODE_DISPLAY_NAME_MAPPINGS = {"ImageInvertV1": "Invert Image"}

V3 (After)

import torch
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io

class ImageInvertV3(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="ImageInvertV3",
            display_name="Invert Image",
            description="Inverts image colors",
            category="image",
            inputs=[
                io.Image.Input("image"),
                io.Float.Input("strength", default=1.0, min=0.0, max=1.0, step=0.01),
                io.Mask.Input("mask", optional=True),
            ],
            outputs=[
                io.Image.Output("IMAGE", tooltip="The inverted image"),
            ],
            hidden=[io.Hidden.unique_id],
        )

    @classmethod
    def fingerprint_inputs(cls, image, strength, mask=None):
        return strength

    @classmethod
    def validate_inputs(cls, image, strength, mask=None):
        if strength < 0:
            return "Strength must be non-negative"
        return True


     ():
        node_id = cls.hidden.unique_id  

        inverted =  - image
        result = image * ( - strength) + inverted * strength
         mask   :
            result = image * ( - mask.unsqueeze(-)) + result * mask.unsqueeze(-)
         io.NodeOutput(result)


 ():

      () -> [[io.ComfyNode]]:
         [ImageInvertV3]

  () -> MyExtension:
     MyExtension()

Property Mapping

V1 Property	V3 Equivalent
CATEGORY = "image"	io.Schema(category="image")
FUNCTION = "my_func"	Always execute (fixed name)
RETURN_TYPES = ("IMAGE",)	outputs=[io.Image.Output()]
RETURN_NAMES = ("image",)	outputs=[io.Image.Output(display_name="image")]
OUTPUT_TOOLTIPS = ("tip",)	outputs=[io.Image.Output(tooltip="tip")]
OUTPUT_NODE = True	io.Schema(is_output_node=True)
DEPRECATED = True	io.Schema(is_deprecated=True)
EXPERIMENTAL = True	io.Schema(is_experimental=True)
API_NODE = True	io.Schema(is_api_node=True)
NOT_IDEMPOTENT = True	io.Schema(not_idempotent=True)
DESCRIPTION = "..."	io.Schema(description="...")
SEARCH_ALIASES = [...]	io.Schema(search_aliases=[...])
INPUT_IS_LIST = True	io.Schema(is_input_list=True)
OUTPUT_IS_LIST = (True,)	io.Image.Output(is_output_list=True)
DEV_ONLY = True	io.Schema(is_dev_only=True)
ESSENTIALS_CATEGORY = "Basic"	io.Schema(essentials_category="Basic")

Input Type Mapping

V1 Input	V3 Input
("IMAGE",)	io.Image.Input("id")
("MASK",)	io.Mask.Input("id")
("LATENT",)	io.Latent.Input("id")
("MODEL",)	io.Model.Input("id")
("CLIP",)	io.Clip.Input("id")
("VAE",)	io.Vae.Input("id")
("CONDITIONING",)	io.Conditioning.Input("id")
("INT", {"default": 0, ...})	io.Int.Input("id", default=0, ...)
("FLOAT", {"default": 1.0, ...})	io.Float.Input("id", default=1.0, ...)
("STRING", {"multiline": True})	io.String.Input("id", multiline=True)
("BOOLEAN", {"default": True})	io.Boolean.Input("id", default=True)
(["opt1", "opt2"],)	io.Combo.Input("id", options=["opt1", "opt2"])
("CONTROL_NET",)	io.ControlNet.Input("id")
("CLIP_VISION",)	io.ClipVision.Input("id")
("CLIP_VISION_OUTPUT",)	io.ClipVisionOutput.Input("id")
("STYLE_MODEL",)	io.StyleModel.Input("id")
("GLIGEN",)	io.Gligen.Input("id")
("UPSCALE_MODEL",)	io.UpscaleModel.Input("id")
("AUDIO",)

Method Migration

Execute Method

# V1: instance method with custom name
class V1Node:
    FUNCTION = "process"
    def process(self, image, value):
        return (result,)

# V3: classmethod named "execute", returns NodeOutput
class V3Node(io.ComfyNode):
    @classmethod
    def execute(cls, image, value):
        return io.NodeOutput(result)

IS_CHANGED → fingerprint_inputs

# V1
@classmethod
def IS_CHANGED(s, **kwargs):
    return float("NaN")  # always re-execute

# V3
@classmethod
def fingerprint_inputs(cls, **kwargs):
    import time
    return time.time()  # always re-execute

VALIDATE_INPUTS → validate_inputs

# V1
@classmethod
def VALIDATE_INPUTS(s, input_types=None, **kwargs):
    return True

# V3
@classmethod
def validate_inputs(cls, input_types=None, **kwargs):
    return True

check_lazy_status

# V1: instance method
def check_lazy_status(self, **kwargs):
    return ["input_name"]

# V3: classmethod
@classmethod
def check_lazy_status(cls, **kwargs):
    return ["input_name"]

Hidden Inputs

# V1: received as kwargs
def execute(self, image, unique_id=None, prompt=None):
    node_id = unique_id

# V3: accessed via cls.hidden
@classmethod
def execute(cls, image):
    node_id = cls.hidden.unique_id
    prompt = cls.hidden.prompt

Registration Migration

# V1
NODE_CLASS_MAPPINGS = {
    "Node1": Node1Class,
    "Node2": Node2Class,
}
NODE_DISPLAY_NAME_MAPPINGS = {
    "Node1": "Node One",
    "Node2": "Node Two",
}
WEB_DIRECTORY = "./js"

# V3
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io

class MyExtension(ComfyExtension):
    @override
    async def get_node_list(self) -> list[type[io.ComfyNode]]:
        return [Node1Class, Node2Class]

    @override
    async def on_load(self):
        # Optional: initialization logic
        pass

async def comfy_entrypoint() -> MyExtension:
    return MyExtension()

# WEB_DIRECTORY still works the same way for JS extensions
WEB_DIRECTORY = "./js"

Output Node Migration

# V1
class V1SaveNode:
    RETURN_TYPES = ()
    OUTPUT_NODE = True
    FUNCTION = "save"

    def save(self, images, prefix):
        # ... save logic ...
        return {"ui": {"images": results}}

# V3
from comfy_api.latest import io, ui

class V3SaveNode(io.ComfyNode):
    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="V3SaveNode",
            display_name="Save",
            category="image",
            is_output_node=True,
            inputs=[
                io.Image.Input("images"),
                io.String.Input("prefix", default="output"),
            ],
            outputs=[],
            hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
        )

    @classmethod
    def execute(cls, images, prefix):
        saved = ui.ImageSaveHelper.get_save_images_ui(images, prefix, cls=cls)
        return io.NodeOutput(ui=saved)

Key Gotchas

1. No instance state: V3 execute is a classmethod. Don't store state on self. Use external storage if needed.
2. Fixed method name: Always execute, never custom names.
3. Hidden access changed: Use cls.hidden.prompt not function parameters.
4. Return type changed: io.NodeOutput(val) not (val,).
5. Optional inputs: Use =None default in execute params, not separate "optional" dict.
6. Async support: V3 execute can be async def execute(cls, ...).

See Also

• comfyui-node-basics - V3 node fundamentals
• comfyui-node-packaging - Project structure
• comfyui-node-lifecycle - Execution lifecycle differences