Merge pull request #149 from pydn/codex/runtime-e2e-validation

Add runtime E2E validation harness and fixtures

README.md

@@ -1,212 +1,126 @@
-## ComfyUI-to-Python-Extension
+# ComfyUI-to-Python-Extension
+
 ![banner](images/comfyui_to_python_banner.png)
 
-The `ComfyUI-to-Python-Extension` is a powerful tool that translates [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflows into executable Python code. Designed to bridge the gap between ComfyUI's visual interface and Python's programming environment, this script facilitates the seamless transition from design to code execution. Whether you're a data scientist, a software developer, or an AI enthusiast, this tool streamlines the process of implementing ComfyUI workflows in Python.
+Build a workflow in ComfyUI, then walk away with runnable Python.
 
-**Convert this:**
+`ComfyUI-to-Python-Extension` turns visual workflows into executable scripts so you can move from node graphs to automation, experiments, and repeatable generation without rebuilding everything by hand.
 
-![SDXL UI Example](images/SDXL-UI-Example.jpg)
+This project supports:
+- exporting from the ComfyUI UI with `Save As Script`
+- converting saved API-format workflows with the CLI
 
+## Install
 
-**To this:**
+Choose the setup that matches how you want to use the project.
 
+### Web UI extension (`File -> Save As Script`)
+
+For ComfyUI to recognize this project as an extension, the repo must be discoverable through ComfyUI's `custom_nodes` search paths.
+
+Use one of these setups:
+
+1. Clone directly into `ComfyUI/custom_nodes`
+```bash
+cd /path/to/ComfyUI/custom_nodes
+git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
+cd ComfyUI-to-Python-Extension
+uv sync
 ```
-import random
-import torch
-import sys
 
-sys.path.append("../")
-from nodes import (
-    VAEDecode,
-    KSamplerAdvanced,
-    EmptyLatentImage,
-    SaveImage,
-    CheckpointLoaderSimple,
-    CLIPTextEncode,
-)
+2. Keep the repo elsewhere, then either:
+- symlink it into `ComfyUI/custom_nodes`
+- add its parent directory to ComfyUI's `custom_nodes` search paths via `extra_model_paths.yaml`
 
-
-def main():
-    with torch.inference_mode():
-        checkpointloadersimple = CheckpointLoaderSimple()
-        checkpointloadersimple_4 = checkpointloadersimple.load_checkpoint(
-            ckpt_name="sd_xl_base_1.0.safetensors"
-        )
-
-        emptylatentimage = EmptyLatentImage()
-        emptylatentimage_5 = emptylatentimage.generate(
-            width=1024, height=1024, batch_size=1
-        )
-
-        cliptextencode = CLIPTextEncode()
-        cliptextencode_6 = cliptextencode.encode(
-            text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it",
-            clip=checkpointloadersimple_4[1],
-        )
-
-        cliptextencode_7 = cliptextencode.encode(
-            text="text, watermark", clip=checkpointloadersimple_4[1]
-        )
-
-        checkpointloadersimple_12 = checkpointloadersimple.load_checkpoint(
-            ckpt_name="sd_xl_refiner_1.0.safetensors"
-        )
-
-        cliptextencode_15 = cliptextencode.encode(
-            text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it",
-            clip=checkpointloadersimple_12[1],
-        )
-
-        cliptextencode_16 = cliptextencode.encode(
-            text="text, watermark", clip=checkpointloadersimple_12[1]
-        )
-
-        ksampleradvanced = KSamplerAdvanced()
-        vaedecode = VAEDecode()
-        saveimage = SaveImage()
-
-        for q in range(10):
-            ksampleradvanced_10 = ksampleradvanced.sample(
-                add_noise="enable",
-                noise_seed=random.randint(1, 2**64),
-                steps=25,
-                cfg=8,
-                sampler_name="euler",
-                scheduler="normal",
-                start_at_step=0,
-                end_at_step=20,
-                return_with_leftover_noise="enable",
-                model=checkpointloadersimple_4[0],
-                positive=cliptextencode_6[0],
-                negative=cliptextencode_7[0],
-                latent_image=emptylatentimage_5[0],
-            )
-
-            ksampleradvanced_11 = ksampleradvanced.sample(
-                add_noise="disable",
-                noise_seed=random.randint(1, 2**64),
-                steps=25,
-                cfg=8,
-                sampler_name="euler",
-                scheduler="normal",
-                start_at_step=20,
-                end_at_step=10000,
-                return_with_leftover_noise="disable",
-                model=checkpointloadersimple_12[0],
-                positive=cliptextencode_15[0],
-                negative=cliptextencode_16[0],
-                latent_image=ksampleradvanced_10[0],
-            )
-
-            vaedecode_17 = vaedecode.decode(
-                samples=ksampleradvanced_11[0], vae=checkpointloadersimple_12[2]
-            )
-
-            saveimage_19 = saveimage.save_images(
-                filename_prefix="ComfyUI", images=vaedecode_17[0]
-            )
-
-
-if __name__ == "__main__":
-    main()
+Example symlink setup:
+```bash
+git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
+cd /path/to/ComfyUI/custom_nodes
+ln -s /path/to/ComfyUI-to-Python-Extension ComfyUI-to-Python-Extension
+cd /path/to/ComfyUI-to-Python-Extension
+uv sync
 ```
-## Potential Use Cases
-- Streamlining the process for creating a lean app or pipeline deployment that uses a ComfyUI workflow
-- Creating programmatic experiments for various prompt/parameter values
-- Creating large queues for image generation (For example, you could adjust the script to generate 1000 images without clicking ctrl+enter 1000 times)
-- Easily expanding or iterating on your architecture in Python once a foundational workflow is in place in the GUI
 
-## V1.3.0 Release Notes
-- Generate .py file directly from the ComfyUI Web App
+After installation, restart ComfyUI.
+
+### CLI exporter / generated scripts
+
+You can keep the repo anywhere for CLI usage and generated-script execution.
+
+```bash
+git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
+cd ComfyUI-to-Python-Extension
+uv sync
+export COMFYUI_PATH=/path/to/ComfyUI
+```
+
+`COMFYUI_PATH` helps the exporter and generated scripts find the ComfyUI codebase. It does not, by itself, register this repo as a ComfyUI extension for the Web UI.
+
+`COMFYUI_PATH` is checked first. If it is not set, the exporter falls back to searching parent directories for a folder named `ComfyUI`.
+
+## Web UI Export
+
+In current ComfyUI builds, `Save As Script` is typically available under:
+
+`File -> Save As Script`
+
+The command downloads a generated `.py` file.
 
 ![Save As Script](images/save_as_script.png)
 
-## V1.2.1 Release Notes
-- Dynamically change `comfyui_to_python.py` parameters with CLI arguments
-- Hotfix to handle nodes that accept kwargs.
+Notes:
+- menu placement can differ between frontend versions
+- ComfyUI Desktop may fail on the current filename prompt flow; use the CLI flow below if that happens
 
-## V1.2.0 Release Notes
-- Updates to adhere to latest changes from `ComfyUI`
+## CLI Export
 
-## V1.0.0 Release Notes
-- **Use all the custom nodes!**
-    - Custom nodes are now supported. If you run into any issues with code execution, first ensure that the each node works as expected in the GUI. If it works in the GUI, but not in the generated script, please submit an issue.
+1. In ComfyUI, enable dev mode options if needed.
+2. Save the workflow in API format: `File -> Export (API)`.
+3. Run the exporter:
 
+```bash
+uv run python comfyui_to_python.py
+```
 
-## Installation
+Options:
 
+```bash
+uv run python comfyui_to_python.py \
+  --input_file workflow_api.json \
+  --output_file workflow_api.py \
+  --queue_size 10
+```
 
-1. Navigate to your `ComfyUI/custom_nodes` directory
+Flags:
+- `--input_file`: input workflow JSON, default `workflow_api.json`
+- `--output_file`: output Python file, default `workflow_api.py`
+- `--queue_size`: default execution count in the generated script, default `10`
 
-2. Clone this repo
-    ```bash
-    git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
-    ```
+![Dev Mode Options](images/dev_mode_options.PNG)
 
-    After cloning the repo, your `ComfyUI` directory should look like this:
-    ```
-    /comfy
-    /comfy_extras
-    /custom_nodes
-    --/ComfyUI-to-Python-Extension
-    /input
-    /models
-    /output
-    /script_examples
-    /web
-    .gitignore
-    LICENSE
-    README.md
-    comfyui_screenshot.png
-    cuda_mollac.py
-    execution.py
-    extra_model_paths.yaml.example
-    folder_paths.py
-    latent_preview.py
-    main.py
-    nodes.py
-    requirements.txt
-    server.py
-    ```
+## Generated Scripts
 
-## Web App Use
-1. Launch ComfyUI
+Generated scripts depend on a working ComfyUI runtime.
 
-2. Load your favorite workflow and click `Save As Script`
+If the repo is not inside ComfyUI, set:
 
-![Save As Script](images/save_as_script.png)
+```bash
+export COMFYUI_PATH=/path/to/ComfyUI
+```
 
-3. Type your desired file name into the pop up screen.
+The generated script is a workflow export. It does not automatically turn workflow inputs into command-line arguments.
 
-4. Move .py file from your downloads folder to your `ComfyUI` directory.
+Scripts exported directly from `File -> Save As Script` in the ComfyUI UI already include the frontend workflow metadata needed for drag-and-drop reimport. Images saved by those scripts can be dropped back into ComfyUI and reopen with the original workflow metadata.
 
-5. Now you can execute the newly created .py file to generate images without launching a server.
+## Troubleshooting
 
-## CLI Usage
-1. Navigate to the `ComfyUI-to-Python-Extension` folder and install requirements
-    ```bash
-    pip install -r requirements.txt
-    ```
-
-2. Launch ComfyUI, click the gear icon over `Queue Prompt`, then check `Enable Dev mode Options`. **THE SCRIPT WILL NOT WORK IF YOU DO NOT ENABLE THIS OPTION!**
-
-![Enable Dev Mode Options](images/dev_mode_options.jpg)
-
-3. Load up your favorite workflows, then click the newly enabled `Save (API Format)` button under Queue Prompt
-
-4. Move the downloaded .json workflow file to your `ComfyUI/ComfyUI-to-Python-Extension` folder
-
-5. If needed, add arguments when executing `comfyui_to_python.py` to update the default `input_file` and `output_file` to match your .json workflow file and desired .py file name. By default, the script will look for a file called `workflow_api.json`. You can also update the `queue_size` variable to your desired number of images that you want to generate in a single script execution. By default, the scripts will generate 10 images. Run `python comfyui_to_python.py --help` for more details.
-
-6a. Run the script with default arguments:
-   ```bash
-   python comfyui_to_python.py
-   ```
-6b. Run the script with optional arguments:
-   ```bash
-   python comfyui_to_python.py --input_file "workflow_api (2).json" --output_file my_workflow.py --queue_size 100
-   ```
-
-7. After running `comfyui_to_python.py`, a new .py file will be created in the current working directory. If you made no changes, look for `workflow_api.py`.
-
-8. Now you can execute the newly created .py file to generate images without launching a server.
+- `Save As Script` not visible:
+  check your current ComfyUI menu/frontend version and look under `File`
+- `Save As Script` not visible after restart:
+  make sure this repo is discoverable by ComfyUI through `custom_nodes` by cloning it into `ComfyUI/custom_nodes`, symlinking it there, or adding an external `custom_nodes` path in `extra_model_paths.yaml`
+- Desktop says `prompt()` is unsupported:
+  use the CLI export flow instead
+- ComfyUI cannot be found:
+  set `COMFYUI_PATH`
+- models or paths are missing at runtime:
+  verify the target ComfyUI install and its `extra_model_paths.yaml`

__init__.py

@@ -45,9 +45,14 @@ async def save_as_script(request):
         data = await request.json()
         name = data["name"]
         workflow = data["workflow"]
+        frontend_workflow = data.get("frontend_workflow")
 
         sio = StringIO()
-        ComfyUItoPython(workflow=workflow, output_file=sio)
+        ComfyUItoPython(
+            workflow=workflow,
+            frontend_workflow=frontend_workflow,
+            output_file=sio,
+        )
 
         sio.seek(0)
         data = sio.read()

comfyui_to_python.py

@@ -2,6 +2,7 @@ import copy
 import glob
 import inspect
 import json
+import keyword
 import os
 import random
 import sys
@@ -16,20 +17,30 @@ sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 from comfyui_to_python_utils import (
     import_custom_nodes,
     find_path,
+    get_comfyui_path,
     add_comfyui_directory_to_sys_path,
     add_extra_model_paths,
     get_value_at_index,
 )
 
-add_comfyui_directory_to_sys_path()
-from nodes import NODE_CLASS_MAPPINGS
-
 
 DEFAULT_INPUT_FILE = "workflow_api.json"
 DEFAULT_OUTPUT_FILE = "workflow_api.py"
 DEFAULT_QUEUE_SIZE = 10
 
 
+def get_node_class_mappings() -> Dict:
+    """Load ComfyUI node mappings on demand.
+
+    Tests that inject explicit node mappings should not need a full ComfyUI runtime
+    just to import this module.
+    """
+    add_comfyui_directory_to_sys_path()
+    from nodes import NODE_CLASS_MAPPINGS
+
+    return NODE_CLASS_MAPPINGS
+
+
 class FileHandler:
     """Handles reading and writing files.
 
@@ -183,9 +194,20 @@ class CodeGenerator:
         self.node_class_mappings = node_class_mappings
         self.base_node_class_mappings = base_node_class_mappings
 
+    @staticmethod
+    def sanitize_node_id(node_id: str) -> str:
+        """Convert node IDs into variable-safe tokens without collapsing separators."""
+        sanitized = re.sub(r"[^a-z0-9_]", "_", str(node_id).lower().strip())
+        sanitized = re.sub(r"_+", "_", sanitized).strip("_")
+        if not sanitized:
+            sanitized = "node"
+        return sanitized
+
     def generate_workflow(
         self,
         load_order: List,
+        workflow_data: Dict,
+        metadata_workflow_data: Dict | None = None,
         queue_size: int = 10,
     ) -> str:
         """Generate the execution code based on the load order.
@@ -199,7 +221,7 @@ class CodeGenerator:
         """
         # Create the necessary data structures to hold imports and generated code
         import_statements, executed_variables, special_functions_code, code = (
-            set(["NODE_CLASS_MAPPINGS"]),
+            {"nodes": {"NODE_CLASS_MAPPINGS"}},
             {},
             [],
             [],
@@ -235,8 +257,9 @@ class CodeGenerator:
                 )
                 initialized_objects[class_type] = self.clean_variable_name(class_type)
                 if class_type in self.base_node_class_mappings.keys():
-                    import_statements.add(import_statement)
-                if class_type not in self.base_node_class_mappings.keys():
+                    module_name, import_name = import_statement
+                    import_statements.setdefault(module_name, set()).add(import_name)
+                if 'NODE_CLASS_MAPPINGS["' in class_code:
                     custom_nodes = True
                 special_functions_code.append(class_code)
 
@@ -253,20 +276,35 @@ class CodeGenerator:
                 if no_params or key in class_def_params
             }
             # Deal with hidden variables
+            hidden_inputs = input_types.get("hidden", {})
             if (
-                "hidden" in input_types.keys()
-                and "unique_id" in input_types["hidden"].keys()
+                "unique_id" in hidden_inputs
+                and (no_params or "unique_id" in class_def_params)
             ):
                 inputs["unique_id"] = random.randint(1, 2**64)
-            elif class_def_params is not None:
+            if "prompt" in hidden_inputs and (no_params or "prompt" in class_def_params):
+                inputs["prompt"] = {"variable_name": "prompt"}
+            if "extra_pnginfo" in hidden_inputs and (
+                no_params or "extra_pnginfo" in class_def_params
+            ):
+                inputs["extra_pnginfo"] = {"variable_name": "extra_pnginfo"}
+            if "hidden" not in input_types and class_def_params is not None:
                 if "unique_id" in class_def_params:
                     inputs["unique_id"] = random.randint(1, 2**64)
 
             # Create executed variable and generate code
-            executed_variables[idx] = f"{self.clean_variable_name(class_type)}_{idx}"
+            executed_variables[idx] = (
+                f"{self.clean_variable_name(class_type)}_"
+                f"{self.sanitize_node_id(str(idx))}"
+            )
             inputs = self.update_inputs(inputs, executed_variables)
+            seed_sync_code = self.create_prompt_seed_sync_code(
+                idx, inputs, is_special_function
+            )
 
             if is_special_function:
+                if seed_sync_code:
+                    special_functions_code.extend(seed_sync_code)
                 special_functions_code.append(
                     self.create_function_call_code(
                         initialized_objects[class_type],
@@ -277,6 +315,8 @@ class CodeGenerator:
                     )
                 )
             else:
+                if seed_sync_code:
+                    code.extend(seed_sync_code)
                 code.append(
                     self.create_function_call_code(
                         initialized_objects[class_type],
@@ -289,7 +329,13 @@ class CodeGenerator:
 
         # Generate final code by combining imports and code, and wrap them in a main function
         final_code = self.assemble_python_code(
-            import_statements, special_functions_code, code, queue_size, custom_nodes
+            import_statements,
+            special_functions_code,
+            code,
+            workflow_data,
+            metadata_workflow_data,
+            queue_size,
+            custom_nodes,
         )
 
         return final_code
@@ -326,6 +372,28 @@ class CodeGenerator:
 
         return code
 
+    def create_prompt_seed_sync_code(
+        self, node_id: str, inputs: Dict, is_special_function: bool
+    ) -> List[str]:
+        """Generate code that keeps prompt metadata aligned with randomized seeds."""
+        seed_sync_lines = []
+        for key in ("seed", "noise_seed"):
+            if key not in inputs:
+                continue
+            randomized_seed_variable = (
+                f"node_{self.sanitize_node_id(str(node_id))}_{self.clean_variable_name(key)}"
+            )
+            seed_sync_lines.append(
+                f'{randomized_seed_variable} = prompt["{node_id}"]["inputs"]["{key}"] = random.randint(1, 2**64)'
+            )
+            inputs[key] = {"variable_name": randomized_seed_variable}
+
+        if not seed_sync_lines:
+            return []
+
+        indentation = "" if is_special_function else "\t"
+        return [f"{indentation}{line}\n" for line in seed_sync_lines]
+
     def format_arg(self, key: str, value: any) -> str:
         """Formats arguments based on key and value.
 
@@ -336,39 +404,61 @@ class CodeGenerator:
         Returns:
             str: Formatted argument as a string.
         """
+        value_code = self.format_arg_value(key, value)
+        if key.isidentifier() and not keyword.iskeyword(key):
+            return f"{key}={value_code}"
+        return f"**{{{json.dumps(key)}: {value_code}}}"
+
+    @staticmethod
+    def format_arg_value(key: str, value: any) -> str:
+        """Formats an argument value as Python source."""
+        if isinstance(value, dict) and "variable_name" in value:
+            return value["variable_name"]
         if key == "noise_seed" or key == "seed":
-            return f"{key}=random.randint(1, 2**64)"
-        elif isinstance(value, str):
-            value = value.replace("\n", "\\n").replace('"', "'")
-            return f'{key}="{value}"'
-        elif isinstance(value, dict) and "variable_name" in value:
-            return f'{key}={value["variable_name"]}'
-        return f"{key}={value}"
+            return "random.randint(1, 2**64)"
+        if isinstance(value, str):
+            return json.dumps(value)
+        return repr(value)
 
     def assemble_python_code(
         self,
-        import_statements: set,
+        import_statements: Dict[str, set],
         speical_functions_code: List[str],
         code: List[str],
+        workflow_data: Dict,
+        metadata_workflow_data: Dict | None,
         queue_size: int,
         custom_nodes=False,
     ) -> str:
         """Generates the final code string.
 
         Args:
-            import_statements (set): A set of unique import statements.
+            import_statements (Dict[str, set]): Import statements grouped by module.
             speical_functions_code (List[str]): A list of special functions code strings.
             code (List[str]): A list of code strings.
+            workflow_data (Dict): The API workflow data used for runtime prompt execution.
+            metadata_workflow_data (Dict | None): The workflow metadata to embed into saved outputs.
             queue_size (int): Number of photos that will be generated by the script.
             custom_nodes (bool): Whether to include custom nodes in the code.
 
         Returns:
             str: Generated final code as a string.
         """
+        if metadata_workflow_data is None:
+            extra_pnginfo_code = "extra_pnginfo = None"
+        else:
+            extra_pnginfo_code = (
+                "extra_pnginfo = "
+                '{"workflow": json.loads('
+                + json.dumps(json.dumps(metadata_workflow_data))
+                + ")}"
+            )
+
         # Get the source code of the utils functions as a string
         func_strings = []
         for func in [
             get_value_at_index,
+            get_comfyui_path,
             find_path,
             add_comfyui_directory_to_sys_path,
             add_extra_model_paths,
@@ -377,6 +467,7 @@ class CodeGenerator:
         # Define static import statements required for the script
         static_imports = (
             [
+                "import json",
                 "import os",
                 "import random",
                 "import sys",
@@ -384,7 +475,12 @@ class CodeGenerator:
                 "import torch",
             ]
             + func_strings
-            + ["\n\nadd_comfyui_directory_to_sys_path()\nadd_extra_model_paths()\n"]
+            + [
+                "\n\nadd_comfyui_directory_to_sys_path()\nadd_extra_model_paths()\n",
+                f"workflow = json.loads({json.dumps(json.dumps(workflow_data))})",
+                "prompt = json.loads(json.dumps(workflow))",
+                extra_pnginfo_code,
+            ]
         )
         # Check if custom nodes should be included
         if custom_nodes:
@@ -393,16 +489,19 @@ class CodeGenerator:
         else:
             custom_nodes = ""
         # Create import statements for node classes
-        imports_code = [
-            f"from nodes import {', '.join([class_name for class_name in import_statements])}"
-        ]
+        imports_code = []
+        for module_name in sorted(import_statements.keys()):
+            class_names = ", ".join(sorted(import_statements[module_name]))
+            imports_code.append(f"from {module_name} import {class_names}")
+        special_functions_body = "\n\t\t".join(speical_functions_code) or "pass"
+        loop_body = "\n\t\t".join(code) or "\tpass"
         # Assemble the main function code, including custom nodes if applicable
         main_function_code = (
             "def main():\n\t"
             + f"{custom_nodes}with torch.inference_mode():\n\t\t"
-            + "\n\t\t".join(speical_functions_code)
+            + special_functions_body
             + f"\n\n\t\tfor q in range({queue_size}):\n\t\t"
-            + "\n\t\t".join(code)
+            + loop_body
         )
         # Concatenate all parts to form the final code
         final_code = "\n".join(
@@ -415,20 +514,31 @@ class CodeGenerator:
 
         return final_code
 
-    def get_class_info(self, class_type: str) -> Tuple[str, str, str]:
+    def get_class_info(self, class_type: str) -> Tuple[str, Tuple[str, str], str]:
         """Generates and returns necessary information about class type.
 
         Args:
             class_type (str): Class type.
 
         Returns:
-            Tuple[str, str, str]: Updated class type, import statement string, class initialization code.
+            Tuple[str, Tuple[str, str], str]: Updated class type, import statement and initialization code.
         """
-        import_statement = class_type
+        class_obj = self.base_node_class_mappings.get(class_type)
+        module_name = "nodes"
+        if class_obj is not None:
+            module_name = class_obj.__module__
         variable_name = self.clean_variable_name(class_type)
-        if class_type in self.base_node_class_mappings.keys():
+        is_importable_module = bool(
+            module_name
+            and "/" not in module_name
+            and "\\" not in module_name
+            and all(part.isidentifier() for part in module_name.split("."))
+        )
+        if class_type in self.base_node_class_mappings.keys() and is_importable_module:
+            import_statement = (module_name, class_type)
             class_code = f"{variable_name} = {class_type.strip()}()"
         else:
+            import_statement = ("nodes", "NODE_CLASS_MAPPINGS")
             class_code = f'{variable_name} = NODE_CLASS_MAPPINGS["{class_type}"]()'
 
         return class_type, import_statement, class_code
@@ -511,10 +621,11 @@ class ComfyUItoPython:
     def __init__(
         self,
         workflow: str = "",
+        frontend_workflow: str | Dict | None = None,
         input_file: str = "",
         output_file: str | TextIO = "",
         queue_size: int = 1,
-        node_class_mappings: Dict = NODE_CLASS_MAPPINGS,
+        node_class_mappings: Dict | None = None,
         needs_init_custom_nodes: bool = False,
     ):
         """Initialize the ComfyUItoPython class with the given parameters. Exactly one of workflow or input_file must be specified.
@@ -523,7 +634,8 @@ class ComfyUItoPython:
             input_file (str): Path to the input JSON file.
             output_file (str | TextIO): Path to the output file or a file-like object.
             queue_size (int): The number of times a workflow will be executed by the script. Defaults to 1.
-            node_class_mappings (Dict): Mappings of node classes. Defaults to NODE_CLASS_MAPPINGS.
+            node_class_mappings (Dict | None): Mappings of node classes. Defaults to the current
+                ComfyUI NODE_CLASS_MAPPINGS when not provided.
             needs_init_custom_nodes (bool): Whether to initialize custom nodes. Defaults to False.
         """
         if input_file and workflow:
@@ -535,10 +647,15 @@ class ComfyUItoPython:
             raise ValueError("Needs output_file")
 
         self.workflow = workflow
+        self.frontend_workflow = frontend_workflow
         self.input_file = input_file
         self.output_file = output_file
         self.queue_size = queue_size
-        self.node_class_mappings = node_class_mappings
+        self.node_class_mappings = (
+            node_class_mappings
+            if node_class_mappings is not None
+            else get_node_class_mappings()
+        )
         self.needs_init_custom_nodes = needs_init_custom_nodes
 
         self.base_node_class_mappings = copy.deepcopy(self.node_class_mappings)
@@ -550,19 +667,30 @@ class ComfyUItoPython:
         Returns:
             None
         """
-        # Step 1: Import all custom nodes if we need to
-        if self.needs_init_custom_nodes:
-            import_custom_nodes()
-        else:
-            # If they're already imported, we don't know which nodes are custom nodes, so we need to import all of them
-            self.base_node_class_mappings = {}
-
-        # Step 2: Read JSON data from the input file
+        # Step 1: Read JSON data from the input file
         if self.input_file:
             data = FileHandler.read_json_file(self.input_file)
         else:
             data = json.loads(self.workflow)
 
+        metadata_workflow_data = None
+        if self.frontend_workflow:
+            if isinstance(self.frontend_workflow, str):
+                metadata_workflow_data = json.loads(self.frontend_workflow)
+            else:
+                metadata_workflow_data = self.frontend_workflow
+
+        # Step 2: Initialize extra/custom nodes when requested or when the workflow references
+        # a node class that is not currently loaded in the runtime.
+        missing_node_types = {
+            node_data["class_type"]
+            for node_data in data.values()
+            if node_data["class_type"] not in self.node_class_mappings
+        }
+        if self.needs_init_custom_nodes or missing_node_types:
+            import_custom_nodes()
+            self.base_node_class_mappings = copy.deepcopy(self.node_class_mappings)
+
         # Step 3: Determine the load order
         load_order_determiner = LoadOrderDeterminer(data, self.node_class_mappings)
         load_order = load_order_determiner.determine_load_order()
@@ -572,7 +700,10 @@ class ComfyUItoPython:
             self.node_class_mappings, self.base_node_class_mappings
         )
         generated_code = code_generator.generate_workflow(
-            load_order, queue_size=self.queue_size
+            load_order,
+            data,
+            metadata_workflow_data,
+            queue_size=self.queue_size,
         )
 
         # Step 5: Write the generated code to a file

comfyui_to_python_utils.py

@@ -3,16 +3,30 @@ from typing import Sequence, Mapping, Any, Union
 import sys
 
 
+def get_comfyui_path() -> str:
+    """Return the configured ComfyUI path, preferring COMFYUI_PATH when set."""
+    comfyui_path = os.environ.get("COMFYUI_PATH")
+    if comfyui_path:
+        return comfyui_path
+    return find_path("ComfyUI")
+
+
 def import_custom_nodes() -> None:
     """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
 
     This function sets up a new asyncio event loop, initializes the PromptServer,
     creates a PromptQueue, and initializes the custom nodes.
     """
+    comfyui_path = get_comfyui_path()
+    if comfyui_path and comfyui_path not in sys.path:
+        sys.path.insert(0, comfyui_path)
+
     import asyncio
     import execution
     from nodes import init_extra_nodes
-    sys.path.insert(0, find_path("ComfyUI"))
+    if comfyui_path in sys.path:
+        sys.path.remove(comfyui_path)
+    sys.path.insert(0, comfyui_path)
     import server
 
     # Creating a new event loop and setting it as the default loop
@@ -57,9 +71,11 @@ def add_comfyui_directory_to_sys_path() -> None:
     """
     Add 'ComfyUI' to the sys.path
     """
-    comfyui_path = find_path("ComfyUI")
+    comfyui_path = get_comfyui_path()
     if comfyui_path is not None and os.path.isdir(comfyui_path):
-        sys.path.append(comfyui_path)
+        if comfyui_path in sys.path:
+            sys.path.remove(comfyui_path)
+        sys.path.insert(0, comfyui_path)
         print(f"'{comfyui_path}' added to sys.path")
 
 

js/save-as-script.js

@@ -29,7 +29,12 @@ const extension = {
 		}
 		
 		app.graphToPrompt().then(async (p) => {
-			const json = JSON.stringify({name: filename + ".json", workflow: JSON.stringify(p.output, null, 2)}, null, 2); // convert the data to a JSON string
+			const frontendWorkflow = p.workflow ?? app.graph.serialize();
+			const json = JSON.stringify({
+				name: filename + ".json",
+				workflow: JSON.stringify(p.output, null, 2),
+				frontend_workflow: JSON.stringify(frontendWorkflow, null, 2),
+			}, null, 2); // convert the data to a JSON string
 			var response = await api.fetchApi(`/saveasscript`, { method: "POST", body: json });
 			if(response.status == 200) {
 				const blob = new Blob([await response.text()], {type: "text/python;charset=utf-8"});

tests/README.md

@@ -0,0 +1,112 @@
+# Tests
+
+This directory contains two test paths:
+
+- unit tests for exporter behavior
+- runtime validation for committed workflow fixtures
+
+## Prerequisites
+
+- Run commands from the repo root.
+- Use `uv` for all project commands.
+- Install the repo environment first:
+
+```bash
+uv sync
+```
+
+- Runtime validation also needs a working ComfyUI checkout.
+  Set `COMFYUI_PATH` to that checkout, or run the tests from a location where a parent directory contains `ComfyUI`.
+- Runtime-tier tests do not download missing models automatically.
+  If a required model is missing, the fixture fails with `model provisioning failure`.
+  Use `--print-download-plan` to print the manual download commands.
+
+### Runtime Model Requirements
+
+The current runtime-capable fixtures require these model files in the target ComfyUI checkout:
+
+- `text-to-image`: `models/checkpoints/v1-5-pruned-emaonly-fp16.safetensors`
+- `upscale-model-loader`: `models/upscale_models/RealESRGAN_x4plus.safetensors`
+
+## Unit Tests
+
+Run the current unit test module:
+
+```bash
+uv run python -m unittest tests.test_upscale_model_loader_export
+```
+
+Run all `unittest`-discoverable tests under `tests`:
+
+```bash
+uv run python -m unittest discover -s tests
+```
+
+## Runtime Tests
+
+The runtime harness lives at `tests/runtime/run_runtime_validation.py`.
+
+### Fast Tier
+
+Fast tier validates export behavior against committed fixtures without requiring a full ComfyUI runtime for every fixture.
+
+Run all fast-tier compatible fixtures:
+
+```bash
+uv run python tests/runtime/run_runtime_validation.py --tier fast --fixture all
+```
+
+Run one fixture:
+
+```bash
+uv run python tests/runtime/run_runtime_validation.py --tier fast --fixture unsafe-kwargs
+```
+
+### Runtime Tier
+
+Runtime tier exports inside a real ComfyUI checkout and executes generated Python for runtime-capable fixtures.
+
+Run all runtime-capable fixtures:
+
+```bash
+uv run python tests/runtime/run_runtime_validation.py --tier runtime --fixture all
+```
+
+Run one runtime-capable fixture:
+
+```bash
+uv run python tests/runtime/run_runtime_validation.py --tier runtime --fixture text-to-image
+```
+
+Print download commands for missing models instead of failing immediately:
+
+```bash
+uv run python tests/runtime/run_runtime_validation.py --tier runtime --fixture all --print-download-plan
+```
+
+## Runtime Fixture Names
+
+Current committed fixtures:
+
+- `upscale-model-loader`
+- `text-to-image`
+- `unsafe-kwargs`
+- `subgraph-identifiers`
+
+Notes:
+
+- `--tier runtime` only runs fixtures marked runtime-capable.
+- `--tier fast` only runs fixtures with local test mappings.
+
+## Troubleshooting
+
+- `No module named ...`:
+  run `uv sync` in this repo, and for runtime-tier failures also make sure the target ComfyUI checkout has its own dependencies installed.
+- `Could not find a valid ComfyUI checkout for runtime validation.`:
+  set `COMFYUI_PATH` to your ComfyUI checkout, or run the tests from a directory layout where a parent folder contains `ComfyUI`.
+- `Missing models for ...`:
+  runtime-tier tests do not fetch models for you. Rerun with `--print-download-plan` to print the expected `curl` commands and target model directories, then install the files manually.
+- `No selected fixtures are runtime-capable for this tier.`:
+  choose a runtime-capable fixture such as `text-to-image` or `upscale-model-loader`.
+- Generated script execution fails because files or models are missing:
+  confirm the required models exist under the target ComfyUI checkout and that any staged inputs can be copied into its `input/` directory.

tests/fixtures/runtime/subgraph-identifiers.json

@@ -0,0 +1,19 @@
+{
+  "173:132": {
+    "class_type": "RegexReplace",
+    "inputs": {
+      "text": "abc123",
+      "pattern": "\\d+",
+      "replace": "X"
+    }
+  },
+  "174:133": {
+    "class_type": "PassthroughText",
+    "inputs": {
+      "text": [
+        "173:132",
+        0
+      ]
+    }
+  }
+}

tests/fixtures/runtime/text-to-image.json

@@ -0,0 +1,86 @@
+{
+  "1": {
+    "class_type": "CheckpointLoaderSimple",
+    "inputs": {
+      "ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"
+    }
+  },
+  "2": {
+    "class_type": "CLIPTextEncode",
+    "inputs": {
+      "text": "a small cottage in a meadow, soft daylight",
+      "clip": [
+        "1",
+        1
+      ]
+    }
+  },
+  "3": {
+    "class_type": "CLIPTextEncode",
+    "inputs": {
+      "text": "blurry, low quality",
+      "clip": [
+        "1",
+        1
+      ]
+    }
+  },
+  "4": {
+    "class_type": "EmptyLatentImage",
+    "inputs": {
+      "width": 512,
+      "height": 512,
+      "batch_size": 1
+    }
+  },
+  "5": {
+    "class_type": "KSampler",
+    "inputs": {
+      "seed": 1,
+      "steps": 4,
+      "cfg": 7,
+      "sampler_name": "euler",
+      "scheduler": "normal",
+      "denoise": 1,
+      "model": [
+        "1",
+        0
+      ],
+      "positive": [
+        "2",
+        0
+      ],
+      "negative": [
+        "3",
+        0
+      ],
+      "latent_image": [
+        "4",
+        0
+      ]
+    }
+  },
+  "6": {
+    "class_type": "VAEDecode",
+    "inputs": {
+      "samples": [
+        "5",
+        0
+      ],
+      "vae": [
+        "1",
+        2
+      ]
+    }
+  },
+  "7": {
+    "class_type": "SaveImage",
+    "inputs": {
+      "filename_prefix": "E2E_text_to_image",
+      "images": [
+        "6",
+        0
+      ]
+    }
+  }
+}

tests/fixtures/runtime/unsafe-kwargs.json

@@ -0,0 +1,11 @@
+{
+  "1": {
+    "class_type": "FlexibleNode",
+    "inputs": {
+      "safe_name": "kept-readable",
+      "class": "reserved-word",
+      "\u2795 Add Lora": "symbol-heavy-key",
+      "spaces and-hyphens": "still-unsafe"
+    }
+  }
+}

tests/fixtures/runtime/upscale-model-loader.json

@@ -0,0 +1,37 @@
+{
+  "1": {
+    "class_type": "LoadImage",
+    "inputs": {
+      "image": "e2e_upscale_input.png"
+    }
+  },
+  "2": {
+    "class_type": "UpscaleModelLoader",
+    "inputs": {
+      "model_name": "RealESRGAN_x4plus.safetensors"
+    }
+  },
+  "3": {
+    "class_type": "ImageUpscaleWithModel",
+    "inputs": {
+      "upscale_model": [
+        "2",
+        0
+      ],
+      "image": [
+        "1",
+        0
+      ]
+    }
+  },
+  "4": {
+    "class_type": "SaveImage",
+    "inputs": {
+      "filename_prefix": "E2E_upscale_model_loader",
+      "images": [
+        "3",
+        0
+      ]
+    }
+  }
+}

tests/runtime/run_runtime_validation.py

@@ -0,0 +1,691 @@
+import argparse
+import ast
+import json
+import os
+import shutil
+import struct
+import subprocess
+import sys
+import tempfile
+import zlib
+from dataclasses import dataclass
+from io import StringIO
+from pathlib import Path
+from typing import Callable
+
+ROOT = Path(__file__).resolve().parents[2]
+FIXTURE_DIR = ROOT / "tests" / "fixtures" / "runtime"
+GENERATED_DIR = ROOT / "tests" / "runtime" / "generated"
+COMFYUI_OUTPUT_DIRNAME = "output"
+COMFYUI_INPUT_DIRNAME = "input"
+
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+from comfyui_to_python_utils import get_comfyui_path
+
+
+class ValidationFailure(RuntimeError):
+    def __init__(self, classification: str, message: str):
+        super().__init__(message)
+        self.classification = classification
+        self.message = message
+
+
+@dataclass(frozen=True)
+class FixtureConfig:
+    name: str
+    path: Path
+    mapping_factory: Callable[[], dict] | None = None
+    fast_mapping_factory: Callable[[], dict] | None = None
+    runtime_capable: bool = False
+    filename_prefix: str | None = None
+    expected_min_dimensions: tuple[int, int] | None = None
+    metadata_markers: tuple[str, ...] = ()
+    model_requirements: tuple["ModelRequirement", ...] = ()
+    staged_inputs: tuple["StagedInput", ...] = ()
+
+
+@dataclass(frozen=True)
+class ModelRequirement:
+    filename: str
+    relative_dir: str
+    source_url: str
+
+
+@dataclass(frozen=True)
+class StagedInput:
+    source_path: Path
+    destination_name: str
+
+
+class FlexibleNode:
+    CATEGORY = "utils"
+    FUNCTION = "run"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "safe_name": ("STRING",),
+            }
+        }
+
+    def run(self, **kwargs):
+        return (kwargs,)
+
+
+class RegexReplace:
+    CATEGORY = "utils"
+    FUNCTION = "replace"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": ("STRING",),
+                "pattern": ("STRING",),
+                "replace": ("STRING",),
+            }
+        }
+
+    def replace(self, text, pattern, replace):
+        return (text,)
+
+
+class PassthroughText:
+    CATEGORY = "utils"
+    FUNCTION = "run"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": ("STRING",),
+            }
+        }
+
+    def run(self, text):
+        return (text,)
+
+
+class UpscaleModelLoader:
+    CATEGORY = "loaders"
+    FUNCTION = "load_model"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "model_name": ("STRING",),
+            }
+        }
+
+    def load_model(self, model_name):
+        return (model_name,)
+
+
+class LoadImage:
+    CATEGORY = "image"
+    FUNCTION = "load_image"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("STRING",),
+            }
+        }
+
+    def load_image(self, image):
+        return (image,)
+
+
+class ImageUpscaleWithModel:
+    CATEGORY = "image/upscaling"
+    FUNCTION = "upscale"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "upscale_model": ("UPSCALE_MODEL",),
+                "image": ("IMAGE",),
+            }
+        }
+
+    def upscale(self, upscale_model, image):
+        return (image,)
+
+
+class SaveImageNode:
+    CATEGORY = "image"
+    FUNCTION = "save_images"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "filename_prefix": ("STRING",),
+            }
+        }
+
+    def save_images(self, images, filename_prefix):
+        return ()
+
+
+FIXTURES = {
+    # Runtime-capable fixtures are exported inside a real ComfyUI checkout and
+    # then executed end-to-end. Fast fixtures use local stub mappings so the
+    # exporter can be validated without importing the full runtime.
+    "upscale-model-loader": FixtureConfig(
+        name="upscale-model-loader",
+        path=FIXTURE_DIR / "upscale-model-loader.json",
+        fast_mapping_factory=lambda: {
+            "LoadImage": LoadImage,
+            "UpscaleModelLoader": UpscaleModelLoader,
+            "ImageUpscaleWithModel": ImageUpscaleWithModel,
+            "SaveImage": SaveImageNode,
+        },
+        runtime_capable=True,
+        filename_prefix="E2E_upscale_model_loader",
+        expected_min_dimensions=(1000, 1000),
+        metadata_markers=("UpscaleModelLoader", "E2E_upscale_model_loader"),
+        model_requirements=(
+            ModelRequirement(
+                filename="RealESRGAN_x4plus.safetensors",
+                relative_dir="models/upscale_models",
+                source_url="https://huggingface.co/Comfy-Org/Real-ESRGAN_repackaged/resolve/main/RealESRGAN_x4plus.safetensors",
+            ),
+        ),
+        staged_inputs=(
+            StagedInput(
+                source_path=ROOT / "images" / "save_as_script.png",
+                destination_name="e2e_upscale_input.png",
+            ),
+        ),
+    ),
+    "text-to-image": FixtureConfig(
+        name="text-to-image",
+        path=FIXTURE_DIR / "text-to-image.json",
+        runtime_capable=True,
+        filename_prefix="E2E_text_to_image",
+        expected_min_dimensions=(512, 512),
+        metadata_markers=("a small cottage in a meadow", "CheckpointLoaderSimple"),
+        model_requirements=(
+            ModelRequirement(
+                filename="v1-5-pruned-emaonly-fp16.safetensors",
+                relative_dir="models/checkpoints",
+                source_url="https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/resolve/main/v1-5-pruned-emaonly-fp16.safetensors",
+            ),
+        ),
+    ),
+    "unsafe-kwargs": FixtureConfig(
+        name="unsafe-kwargs",
+        path=FIXTURE_DIR / "unsafe-kwargs.json",
+        mapping_factory=lambda: {"FlexibleNode": FlexibleNode},
+    ),
+    "subgraph-identifiers": FixtureConfig(
+        name="subgraph-identifiers",
+        path=FIXTURE_DIR / "subgraph-identifiers.json",
+        mapping_factory=lambda: {
+            "RegexReplace": RegexReplace,
+            "PassthroughText": PassthroughText,
+        },
+    ),
+}
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Run fast or runtime validation for committed fixtures."
+    )
+    parser.add_argument(
+        "--tier",
+        choices=("fast", "runtime"),
+        help="Validation tier to run.",
+    )
+    parser.add_argument(
+        "--fixture",
+        default="all",
+        help="Fixture name or 'all'.",
+    )
+    parser.add_argument(
+        "--execute",
+        action="store_true",
+        help="Execute generated Python for runtime-capable fixtures.",
+    )
+    parser.add_argument(
+        "--print-download-plan",
+        action="store_true",
+        help="Print model download commands for missing models.",
+    )
+    parser.add_argument(
+        "--internal-export",
+        choices=tuple(FIXTURES.keys()),
+        help=argparse.SUPPRESS,
+    )
+    parser.add_argument(
+        "--generated-path",
+        help=argparse.SUPPRESS,
+    )
+    args = parser.parse_args()
+    if not args.internal_export and not args.tier:
+        parser.error("--tier is required unless --internal-export is used.")
+    return args
+
+
+def load_fixture_names(selection: str) -> list[str]:
+    if selection == "all":
+        return list(FIXTURES.keys())
+    if selection not in FIXTURES:
+        raise ValidationFailure("fixture bug", f"Unknown fixture '{selection}'.")
+    return [selection]
+
+
+def ensure_runtime_path(tier: str) -> str:
+    if tier == "runtime":
+        runtime_path = get_comfyui_path()
+    else:
+        return os.environ.get("COMFYUI_PATH", "")
+
+    if not runtime_path or not Path(runtime_path).is_dir():
+        raise ValidationFailure(
+            "environment/setup failure",
+            "Could not find a valid ComfyUI checkout for runtime validation. "
+            "Set COMFYUI_PATH or run the tests from a location where a "
+            "parent directory contains ComfyUI.",
+        )
+
+    return str(runtime_path)
+
+
+def get_runtime_python(runtime_path: str) -> str:
+    runtime_python = Path(runtime_path) / ".venv" / "bin" / "python"
+    if runtime_python.is_file():
+        return str(runtime_python)
+    return sys.executable
+
+
+def get_fixture(fixture_name: str) -> FixtureConfig:
+    return FIXTURES[fixture_name]
+
+
+def check_models(fixture: FixtureConfig, runtime_path: str) -> list[ModelRequirement]:
+    runtime_root = Path(runtime_path)
+    missing = []
+    for requirement in fixture.model_requirements:
+        target = runtime_root / requirement.relative_dir / requirement.filename
+        if not target.is_file():
+            missing.append(requirement)
+    return missing
+
+
+def print_download_plan(fixture: FixtureConfig, runtime_path: str) -> None:
+    runtime_root = Path(runtime_path)
+    for requirement in check_models(fixture, runtime_path):
+        target_dir = runtime_root / requirement.relative_dir
+        print(
+            "download:",
+            f"mkdir -p {target_dir} && curl -L {requirement.source_url} -o {target_dir / requirement.filename}",
+        )
+
+
+def stage_inputs(fixture: FixtureConfig, runtime_path: str) -> None:
+    runtime_input_dir = Path(runtime_path) / COMFYUI_INPUT_DIRNAME
+    runtime_input_dir.mkdir(parents=True, exist_ok=True)
+    for staged_input in fixture.staged_inputs:
+        if not staged_input.source_path.is_file():
+            raise ValidationFailure(
+                "fixture bug",
+                f"Missing staged input source {staged_input.source_path} for {fixture.name}.",
+            )
+        shutil.copyfile(
+            staged_input.source_path,
+            runtime_input_dir / staged_input.destination_name,
+        )
+
+
+def export_workflow(
+    fixture: FixtureConfig,
+    tier: str,
+    runtime_path: str,
+) -> tuple[str, str]:
+    from comfyui_to_python import ComfyUItoPython
+
+    workflow = fixture.path.read_text(encoding="utf-8")
+    output = StringIO()
+    kwargs = {
+        "workflow": workflow,
+        "output_file": output,
+    }
+    if tier == "fast" and fixture.fast_mapping_factory is not None:
+        kwargs["node_class_mappings"] = fixture.fast_mapping_factory()
+    elif fixture.mapping_factory is not None:
+        kwargs["node_class_mappings"] = fixture.mapping_factory()
+    else:
+        os.environ["COMFYUI_PATH"] = runtime_path
+
+    try:
+        ComfyUItoPython(**kwargs)
+    except ModuleNotFoundError as exc:
+        missing_module = exc.name or "unknown"
+        raise ValidationFailure(
+            "environment/setup failure",
+            f"Missing runtime dependency '{missing_module}' while exporting {fixture.name}.",
+        ) from exc
+    except KeyError as exc:
+        raise ValidationFailure(
+            "repo regression",
+            f"Exporter failed to resolve workflow data for {fixture.name}: {exc}",
+        ) from exc
+    except Exception as exc:
+        raise ValidationFailure(
+            "repo regression",
+            f"Exporter failed for {fixture.name}: {exc}",
+        ) from exc
+
+    return workflow, output.getvalue()
+
+
+def export_workflow_in_runtime_env(fixture: FixtureConfig, runtime_path: str) -> str:
+    runtime_python = get_runtime_python(runtime_path)
+    GENERATED_DIR.mkdir(parents=True, exist_ok=True)
+    generated_path = GENERATED_DIR / f"{fixture.name}.py"
+    env = os.environ.copy()
+    env["COMFYUI_PATH"] = runtime_path
+    env["PYTHONPATH"] = os.pathsep.join([str(ROOT), env.get("PYTHONPATH", "")]).rstrip(
+        os.pathsep
+    )
+    # Re-enter this script under the runtime interpreter so export happens with
+    # the target ComfyUI checkout on sys.path, not just the repo's current venv.
+    result = subprocess.run(
+        [
+            runtime_python,
+            str(Path(__file__).resolve()),
+            "--internal-export",
+            fixture.name,
+            "--generated-path",
+            str(generated_path),
+        ],
+        cwd=ROOT,
+        env=env,
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        output = (result.stderr or result.stdout or "").strip()
+        classification = "environment/setup failure"
+        if (
+            "Missing runtime dependency" not in output
+            and "ModuleNotFoundError" not in output
+        ):
+            classification = "repo regression"
+        raise ValidationFailure(
+            classification,
+            f"Runtime export failed for {fixture.name}: {output}",
+        )
+    return generated_path.read_text(encoding="utf-8")
+
+
+def validate_generated_python(generated_code: str, fixture_name: str) -> None:
+    try:
+        ast.parse(generated_code)
+    except SyntaxError as exc:
+        raise ValidationFailure(
+            "repo regression",
+            f"Generated Python is not valid for {fixture_name}: {exc}",
+        ) from exc
+
+
+def parse_png_info(image_path: Path) -> tuple[int, int, dict[str, str]]:
+    with image_path.open("rb") as handle:
+        signature = handle.read(8)
+        if signature != b"\x89PNG\r\n\x1a\n":
+            raise ValidationFailure(
+                "environment/setup failure",
+                f"Expected PNG output for {image_path.name}, got a different file format.",
+            )
+
+        width = height = None
+        text_data: dict[str, str] = {}
+        while True:
+            length_bytes = handle.read(4)
+            if not length_bytes:
+                break
+            length = struct.unpack(">I", length_bytes)[0]
+            chunk_type = handle.read(4)
+            chunk_data = handle.read(length)
+            handle.read(4)
+
+            if chunk_type == b"IHDR":
+                width, height = struct.unpack(">II", chunk_data[:8])
+            elif chunk_type == b"tEXt":
+                key, value = chunk_data.split(b"\x00", 1)
+                text_data[key.decode("latin-1")] = value.decode("latin-1")
+            elif chunk_type == b"zTXt":
+                key, compressed = chunk_data.split(b"\x00", 1)
+                text_data[key.decode("latin-1")] = zlib.decompress(
+                    compressed[1:]
+                ).decode("latin-1")
+            elif chunk_type == b"iTXt":
+                parts = chunk_data.split(b"\x00", 5)
+                if len(parts) == 6:
+                    key = parts[0].decode("utf-8")
+                    compressed_flag = parts[1]
+                    value = parts[5]
+                    if compressed_flag == b"\x01":
+                        value = zlib.decompress(value)
+                    text_data[key] = value.decode("utf-8")
+            elif chunk_type == b"IEND":
+                break
+
+        if width is None or height is None:
+            raise ValidationFailure(
+                "environment/setup failure",
+                f"Could not read PNG dimensions from {image_path.name}.",
+            )
+
+    return width, height, text_data
+
+
+def validate_output_artifact(
+    fixture: FixtureConfig,
+    output_path: Path,
+) -> None:
+    # Read PNG metadata directly so artifact validation does not depend on
+    # optional imaging libraries inside the runtime environment.
+    width, height, metadata = parse_png_info(output_path)
+
+    if fixture.expected_min_dimensions is not None:
+        min_width, min_height = fixture.expected_min_dimensions
+        if width < min_width or height < min_height:
+            raise ValidationFailure(
+                "repo regression",
+                f"Output dimensions for {fixture.name} were {width}x{height}, expected at least {min_width}x{min_height}.",
+            )
+
+    metadata_blob = "\n".join(
+        [output_path.name] + [f"{key}={value}" for key, value in metadata.items()]
+    )
+    for marker in fixture.metadata_markers:
+        if marker not in metadata_blob:
+            raise ValidationFailure(
+                "repo regression",
+                f"Output metadata for {fixture.name} did not contain expected marker '{marker}'.",
+            )
+
+
+def execute_generated_python(
+    generated_code: str,
+    fixture: FixtureConfig,
+    runtime_path: str,
+) -> None:
+    if not fixture.runtime_capable:
+        raise ValidationFailure(
+            "fixture bug",
+            f"Fixture {fixture.name} is not marked runtime-capable.",
+        )
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        tmp_path = Path(tmpdir) / f"{fixture.name}.py"
+        tmp_path.write_text(generated_code, encoding="utf-8")
+        output_dir = Path(runtime_path) / COMFYUI_OUTPUT_DIRNAME
+        # Compare against the pre-run snapshot so validation can prove this
+        # execution created a fresh artifact instead of reusing an old output.
+        existing_outputs = set(output_dir.glob("*.png"))
+        env = os.environ.copy()
+        env["COMFYUI_PATH"] = runtime_path
+        env["PYTHONPATH"] = os.pathsep.join(
+            [str(ROOT), env.get("PYTHONPATH", "")]
+        ).rstrip(os.pathsep)
+        runtime_python = get_runtime_python(runtime_path)
+
+        result = subprocess.run(
+            [runtime_python, str(tmp_path)],
+            cwd=ROOT,
+            env=env,
+            capture_output=True,
+            text=True,
+        )
+        if result.returncode == 0:
+            if fixture.filename_prefix is None:
+                return
+            new_outputs = [
+                path
+                for path in output_dir.glob(f"{fixture.filename_prefix}*.png")
+                if path not in existing_outputs
+            ]
+            if not new_outputs:
+                raise ValidationFailure(
+                    "repo regression",
+                    f"Generated script for {fixture.name} did not produce a new output file with prefix {fixture.filename_prefix}.",
+                )
+            newest_output = max(new_outputs, key=lambda path: path.stat().st_mtime)
+            validate_output_artifact(fixture, newest_output)
+            return
+
+        stderr = (result.stderr or "").strip()
+        stdout = (result.stdout or "").strip()
+        output = stderr or stdout or "generated script exited with a non-zero status"
+        lower_output = output.lower()
+
+        if "no module named 'torch'" in lower_output:
+            classification = "environment/setup failure"
+        elif "no such file or directory" in lower_output or "not found" in lower_output:
+            classification = "environment/setup failure"
+        else:
+            classification = "repo regression"
+
+        raise ValidationFailure(
+            classification,
+            f"Generated script execution failed for {fixture.name}: {output}",
+        )
+
+
+def run_fixture(fixture: FixtureConfig, tier: str, execute: bool, runtime_path: str) -> str:
+    if tier == "fast":
+        _, generated_code = export_workflow(fixture, tier, runtime_path)
+    else:
+        missing_models = check_models(fixture, runtime_path)
+        if missing_models:
+            raise ValidationFailure(
+                "model provisioning failure",
+                "Missing models for "
+                f"{fixture.name}: "
+                + ", ".join(
+                    f"{item.relative_dir}/{item.filename}" for item in missing_models
+                ),
+            )
+        stage_inputs(fixture, runtime_path)
+        generated_code = export_workflow_in_runtime_env(fixture, runtime_path)
+    validate_generated_python(generated_code, fixture.name)
+
+    # Fast keeps execution opt-in because its stub node mappings are intended for
+    # export coverage only. Runtime always executes the generated script.
+    should_execute = execute or tier == "runtime"
+    if should_execute and tier == "runtime":
+        execute_generated_python(generated_code, fixture, runtime_path)
+
+    return "pass"
+
+
+def main() -> int:
+    args = parse_args()
+
+    if args.internal_export:
+        fixture = get_fixture(args.internal_export)
+        output_path = Path(args.generated_path)
+        _, generated_code = export_workflow(
+            fixture=fixture,
+            tier="runtime",
+            runtime_path=os.environ.get("COMFYUI_PATH", ""),
+        )
+        output_path.write_text(generated_code, encoding="utf-8")
+        return 0
+
+    try:
+        runtime_path = ensure_runtime_path(args.tier)
+        fixture_names = load_fixture_names(args.fixture)
+        requested = [FIXTURES[name] for name in fixture_names]
+
+        if args.tier == "fast":
+            requested = [
+                fixture
+                for fixture in requested
+                if fixture.fast_mapping_factory is not None
+                or fixture.mapping_factory is not None
+            ]
+            if not requested:
+                raise ValidationFailure(
+                    "fixture bug",
+                    "No selected fixtures are fast-tier compatible.",
+                )
+        elif args.tier == "runtime":
+            requested = [fixture for fixture in requested if fixture.runtime_capable]
+            if not requested:
+                raise ValidationFailure(
+                    "fixture bug",
+                    "No selected fixtures are runtime-capable for this tier.",
+                )
+
+        failures: list[tuple[str, str, str]] = []
+        for fixture in requested:
+            try:
+                if args.print_download_plan and args.tier == "runtime":
+                    missing_models = check_models(fixture, runtime_path)
+                    for requirement in missing_models:
+                        target_dir = Path(runtime_path) / requirement.relative_dir
+                        print(
+                            "download:",
+                            f"mkdir -p {target_dir} && curl -L {requirement.source_url} -o {target_dir / requirement.filename}",
+                        )
+                    if missing_models:
+                        print(f"{fixture.name}: download-plan")
+                        continue
+                status = run_fixture(fixture, args.tier, args.execute, runtime_path)
+                print(f"{fixture.name}: {status}")
+            except ValidationFailure as exc:
+                failures.append((fixture.name, exc.classification, exc.message))
+                print(
+                    f"{fixture.name}: fail ({exc.classification})",
+                    file=sys.stderr,
+                )
+                print(exc.message, file=sys.stderr)
+        if failures:
+            classifications = ", ".join(
+                f"{name}={classification}" for name, classification, _ in failures
+            )
+            print(f"classification: {classifications}", file=sys.stderr)
+            return 1
+    except ValidationFailure as exc:
+        print(f"classification: {exc.classification}", file=sys.stderr)
+        print(exc.message, file=sys.stderr)
+        return 1
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

tests/test_upscale_model_loader_export.py

@@ -0,0 +1,364 @@
+import json
+import tempfile
+import unittest
+from io import StringIO
+from pathlib import Path
+from unittest.mock import patch
+
+from comfyui_to_python import ComfyUItoPython, run
+
+
+class UpscaleModelLoader:
+    CATEGORY = "loaders"
+    FUNCTION = "load_model"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "model_name": ("STRING",),
+            }
+        }
+
+    def load_model(self, model_name):
+        return (model_name,)
+
+
+class LoadImage:
+    CATEGORY = "image"
+    FUNCTION = "load_image"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("STRING",),
+            }
+        }
+
+    def load_image(self, image):
+        return (image,)
+
+
+class ImageUpscaleWithModel:
+    CATEGORY = "image/upscaling"
+    FUNCTION = "upscale"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "upscale_model": ("UPSCALE_MODEL",),
+                "image": ("IMAGE",),
+            }
+        }
+
+    def upscale(self, upscale_model, image):
+        return (image,)
+
+
+class MergeImages:
+    CATEGORY = "image"
+    FUNCTION = "merge"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "left": ("IMAGE",),
+                "right": ("IMAGE",),
+            }
+        }
+
+    def merge(self, left, right):
+        return (left, right)
+
+
+class HiddenMetadataFilteredNode:
+    CATEGORY = "image"
+    FUNCTION = "save"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO",
+            },
+        }
+
+    def save(self, image):
+        return (image,)
+
+
+class HiddenPromptSeedNode:
+    CATEGORY = "sampling"
+    FUNCTION = "sample"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "seed": ("INT",),
+                "noise_seed": ("INT",),
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+            },
+        }
+
+    def sample(self, seed, noise_seed, prompt):
+        return (seed, noise_seed, prompt)
+
+
+class UpscaleModelLoaderExportTest(unittest.TestCase):
+    def test_upscale_workflow_uses_direct_upscale_model_loader_init(self):
+        workflow = {
+            "1": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "example.png",
+                },
+            },
+            "2": {
+                "class_type": "UpscaleModelLoader",
+                "inputs": {
+                    "model_name": "RealESRGAN_x4plus.safetensors",
+                },
+            },
+            "3": {
+                "class_type": "ImageUpscaleWithModel",
+                "inputs": {
+                    "upscale_model": ["2", 0],
+                    "image": ["1", 0],
+                },
+            },
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            output_file=output,
+            node_class_mappings={
+                "LoadImage": LoadImage,
+                "UpscaleModelLoader": UpscaleModelLoader,
+                "ImageUpscaleWithModel": ImageUpscaleWithModel,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn("from nodes import NODE_CLASS_MAPPINGS", generated)
+        self.assertIn(f"from {LoadImage.__module__} import (", generated)
+        self.assertIn("LoadImage,", generated)
+        self.assertIn("UpscaleModelLoader,", generated)
+        self.assertIn("ImageUpscaleWithModel,", generated)
+        self.assertIn("loadimage = LoadImage()", generated)
+        self.assertIn("upscalemodelloader = UpscaleModelLoader()", generated)
+        self.assertIn(
+            "imageupscalewithmodel_3 = imageupscalewithmodel.upscale(",
+            generated,
+        )
+        self.assertNotIn('NODE_CLASS_MAPPINGS["UpscaleModelLoader"]()', generated)
+
+    def test_frontend_workflow_metadata_is_embedded_for_reimport(self):
+        workflow = {
+            "1": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "example.png",
+                },
+            }
+        }
+        frontend_workflow = {
+            "version": 0.4,
+            "last_node_id": 1,
+            "last_link_id": 0,
+            "nodes": [],
+            "links": [],
+            "groups": [],
+            "config": {},
+            "extra": {},
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            frontend_workflow=json.dumps(frontend_workflow),
+            output_file=output,
+            node_class_mappings={
+                "LoadImage": LoadImage,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn('extra_pnginfo = {', generated)
+        self.assertIn('"workflow": json.loads(', generated)
+        self.assertIn('"version": 0.4', generated)
+        self.assertIn('"nodes": []', generated)
+        self.assertNotIn('"source": "workflow_api"', generated)
+
+    def test_export_without_frontend_workflow_leaves_png_workflow_metadata_absent(self):
+        workflow = {
+            "1": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "example.png",
+                },
+            }
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            output_file=output,
+            node_class_mappings={
+                "LoadImage": LoadImage,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn("extra_pnginfo = None", generated)
+        self.assertNotIn('"workflow": json.loads(', generated)
+
+    def test_export_preserves_unique_variable_names_for_subgraph_node_ids(self):
+        workflow = {
+            "1:23": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "left.png",
+                },
+            },
+            "12:3": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "right.png",
+                },
+            },
+            "20": {
+                "class_type": "MergeImages",
+                "inputs": {
+                    "left": ["1:23", 0],
+                    "right": ["12:3", 0],
+                },
+            },
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            output_file=output,
+            node_class_mappings={
+                "LoadImage": LoadImage,
+                "MergeImages": MergeImages,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn("loadimage_1_23 = loadimage.load_image(", generated)
+        self.assertIn("loadimage_12_3 = loadimage.load_image(", generated)
+        self.assertIn("mergeimages_20 = mergeimages.merge(", generated)
+        self.assertIn("left=get_value_at_index(loadimage_1_23, 0)", generated)
+        self.assertIn("right=get_value_at_index(loadimage_12_3, 0)", generated)
+
+    def test_run_cli_export_leaves_png_workflow_metadata_absent(self):
+        workflow = {
+            "1": {
+                "class_type": "LoadImage",
+                "inputs": {
+                    "image": "example.png",
+                },
+            }
+        }
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            tmpdir_path = Path(tmpdir)
+            input_file = tmpdir_path / "workflow_api.json"
+            output_file = tmpdir_path / "workflow_api.py"
+
+            input_file.write_text(json.dumps(workflow), encoding="utf-8")
+
+            with patch(
+                "comfyui_to_python.get_node_class_mappings",
+                return_value={"LoadImage": LoadImage},
+            ), patch("comfyui_to_python.import_custom_nodes"):
+                run(
+                    input_file=str(input_file),
+                    output_file=str(output_file),
+                    queue_size=1,
+                )
+
+            generated = output_file.read_text(encoding="utf-8")
+
+        self.assertIn("extra_pnginfo = None", generated)
+        self.assertNotIn('"workflow": json.loads(', generated)
+
+    def test_hidden_metadata_kwargs_follow_function_signature(self):
+        workflow = {
+            "1": {
+                "class_type": "HiddenMetadataFilteredNode",
+                "inputs": {
+                    "image": "example.png",
+                },
+            }
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            output_file=output,
+            node_class_mappings={
+                "HiddenMetadataFilteredNode": HiddenMetadataFilteredNode,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn("hiddenmetadatafilterednode_1 =", generated)
+        self.assertNotIn("prompt=prompt", generated)
+        self.assertNotIn("extra_pnginfo=extra_pnginfo", generated)
+
+    def test_randomized_seed_inputs_update_prompt_metadata_before_execution(self):
+        workflow = {
+            "1": {
+                "class_type": "HiddenPromptSeedNode",
+                "inputs": {
+                    "seed": 1,
+                    "noise_seed": 2,
+                },
+            }
+        }
+
+        output = StringIO()
+        ComfyUItoPython(
+            workflow=json.dumps(workflow),
+            output_file=output,
+            node_class_mappings={
+                "HiddenPromptSeedNode": HiddenPromptSeedNode,
+            },
+        )
+
+        generated = output.getvalue()
+
+        self.assertIn(
+            'node_1_seed = prompt["1"]["inputs"]["seed"] = random.randint(1, 2**64)',
+            generated,
+        )
+        self.assertIn(
+            'node_1_noise_seed = prompt["1"]["inputs"]["noise_seed"] = random.randint(',
+            generated,
+        )
+        self.assertIn("1, 2**64", generated)
+        self.assertIn("seed=node_1_seed", generated)
+        self.assertIn("noise_seed=node_1_noise_seed", generated)
+        self.assertIn("prompt=prompt", generated)
+
+
+if __name__ == "__main__":
+    unittest.main()

uv.lock

@@ -0,0 +1,132 @@
+version = 1
+revision = 3
+requires-python = ">=3.12"
+
+[[package]]
+name = "black"
+version = "26.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "mypy-extensions" },
+    { name = "packaging" },
+    { name = "pathspec" },
+    { name = "platformdirs" },
+    { name = "pytokens" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e1/c5/61175d618685d42b005847464b8fb4743a67b1b8fdb75e50e5a96c31a27a/black-26.3.1.tar.gz", hash = "sha256:2c50f5063a9641c7eed7795014ba37b0f5fa227f3d408b968936e24bc0566b07", size = 666155, upload-time = "2026-03-12T03:36:03.593Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/dc/f8/da5eae4fc75e78e6dceb60624e1b9662ab00d6b452996046dfa9b8a6025b/black-26.3.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b5e6f89631eb88a7302d416594a32faeee9fb8fb848290da9d0a5f2903519fc1", size = 1895920, upload-time = "2026-03-12T03:40:13.921Z" },
+    { url = "https://files.pythonhosted.org/packages/2c/9f/04e6f26534da2e1629b2b48255c264cabf5eedc5141d04516d9d68a24111/black-26.3.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:41cd2012d35b47d589cb8a16faf8a32ef7a336f56356babd9fcf70939ad1897f", size = 1718499, upload-time = "2026-03-12T03:40:15.239Z" },
+    { url = "https://files.pythonhosted.org/packages/04/91/a5935b2a63e31b331060c4a9fdb5a6c725840858c599032a6f3aac94055f/black-26.3.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0f76ff19ec5297dd8e66eb64deda23631e642c9393ab592826fd4bdc97a4bce7", size = 1794994, upload-time = "2026-03-12T03:40:17.124Z" },
+    { url = "https://files.pythonhosted.org/packages/e7/0a/86e462cdd311a3c2a8ece708d22aba17d0b2a0d5348ca34b40cdcbea512e/black-26.3.1-cp312-cp312-win_amd64.whl", hash = "sha256:ddb113db38838eb9f043623ba274cfaf7d51d5b0c22ecb30afe58b1bb8322983", size = 1420867, upload-time = "2026-03-12T03:40:18.83Z" },
+    { url = "https://files.pythonhosted.org/packages/5b/e5/22515a19cb7eaee3440325a6b0d95d2c0e88dd180cb011b12ae488e031d1/black-26.3.1-cp312-cp312-win_arm64.whl", hash = "sha256:dfdd51fc3e64ea4f35873d1b3fb25326773d55d2329ff8449139ebaad7357efb", size = 1230124, upload-time = "2026-03-12T03:40:20.425Z" },
+    { url = "https://files.pythonhosted.org/packages/f5/77/5728052a3c0450c53d9bb3945c4c46b91baa62b2cafab6801411b6271e45/black-26.3.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:855822d90f884905362f602880ed8b5df1b7e3ee7d0db2502d4388a954cc8c54", size = 1895034, upload-time = "2026-03-12T03:40:21.813Z" },
+    { url = "https://files.pythonhosted.org/packages/52/73/7cae55fdfdfbe9d19e9a8d25d145018965fe2079fa908101c3733b0c55a0/black-26.3.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:8a33d657f3276328ce00e4d37fe70361e1ec7614da5d7b6e78de5426cb56332f", size = 1718503, upload-time = "2026-03-12T03:40:23.666Z" },
+    { url = "https://files.pythonhosted.org/packages/e1/87/af89ad449e8254fdbc74654e6467e3c9381b61472cc532ee350d28cfdafb/black-26.3.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f1cd08e99d2f9317292a311dfe578fd2a24b15dbce97792f9c4d752275c1fa56", size = 1793557, upload-time = "2026-03-12T03:40:25.497Z" },
+    { url = "https://files.pythonhosted.org/packages/43/10/d6c06a791d8124b843bf325ab4ac7d2f5b98731dff84d6064eafd687ded1/black-26.3.1-cp313-cp313-win_amd64.whl", hash = "sha256:c7e72339f841b5a237ff14f7d3880ddd0fc7f98a1199e8c4327f9a4f478c1839", size = 1422766, upload-time = "2026-03-12T03:40:27.14Z" },
+    { url = "https://files.pythonhosted.org/packages/59/4f/40a582c015f2d841ac24fed6390bd68f0fc896069ff3a886317959c9daf8/black-26.3.1-cp313-cp313-win_arm64.whl", hash = "sha256:afc622538b430aa4c8c853f7f63bc582b3b8030fd8c80b70fb5fa5b834e575c2", size = 1232140, upload-time = "2026-03-12T03:40:28.882Z" },
+    { url = "https://files.pythonhosted.org/packages/d5/da/e36e27c9cebc1311b7579210df6f1c86e50f2d7143ae4fcf8a5017dc8809/black-26.3.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:2d6bfaf7fd0993b420bed691f20f9492d53ce9a2bcccea4b797d34e947318a78", size = 1889234, upload-time = "2026-03-12T03:40:30.964Z" },
+    { url = "https://files.pythonhosted.org/packages/0e/7b/9871acf393f64a5fa33668c19350ca87177b181f44bb3d0c33b2d534f22c/black-26.3.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:f89f2ab047c76a9c03f78d0d66ca519e389519902fa27e7a91117ef7611c0568", size = 1720522, upload-time = "2026-03-12T03:40:32.346Z" },
+    { url = "https://files.pythonhosted.org/packages/03/87/e766c7f2e90c07fb7586cc787c9ae6462b1eedab390191f2b7fc7f6170a9/black-26.3.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b07fc0dab849d24a80a29cfab8d8a19187d1c4685d8a5e6385a5ce323c1f015f", size = 1787824, upload-time = "2026-03-12T03:40:33.636Z" },
+    { url = "https://files.pythonhosted.org/packages/ac/94/2424338fb2d1875e9e83eed4c8e9c67f6905ec25afd826a911aea2b02535/black-26.3.1-cp314-cp314-win_amd64.whl", hash = "sha256:0126ae5b7c09957da2bdbd91a9ba1207453feada9e9fe51992848658c6c8e01c", size = 1445855, upload-time = "2026-03-12T03:40:35.442Z" },
+    { url = "https://files.pythonhosted.org/packages/86/43/0c3338bd928afb8ee7471f1a4eec3bdbe2245ccb4a646092a222e8669840/black-26.3.1-cp314-cp314-win_arm64.whl", hash = "sha256:92c0ec1f2cc149551a2b7b47efc32c866406b6891b0ee4625e95967c8f4acfb1", size = 1258109, upload-time = "2026-03-12T03:40:36.832Z" },
+    { url = "https://files.pythonhosted.org/packages/8e/0d/52d98722666d6fc6c3dd4c76df339501d6efd40e0ff95e6186a7b7f0befd/black-26.3.1-py3-none-any.whl", hash = "sha256:2bd5aa94fc267d38bb21a70d7410a89f1a1d318841855f698746f8e7f51acd1b", size = 207542, upload-time = "2026-03-12T03:36:01.668Z" },
+]
+
+[[package]]
+name = "click"
+version = "8.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/3d/fa/656b739db8587d7b5dfa22e22ed02566950fbfbcdc20311993483657a5c0/click-8.3.1.tar.gz", hash = "sha256:12ff4785d337a1bb490bb7e9c2b1ee5da3112e94a8622f26a6c77f5d2fc6842a", size = 295065, upload-time = "2025-11-15T20:45:42.706Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/98/78/01c019cdb5d6498122777c1a43056ebb3ebfeef2076d9d026bfe15583b2b/click-8.3.1-py3-none-any.whl", hash = "sha256:981153a64e25f12d547d3426c367a4857371575ee7ad18df2a6183ab0545b2a6", size = 108274, upload-time = "2025-11-15T20:45:41.139Z" },
+]
+
+[[package]]
+name = "colorama"
+version = "0.4.6"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" },
+]
+
+[[package]]
+name = "comfyui-to-python-extension"
+version = "1.3.1"
+source = { virtual = "." }
+dependencies = [
+    { name = "black" },
+]
+
+[package.metadata]
+requires-dist = [{ name = "black" }]
+
+[[package]]
+name = "mypy-extensions"
+version = "1.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/a2/6e/371856a3fb9d31ca8dac321cda606860fa4548858c0cc45d9d1d4ca2628b/mypy_extensions-1.1.0.tar.gz", hash = "sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558", size = 6343, upload-time = "2025-04-22T14:54:24.164Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" },
+]
+
+[[package]]
+name = "packaging"
+version = "26.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/65/ee/299d360cdc32edc7d2cf530f3accf79c4fca01e96ffc950d8a52213bd8e4/packaging-26.0.tar.gz", hash = "sha256:00243ae351a257117b6a241061796684b084ed1c516a08c48a3f7e147a9d80b4", size = 143416, upload-time = "2026-01-21T20:50:39.064Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl", hash = "sha256:b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529", size = 74366, upload-time = "2026-01-21T20:50:37.788Z" },
+]
+
+[[package]]
+name = "pathspec"
+version = "1.0.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/fa/36/e27608899f9b8d4dff0617b2d9ab17ca5608956ca44461ac14ac48b44015/pathspec-1.0.4.tar.gz", hash = "sha256:0210e2ae8a21a9137c0d470578cb0e595af87edaa6ebf12ff176f14a02e0e645", size = 131200, upload-time = "2026-01-27T03:59:46.938Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ef/3c/2c197d226f9ea224a9ab8d197933f9da0ae0aac5b6e0f884e2b8d9c8e9f7/pathspec-1.0.4-py3-none-any.whl", hash = "sha256:fb6ae2fd4e7c921a165808a552060e722767cfa526f99ca5156ed2ce45a5c723", size = 55206, upload-time = "2026-01-27T03:59:45.137Z" },
+]
+
+[[package]]
+name = "platformdirs"
+version = "4.9.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/19/56/8d4c30c8a1d07013911a8fdbd8f89440ef9f08d07a1b50ab8ca8be5a20f9/platformdirs-4.9.4.tar.gz", hash = "sha256:1ec356301b7dc906d83f371c8f487070e99d3ccf9e501686456394622a01a934", size = 28737, upload-time = "2026-03-05T18:34:13.271Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/63/d7/97f7e3a6abb67d8080dd406fd4df842c2be0efaf712d1c899c32a075027c/platformdirs-4.9.4-py3-none-any.whl", hash = "sha256:68a9a4619a666ea6439f2ff250c12a853cd1cbd5158d258bd824a7df6be2f868", size = 21216, upload-time = "2026-03-05T18:34:12.172Z" },
+]
+
+[[package]]
+name = "pytokens"
+version = "0.4.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b6/34/b4e015b99031667a7b960f888889c5bd34ef585c85e1cb56a594b92836ac/pytokens-0.4.1.tar.gz", hash = "sha256:292052fe80923aae2260c073f822ceba21f3872ced9a68bb7953b348e561179a", size = 23015, upload-time = "2026-01-30T01:03:45.924Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/41/5d/e44573011401fb82e9d51e97f1290ceb377800fb4eed650b96f4753b499c/pytokens-0.4.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:140709331e846b728475786df8aeb27d24f48cbcf7bcd449f8de75cae7a45083", size = 160663, upload-time = "2026-01-30T01:03:06.473Z" },
+    { url = "https://files.pythonhosted.org/packages/f0/e6/5bbc3019f8e6f21d09c41f8b8654536117e5e211a85d89212d59cbdab381/pytokens-0.4.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6d6c4268598f762bc8e91f5dbf2ab2f61f7b95bdc07953b602db879b3c8c18e1", size = 255626, upload-time = "2026-01-30T01:03:08.177Z" },
+    { url = "https://files.pythonhosted.org/packages/bf/3c/2d5297d82286f6f3d92770289fd439956b201c0a4fc7e72efb9b2293758e/pytokens-0.4.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:24afde1f53d95348b5a0eb19488661147285ca4dd7ed752bbc3e1c6242a304d1", size = 269779, upload-time = "2026-01-30T01:03:09.756Z" },
+    { url = "https://files.pythonhosted.org/packages/20/01/7436e9ad693cebda0551203e0bf28f7669976c60ad07d6402098208476de/pytokens-0.4.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:5ad948d085ed6c16413eb5fec6b3e02fa00dc29a2534f088d3302c47eb59adf9", size = 268076, upload-time = "2026-01-30T01:03:10.957Z" },
+    { url = "https://files.pythonhosted.org/packages/2e/df/533c82a3c752ba13ae7ef238b7f8cdd272cf1475f03c63ac6cf3fcfb00b6/pytokens-0.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:3f901fe783e06e48e8cbdc82d631fca8f118333798193e026a50ce1b3757ea68", size = 103552, upload-time = "2026-01-30T01:03:12.066Z" },
+    { url = "https://files.pythonhosted.org/packages/cb/dc/08b1a080372afda3cceb4f3c0a7ba2bde9d6a5241f1edb02a22a019ee147/pytokens-0.4.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:8bdb9d0ce90cbf99c525e75a2fa415144fd570a1ba987380190e8b786bc6ef9b", size = 160720, upload-time = "2026-01-30T01:03:13.843Z" },
+    { url = "https://files.pythonhosted.org/packages/64/0c/41ea22205da480837a700e395507e6a24425151dfb7ead73343d6e2d7ffe/pytokens-0.4.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5502408cab1cb18e128570f8d598981c68a50d0cbd7c61312a90507cd3a1276f", size = 254204, upload-time = "2026-01-30T01:03:14.886Z" },
+    { url = "https://files.pythonhosted.org/packages/e0/d2/afe5c7f8607018beb99971489dbb846508f1b8f351fcefc225fcf4b2adc0/pytokens-0.4.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:29d1d8fb1030af4d231789959f21821ab6325e463f0503a61d204343c9b355d1", size = 268423, upload-time = "2026-01-30T01:03:15.936Z" },
+    { url = "https://files.pythonhosted.org/packages/68/d4/00ffdbd370410c04e9591da9220a68dc1693ef7499173eb3e30d06e05ed1/pytokens-0.4.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:970b08dd6b86058b6dc07efe9e98414f5102974716232d10f32ff39701e841c4", size = 266859, upload-time = "2026-01-30T01:03:17.458Z" },
+    { url = "https://files.pythonhosted.org/packages/a7/c9/c3161313b4ca0c601eeefabd3d3b576edaa9afdefd32da97210700e47652/pytokens-0.4.1-cp313-cp313-win_amd64.whl", hash = "sha256:9bd7d7f544d362576be74f9d5901a22f317efc20046efe2034dced238cbbfe78", size = 103520, upload-time = "2026-01-30T01:03:18.652Z" },
+    { url = "https://files.pythonhosted.org/packages/8f/a7/b470f672e6fc5fee0a01d9e75005a0e617e162381974213a945fcd274843/pytokens-0.4.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:4a14d5f5fc78ce85e426aa159489e2d5961acf0e47575e08f35584009178e321", size = 160821, upload-time = "2026-01-30T01:03:19.684Z" },
+    { url = "https://files.pythonhosted.org/packages/80/98/e83a36fe8d170c911f864bfded690d2542bfcfacb9c649d11a9e6eb9dc41/pytokens-0.4.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:97f50fd18543be72da51dd505e2ed20d2228c74e0464e4262e4899797803d7fa", size = 254263, upload-time = "2026-01-30T01:03:20.834Z" },
+    { url = "https://files.pythonhosted.org/packages/0f/95/70d7041273890f9f97a24234c00b746e8da86df462620194cef1d411ddeb/pytokens-0.4.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:dc74c035f9bfca0255c1af77ddd2d6ae8419012805453e4b0e7513e17904545d", size = 268071, upload-time = "2026-01-30T01:03:21.888Z" },
+    { url = "https://files.pythonhosted.org/packages/da/79/76e6d09ae19c99404656d7db9c35dfd20f2086f3eb6ecb496b5b31163bad/pytokens-0.4.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:f66a6bbe741bd431f6d741e617e0f39ec7257ca1f89089593479347cc4d13324", size = 271716, upload-time = "2026-01-30T01:03:23.633Z" },
+    { url = "https://files.pythonhosted.org/packages/79/37/482e55fa1602e0a7ff012661d8c946bafdc05e480ea5a32f4f7e336d4aa9/pytokens-0.4.1-cp314-cp314-win_amd64.whl", hash = "sha256:b35d7e5ad269804f6697727702da3c517bb8a5228afa450ab0fa787732055fc9", size = 104539, upload-time = "2026-01-30T01:03:24.788Z" },
+    { url = "https://files.pythonhosted.org/packages/30/e8/20e7db907c23f3d63b0be3b8a4fd1927f6da2395f5bcc7f72242bb963dfe/pytokens-0.4.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:8fcb9ba3709ff77e77f1c7022ff11d13553f3c30299a9fe246a166903e9091eb", size = 168474, upload-time = "2026-01-30T01:03:26.428Z" },
+    { url = "https://files.pythonhosted.org/packages/d6/81/88a95ee9fafdd8f5f3452107748fd04c24930d500b9aba9738f3ade642cc/pytokens-0.4.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:79fc6b8699564e1f9b521582c35435f1bd32dd06822322ec44afdeba666d8cb3", size = 290473, upload-time = "2026-01-30T01:03:27.415Z" },
+    { url = "https://files.pythonhosted.org/packages/cf/35/3aa899645e29b6375b4aed9f8d21df219e7c958c4c186b465e42ee0a06bf/pytokens-0.4.1-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d31b97b3de0f61571a124a00ffe9a81fb9939146c122c11060725bd5aea79975", size = 303485, upload-time = "2026-01-30T01:03:28.558Z" },
+    { url = "https://files.pythonhosted.org/packages/52/a0/07907b6ff512674d9b201859f7d212298c44933633c946703a20c25e9d81/pytokens-0.4.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:967cf6e3fd4adf7de8fc73cd3043754ae79c36475c1c11d514fc72cf5490094a", size = 306698, upload-time = "2026-01-30T01:03:29.653Z" },
+    { url = "https://files.pythonhosted.org/packages/39/2a/cbbf9250020a4a8dd53ba83a46c097b69e5eb49dd14e708f496f548c6612/pytokens-0.4.1-cp314-cp314t-win_amd64.whl", hash = "sha256:584c80c24b078eec1e227079d56dc22ff755e0ba8654d8383b2c549107528918", size = 116287, upload-time = "2026-01-30T01:03:30.912Z" },
+    { url = "https://files.pythonhosted.org/packages/c6/78/397db326746f0a342855b81216ae1f0a32965deccfd7c830a2dbc66d2483/pytokens-0.4.1-py3-none-any.whl", hash = "sha256:26cef14744a8385f35d0e095dc8b3a7583f6c953c2e3d269c7f82484bf5ad2de", size = 13729, upload-time = "2026-01-30T01:03:45.029Z" },
+]