Files
Lex-DRL-ComfyUI-StringConst…/node_dict_from_text.py
T

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2.2 KiB
Python

# encoding: utf-8
"""
"""
import typing as _t
from inspect import cleandoc as _cleandoc
from frozendict import frozendict as _frozendict, deepfreeze as _deepfreeze
from comfy.comfy_types.node_typing import IO as _IO
from . import _meta
from .docstring_formatter import format_docstring as _format_docstring
from .enums import DataTypes as _DataTypes
from .funcs_dict_from_text import parse_dict_from_text as _parse_dict_from_text
from .node_dict_add_string import _input_types as _input_types_str
# A tiny optimization by reusing the same immutable dict:
_input_types = _deepfreeze({
'required': {
'cleanup': (_IO.BOOLEAN, {'default': True, 'label_on': 'leading/trailing spaces', 'label_off': 'no', 'tooltip': (
"When enabled, each line in each sub-string is stripped from any spaces at its start and end."
)}),
'strings': (_IO.STRING, {'multiline': True, 'tooltip': (
"Sub-string names followed by their text. Different sub-string chunks are separated by empty lines. Example:\n\n"
"char1_short\n1boy, blond, short hair\n\n"
"char1_long\n1boy, smiling, blue eyes, blond, short hair,\nsitting on a motorcycle, wearing a leather jacket"
)}),
'show_status': (_IO.BOOLEAN, {'default': False, 'label_on': 'found names', 'label_off': 'no', 'tooltip': (
"Show detected string names on the node itself?"
)}),
},
'optional': {
'dict': _input_types_str['optional']['dict'],
},
'hidden': {
'unique_id': 'UNIQUE_ID', # used for text display at the bottom of the node
},
})
class StringConstructorDictFromText:
"""
Build a dict of named sub-strings to be used later in string formatting (text construction).
"""
NODE_NAME = 'StringConstructorDictFromText'
CATEGORY = _meta.category
DESCRIPTION = _format_docstring(_cleandoc(__doc__))
OUTPUT_NODE = True # Just to show the status message even if not connected to anything
FUNCTION = 'main'
RETURN_TYPES = (_DataTypes.DICT, )
RETURN_NAMES = (_DataTypes.DICT.lower(), )
# OUTPUT_TOOLTIPS = tuple()
@classmethod
def INPUT_TYPES(cls):
return _input_types
def main(
self, cleanup: bool, strings: str, show_status: bool,
dict: _t.Dict[str, _t.Any] = None,
unique_id: str = None,
):
return _parse_dict_from_text(strings, strip_lines=cleanup, show=show_status, in_dict=dict, unique_id=unique_id)