Basic data handling

Basic Python functions for manipulating data that every programmer is used to.

These nodes are very lightweight and require no additional dependencies.

Note

This projected is in early development—do not use it in production, yet!

Quickstart

1. Install ComfyUI.
2. Install ComfyUI-Manager
3. Look up this extension in ComfyUI-Manager. If you are installing manually, clone this repository under ComfyUI/custom_nodes.
4. Restart ComfyUI.

Features

• STRING: String manipulation nodes

  • Basic functions: capitalize, casefold, center, concat, count, encode/decode, find/rfind, join, lower/upper, replace, split, strip, etc.
  • String checking: contains, endswith, startswith
  • Case conversion: lower, upper, swapcase, title, capitalize
  • Validation: isalnum, isalpha, isdigit, isnumeric, etc.

• LIST: Python list manipulation nodes (as a single variable)

  • Conversion: convert to data list
  • Creation: any to LIST
  • Modification: append, extend, insert, remove, pop, clear, set_item
  • Access: get_item, slice, index, contains
  • Information: length, count
  • Operations: sort, reverse

• data list: ComfyUI list manipulation nodes (for processing individual items)

  • Conversion: convert to LIST
  • Creation: create_empty
  • Modification: append, extend, insert, remove, pop, clear, set_item
  • Access: get_item, slice, index, contains
  • Information: length, count
  • Operations: sort, reverse, copy, zip

• DICT: Dictionary manipulation nodes

  • Creation: create, from_items, from_lists, fromkeys, any_to_DICT
  • Access: get, get_multiple, keys, values, items
  • Modification: set, update, setdefault, merge
  • Removal: pop, popitem, remove, clear
  • Information: length, contains_key
  • Operations: copy, filter_by_keys, exclude_keys, invert, compare
  • Conversion: get_keys_values

• INT: Integer operation nodes

  • Basic operations: add, subtract, multiply, divide, modulus, power
  • Bit operations: bit_length, to_bytes, from_bytes, bit_count

• FLOAT: Floating-point operation nodes

  • Basic operations: add, subtract, multiply, divide, power, round
  • Specialized: is_integer, as_integer_ratio, to_hex, from_hex

• BOOLEAN: Boolean logic nodes

  • Logic operations: and, or, not, xor, nand, nor

Understanding LIST vs. data list

ComfyUI has two different list data types that serve different purposes:

1. LIST datatype

• A Python list represented as a single variable in the workflow
• Treated as a self-contained object that can be passed between nodes
• Cannot directly connect to nodes that expect individual items
• Best for:
  • Working with collections of data as a single unit
  • Storing intermediate results that need to be processed as a whole
  • Passing collections between different parts of your workflow
  • Complex data storage that shouldn't be split apart

2. data list

• A native ComfyUI list where items are processed individually
• Acts like a standard array/list in most programming contexts
• Items can be accessed individually by compatible nodes
• Supports built-in ComfyUI iteration over each item
• Best for:
  • Working directly with multiple items in parallel
  • Batch processing scenarios
  • When you need to apply the same operation to multiple inputs
  • When your operation needs to work with individual items separately

Converting between types

• Use convert to data list node to transform a LIST into a ComfyUI data list
• Use convert to LIST node to transform a ComfyUI data list into a LIST object

When to use which type

• Use LIST when you need to:

  • Keep items grouped together as a single entity
  • Perform operations on the entire collection (sorting, reversing, etc.)
  • Pass a collection between workflow sections
  • Prevent automatic iteration over items

• Use data list when you need to:

  • Process each item individually through ComfyUI nodes
  • Allow nodes to iterate through your items automatically
  • Connect to nodes that expect individual inputs
  • Perform batch processing operations

Tests

This repo contains unit tests written in Pytest in the tests/ directory. It is recommended to unit test your custom node.

• build-pipeline.yml will run pytest and linter on any open PRs
• validate.yml will run node-diff to check for breaking changes