code: def hash(
      name: Optional[str],
      primitive: Optional[PrimitiveBase] = None,
      base_features: List[LiteFeature] = [],
      df_id: Optional[str] = None,
      idx: int = 0,
  ):
      hash_msg = hashlib.sha256()
  
      if primitive:
          # TODO: hashing should be on primitive
          hash_msg.update(hash_primitive(primitive)[0].encode("utf-8"))
          commutative = primitive.commutative
          assert (
              len(base_features) > 0
          ), "there must be base features if give a primitive"
          base_columns = base_features
          if commutative:
              base_features.sort()
  
          for c in base_columns:
              hash_msg.update(c.id.encode("utf-8"))
  
      else:
          assert name
          hash_msg.update(name.encode("utf-8"))
          if df_id:
              hash_msg.update(df_id.encode("utf-8"))
  
      hash_msg.update(str(idx).encode("utf-8"))
  
      return hash_msg.hexdigest()
  
imports: from __future__ import annotations
  import hashlib
  from dataclasses import field
  from functools import total_ordering
  from typing import Any, Dict, List, Optional, Set, Type, Union
  from woodwork.column_schema import ColumnSchema
  from woodwork.logical_types import LogicalType
  from featuretools.feature_discovery.utils import get_primitive_return_type, hash_primitive
  from featuretools.primitives.base.primitive_base import PrimitiveBase
label_desc: Use image node_id 26 for calling the LiteFeature obj's underlying member method code with example usage: obj.hash(name, primitive, base_features, df_id, idx) and returns: hash_msg