class_docstr: A random-item recommender.
  
  Attributes:
      selector(CandidateSelector):
          Selects candidate items for recommendation.
          Default is :class:`UnratedItemCandidateSelector`.
      rng_spec:
          Seed or random state for generating recommendations.  Pass
          ``'user'`` to deterministically derive per-user RNGS from
          the user IDs for reproducibility.
class_docstr_tok: ["A","random-item","recommender",".","Attributes",":","selector","(","CandidateSelector",")",":","Selects","candidate","items","for","recommendation",".","Default","is",":","class",":","`","UnratedItemCandidateSelector","`",".","rng_spec",":","Seed","or","random","state","for","generating","recommendations",".","Pass","``","'user","'","``","to","deterministically","derive","per-user","RNGS","from","the","user","IDs","for","reproducibility","."]
code: def __str__(self):
      return "Random"
  
imports: import logging
  from collections.abc import Iterable, Sequence
  import pandas
  import numpy
  from ..data import sparse_ratings
  from .None import Predictor, Recommender, CandidateSelector
  from ..util import derivable_rng
  from .bias import Bias
  from .ranking import TopN
label_desc: Use image node_id 4 for calling the Random obj's underlying member method code with example usage: obj.__str__() and returns: str