class_docstr: Returns a random sample of items from the dataset, from the given property
class_docstr_tok: ["Returns","a","random","sample","of","items","from","the","dataset",",","from","the","given","property"]
docstr: ### Parameter
  
  **field**: Field to sample from
  **size**: Return this many items (can be less)
docstr_tok: ["#","#","#","Parameter","*","*","field","*","*",":","Field","to","sample","from","*","*","size","*","*",":","Return","this","many","items","(","can","be","less",")"]
code: def __init__(self, field: str, size: int) -> None:
      """
      ### Parameter
  
      **field**: Field to sample from
      **size**: Return this many items (can be less)
      """
      args = [field, str(size)]
      super().__init__(*args)
      self._field = field
  
imports: from typing import Union
  from .aggregation import Asc, Desc, Reducer, SortDirection
label_desc: Use image node_id 1 to create a new random_sample object from inherited base classes: Reducer with example: obj = random_sample(field, size)