class_docstr: A data structure that provides an interface to access nested dictionaries with "flattened keys", and a few more functions.
  
  e.g.
      dct = RecursiveDict({'a':{'b':2}})
      assert dct["a__b"] == 2
      dct["a__b__c"] = 3
      assert dct['a']['b']['c'] == dct["a__b__c"] == dct.to_flat_dict()["a__b__c"]
  
  This class serves as a base for HyperparameterSamples and HyperparameterSpace
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docstr: Split the keys and call getter recursively until we get to the desired element.
  None returns every non-recursive elements.
docstr_tok: ["Split","the","keys","and","call","getter","recursively","until","we","get","to","the","desired","element",".","None","returns","every","non-recursive","elements","."]
code: def _rec_get(self, key) -> RecursiveDictValue:
      """
      Split the keys and call getter recursively until we get to the desired element.
      None returns every non-recursive elements.
      """
      if key is None:
          return self.get_root_leaf_data()
  
      lkey, _, rkey = key.partition(self.separator)
      rec_dict: RecursiveDict = OrderedDict.__getitem__(self, lkey)
      if rkey == "":
          return rec_dict
      else:
          # Splitted on sep and recursively call getter
          return rec_dict._rec_get(rkey)
  
imports: import typing
  from collections import Counter, OrderedDict, defaultdict
  from copy import copy
  from typing import Any, Dict, Iterable, List, Set, Union
  from neuraxle.hyperparams.distributions import FixedHyperparameter, HPSampledValue, HyperparameterDistribution
  from neuraxle.hyperparams.scipy_distributions import ScipyContinuousDistributionWrapper, ScipyDiscreteDistributionWrapper
  from scipy.stats import rv_continuous, rv_discrete
  from scipy.stats._distn_infrastructure import rv_generic
label_desc: Use image node_id 8 for calling the RecursiveDict obj's underlying member method code with example usage: obj._rec_get(key) and returns: self, rec_dict, rec_dict