class_docstr: Chooses DPStrategy based on DP budget, computation sensitivites, etc
  
  It chooses noise_kind to minimize the noise std deviation.
  For non-public partitions it chooses partition selection strategy to
  minimize threshold. For more details see docstring to
  select_partition_selection_strategy().
code: def _get_strategy_for_select_partition(
      self, l0_sensitivity: int
  ) -> DPStrategy:
      return DPStrategy(
          noise_kind=None,
          partition_selection_strategy=self.select_partition_selection_strategy(
              self._epsilon, self._delta, l0_sensitivity
          ),
          post_aggregation_thresholding=False,
      )
  
imports: from dataclasses import dataclass
  from typing import Optional
  import pipeline_dp
  from pipeline_dp import aggregate_params
  from pipeline_dp import dp_computations
  from pipeline_dp import input_validators
label_desc: Use image node_id 5 for calling the DPStrategySelector obj's underlying member method code with example usage: obj._get_strategy_for_select_partition(l0_sensitivity) and returns: DPStrategy