class_docstr: Utility for collecting samples into a dictionary.
  
  Name comes from its similarity to ``defaultdict``:
  entries are lazily created.
  
  Parameters
  ----------
  samples : int
      The number of samples that will be collected, per variable,
      into the trace.
  
  Attributes
  ----------
  trace_dict : Dict[str, np.ndarray]
      A dictionary constituting a trace.  Should be extracted
      after a procedure has filled the `_DefaultTrace` using the
      `insert()` method
code: def __init__(self, samples: int):
      self._len: int = samples
      self.trace_dict: Dict[str, np.ndarray] = {}
  
imports: import logging
  import warnings
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Mapping, Optional, Tuple, Union
  import numpy
  from arviz import InferenceData, concat, rcParams
  from arviz.data.base import CoordSpec, DimSpec, dict_to_dataset, requires
  from pytensor.graph.basic import Constant
  from pytensor.tensor.sharedvar import SharedVariable
  import pymc
  from pymc.model import Model, modelcontext
  from pymc.pytensorf import extract_obs_data
  from pymc.util import get_default_varnames
label_desc: Use image node_id 1 to create a new _DefaultTrace object  with example: obj = _DefaultTrace(samples)