class_docstr: Logs parameter and run information throughout into a file during
  optimization.
  
  Parameters
  ----------
  filepath: str or pathlib.Path
      the path to dump data to
  append: bool
      whether to append the file (otherwise it replaces it)
  order: int
      order of the internal/model parameters to extract
  
  Example
  -------
  
  .. code-block:: python
  
      logger = ParametersLogger(filepath)
      optimizer.register_callback("tell",  logger)
      optimizer.minimize()
      list_of_dict_of_data = logger.load()
  
  Note
  ----
  Arrays are converted to lists
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code: def __init__(
      self,
      filepath: tp.Union[str, Path],
      append: bool = True,
      order: int = 1,
  ) -> None:
      self._session = datetime.datetime.now().strftime(
          "%y-%m-%d %H:%M:%S"
      )
      self._filepath = Path(filepath)
      self._order = order
      if self._filepath.exists() and not append:
          self._filepath.unlink()  # missing_ok argument added in python 3.8
      self._filepath.parent.mkdir(exist_ok=True, parents=True)
  
imports: import json
  import time
  import warnings
  import inspect
  import datetime
  import logging
  from pathlib import Path
  import numpy
  import nevergrad.common.typing
  from nevergrad.common import errors
  from nevergrad.parametrization import parameter
  from nevergrad.parametrization import helpers
  from .None import base
label_desc: Use image node_id 1 to create a new ParametersLogger object  with example: obj = ParametersLogger(filepath, append, order)