class_docstr: Pipeline for applying ``SeriesProcessor`` objects sequentially.
  
  Parameters
  ----------
  processors : List[Union[SeriesProcessor, SeriesPipeline]], optional
      List of ``SeriesProcessor`` or ``SeriesPipeline`` instances that will be applied
      sequentially to the internal series dict, by default None.
      **The processing steps will be executed in the same order as passed in this
      list.**
class_docstr_tok: ["Pipeline","for","applying","``","SeriesProcessor","``","objects","sequentially",".","Parameters","--","--","--","--","--","processors",":","List","[","Union","[","SeriesProcessor",",","SeriesPipeline","]","]",",","optional","List","of","``","SeriesProcessor","``","or","``","SeriesPipeline","``","instances","that","will","be","applied","sequentially","to","the","internal","series","dict",",","by","default","None",".","*","*","The","processing","steps","will","be","executed","in","the","same","order","as","passed","in","this","list",".","*","*"]
code: def __init__(
      self,
      processors: Optional[
          List[Union[SeriesProcessor, SeriesPipeline]]
      ] = None,
  ):
      self.processing_steps: List[
          SeriesProcessor
      ] = []  # TODO: dit private of niet?
      if processors is not None:
          assert isinstance(processors, list)
  
          self.processing_steps = list(
              flatten(
                  [
                      p.processing_steps
                      if isinstance(p, SeriesPipeline)
                      else [p]
                      for p in processors
                  ]
              )
          )
  
file_path: tsflex/tsflex/processing/series_pipeline.py
imports: from __future__ import annotations
  from pathlib import Path
  from typing import Dict, List, Optional, Union
  import dill
  import pandas
  from ..utils.data import flatten, series_dict_to_df, to_series_list
  from ..utils.logging import add_logging_handler, delete_logging_handlers
  from .logger import logger
  from .series_processor import SeriesProcessor
label_desc: Use image node_id 1 to create a new SeriesPipeline object  with example: obj = SeriesPipeline(processors)