class_docstr: A way to represent a set of dot chained operations on an object without actually running them.
      
class_docstr_tok: ["A","way","to","represent","a","set","of","dot","chained","operations","on","an","object","without","actually","running","them","."]
code: def __repr__(self):
      out = self._root_name
      for o in self._ops:
          op, args, kwargs = o
          out += "."
          out += op
          if (args is not None and len(args) > 0) or (
              kwargs is not None and len(kwargs) > 0
          ):
              out += "("
              if args is not None and len(args) > 0:
                  out += ", ".join([str(v) for v in args])
              if kwargs is not None and len(kwargs) > 0:
                  out += ", " + ", ".join(
                      [
                          str(k) + "=" + str(kwargs[k])
                          for k in kwargs.keys()
                      ]
                  )
              out += ")"
      return out
  
imports: import copy
  import os
  import re
  import sys
  from contextlib import contextmanager
  import numpy
  import pandas
  import scipy.special
  import sklearn
label_desc: Use image node_id 6 for calling the OpChain obj's underlying member method code with example usage: obj.__repr__() and returns: out