class_docstr: This is for indexing(rows or columns)
  
  Read-only operations has higher priorities than others.
  So this class is designed in a **read-only** way to shared data for queries.
  Modifications will results in new Index.
  
  NOTE: the indexing has following flaws
  - duplicated index value is not well supported (only the first appearance will be considered)
  - The order of the index is not considered!!!! So the slicing will not behave like pandas when indexings are ordered
class_docstr_tok: ["This","is","for","indexing","(","rows","or","columns",")","Read-only","operations","has","higher","priorities","than","others",".","So","this","class","is","designed","in","a","*","*","read-only","*","*","way","to","shared","data","for","queries",".","Modifications","will","results","in","new","Index",".","NOTE",":","the","indexing","has","following","flaws","-","duplicated","index","value","is","not","well","supported","(","only","the","first","appearance","will","be","considered",")","-","The","order","of","the","index","is","not","considered","!","!","!","!","So","the","slicing","will","not","behave","like","pandas","when","indexings","are","ordered"]
docstr: After user creates indices with Type A, user may query data with other types with the same info.
      This method try to make type conversion and make query sane rather than raising KeyError strictly
  
  Parameters
  ----------
  item :
      The item to query index
docstr_tok: ["After","user","creates","indices","with","Type","A",",","user","may","query","data","with","other","types","with","the","same","info",".","This","method","try","to","make","type","conversion","and","make","query","sane","rather","than","raising","KeyError","strictly","Parameters","--","--","--","--","--","item",":","The","item","to","query","index"]
code: def _convert_type(self, item):
      """
  
      After user creates indices with Type A, user may query data with other types with the same info.
          This method try to make type conversion and make query sane rather than raising KeyError strictly
  
      Parameters
      ----------
      item :
          The item to query index
      """
  
      if self.idx_list.dtype.type is np.datetime64:
          if isinstance(item, pd.Timestamp):
              # This happens often when creating index based on pandas.DatetimeIndex and query with pd.Timestamp
              return item.to_numpy()
      return item
  
imports: from __future__ import annotations
  from typing import Dict, Tuple, Union, Callable, List
  import bisect
  import numpy
  import pandas
label_desc: Use image node_id 3 for calling the Index obj's underlying member method code with example usage: obj._convert_type(item) and returns: item, item