code: def get_calendar_day(freq="1min", future=False):
      """
      Load High-Freq Calendar Date Using Memcache.
      !!!NOTE: Loading the calendar is quite slow. So loading calendar before start multiprocessing will make it faster.
  
      Parameters
      ----------
      freq : str
          frequency of read calendar file.
      future : bool
          whether including future trading day.
  
      Returns
      -------
      _calendar:
          array of date.
      """
      flag = f"{freq}_future_{future}_day"
      if flag in H["c"]:
          _calendar = H["c"][flag]
      else:
          _calendar = np.array(
              list(
                  map(
                      lambda x: x.date(),
                      Cal.load_calendar(freq, future),
                  )
              )
          )
          H["c"][flag] = _calendar
      return _calendar
  
imports: import numpy
  import pandas
  from datetime import datetime
  from qlib.data.cache import H
  from qlib.data.data import Cal
  from qlib.data.ops import ElemOperator, PairOperator
  from qlib.utils.time import time_to_day_index
label_desc: Use image node_id 1 for calling a global function with example usage: get_calendar_day(freq, future) and returns: _calendar