class_docstr: Class for generating metrics and printing it to stdout of the worker
class_docstr_tok: ["Class","for","generating","metrics","and","printing","it","to","stdout","of","the","worker"]
docstr: BACKWARDS COMPATIBILITY: Update metric value
  
  Parameters
  ----------
  value : int, float
      metric to be updated
  request_id : str
      request id to be associated with the metric
  dimensions : list
      list of Dimension objects
docstr_tok: ["BACKWARDS","COMPATIBILITY",":","Update","metric","value","Parameters","--","--","--","--","--","value",":","int",",","float","metric","to","be","updated","request_id",":","str","request","id","to","be","associated","with","the","metric","dimensions",":","list","list","of","Dimension","objects"]
code: def update(
      self,
      value: int or float,
      request_id: str = "",
      dimensions: list = [],
  ):
      """
      BACKWARDS COMPATIBILITY: Update metric value
  
      Parameters
      ----------
      value : int, float
          metric to be updated
      request_id : str
          request id to be associated with the metric
      dimensions : list
          list of Dimension objects
      """
      logger.warning("Overriding existing dimensions")
      self.dimension_names = [dim.name for dim in dimensions]
      self.add_or_update(
          value, [dim.value for dim in dimensions], request_id
      )
  
file_path: serve/ts/metrics/caching_metric.py
imports: import logging
  import socket
  import time
  from ts.metrics.dimension import Dimension
  from ts.metrics.metric_abstract import MetricAbstract
  from ts.metrics.metric_type_enum import MetricTypes
label_desc: Use image node_id 6 for calling the CachingMetric obj's underlying member method code with example usage: obj.update(value, request_id, dimensions) without return types