code: def drift_score_bar_traces(
      drift_score: float, bar_max: float = None
  ) -> Tuple[List[go.Bar], Dict, Dict]:
      """Create a traffic light bar traces for drift score.
  
      Parameters
      ----------
      drift_score : float
          Drift score
      bar_max : float , default: None
          Maximum value for the bar
      Returns
      -------
      Tuple[List[go.Bar], Dict, Dict]
          list of plotly bar traces.
      """
      traffic_light_colors = [
          ((0, 0.1), "#01B8AA"),
          ((0.1, 0.2), "#F2C80F"),
          ((0.2, 0.3), "#FE9666"),
          ((0.3, 1), "#FD625E"),
      ]
  
      bars = []
  
      for range_tuple, color in traffic_light_colors:
          if drift_score < range_tuple[0]:
              break
  
          bars.append(
              go.Bar(
                  x=[min(drift_score, range_tuple[1]) - range_tuple[0]],
                  y=["Drift Score"],
                  orientation="h",
                  marker=dict(
                      color=color,
                  ),
                  offsetgroup=0,
                  base=range_tuple[0],
                  showlegend=False,
              )
          )
  
      bar_stop = max(0.4, drift_score + 0.1)
      if bar_max:
          bar_stop = min(bar_stop, bar_max)
      xaxis = dict(
          showgrid=False,
          gridcolor="black",
          linecolor="black",
          range=[0, bar_stop],
          dtick=0.05,
          fixedrange=True,
      )
      yaxis = dict(
          showgrid=False,
          showline=False,
          showticklabels=False,
          zeroline=False,
          color="black",
          autorange=True,
          rangemode="normal",
          fixedrange=True,
      )
  
      return bars, xaxis, yaxis
  
file_path: deepchecks/deepchecks/utils/distribution/plot.py
imports: from functools import cmp_to_key
  from numbers import Number
  from typing import Any, Dict, List, Tuple, Union
  import numpy
  import pandas
  import plotly.graph_objs
  from plotly.basedatatypes import BaseTraceType
  from scipy.stats import gaussian_kde
  from typing_extensions import Literal
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.dataframes import un_numpy
  from deepchecks.utils.distribution.preprocessing import preprocess_2_cat_cols_to_same_bins
  from deepchecks.utils.plot import DEFAULT_DATASET_NAMES, colors
label_desc: Use image node_id 2 for calling a global function with example usage: drift_score_bar_traces(drift_score, bar_max) and returns: bars,  xaxis,  yaxis