code: def get_common_fields_by_data(data, exclude_fields=None):
      fields = set()
      if isinstance(data, dict):
          data = [data]
      if not isinstance(data, list):
          raise Exception("data must be list or dict")
      common_fields = set(data[0].keys())
      for d in data:
          keys = set(d.keys())
          common_fields = common_fields.intersection(keys)
      if exclude_fields is not None:
          exclude_fields = set(exclude_fields)
          common_fields = common_fields.difference(exclude_fields)
      return list(common_fields)
  
imports: import random
  import time
  import random
  import string
  from faker import Faker
  import numpy
  from sklearn import preprocessing
  import requests
  from loguru import logger
  import datetime
label_desc: Use image node_id 10 for calling a global function with example usage: get_common_fields_by_data(data, exclude_fields) and returns: list