code: def gen_data_by_data_field(
      data_field,
      rows,
      start=0,
      float_vector=True,
      dim=128,
      array_length=None,
  ):
      if array_length is None:
          array_length = random.randint(0, 10)
  
      data = []
      if rows > 0:
          if data_field == DataField.vec_field:
              data = gen_vectors(
                  float_vector=float_vector, rows=rows, dim=dim
              )
          elif data_field == DataField.float_field:
              data = [np.float32(random.random()) for _ in range(rows)]
          elif data_field == DataField.double_field:
              data = [np.float64(random.random()) for _ in range(rows)]
          elif data_field == DataField.pk_field:
              data = [np.int64(i) for i in range(start, start + rows)]
          elif data_field == DataField.int_field:
              data = [
                  np.int64(random.randint(-999999, 9999999))
                  for _ in range(rows)
              ]
          elif data_field == DataField.string_field:
              data = [
                  gen_unique_str(str(i))
                  for i in range(start, rows + start)
              ]
          elif data_field == DataField.bool_field:
              data = [
                  random.choice([True, False])
                  for i in range(start, rows + start)
              ]
          elif data_field == DataField.json_field:
              data = pd.Series(
                  [
                      json.dumps(
                          {
                              gen_unique_str(): random.randint(
                                  -999999, 9999999
                              )
                          }
                      )
                      for i in range(start, rows + start)
                  ],
                  dtype=np.dtype("str"),
              )
          elif data_field == DataField.array_bool_field:
              data = pd.Series(
                  [
                      np.array(
                          [
                              random.choice([True, False])
                              for _ in range(array_length)
                          ],
                          dtype=np.dtype("bool"),
                      )
                      for i in range(start, rows + start)
                  ]
              )
          elif data_field == DataField.array_int_field:
              data = pd.Series(
                  [
                      np.array(
                          [
                              random.randint(-999999, 9999999)
                              for _ in range(array_length)
                          ],
                          dtype=np.dtype("int64"),
                      )
                      for i in range(start, rows + start)
                  ]
              )
          elif data_field == DataField.array_float_field:
              data = pd.Series(
                  [
                      np.array(
                          [
                              random.random()
                              for _ in range(array_length)
                          ],
                          dtype=np.dtype("float32"),
                      )
                      for i in range(start, rows + start)
                  ]
              )
          elif data_field == DataField.array_string_field:
              data = pd.Series(
                  [
                      np.array(
                          [
                              gen_unique_str(str(i))
                              for _ in range(array_length)
                          ],
                          dtype=np.dtype("str"),
                      )
                      for i in range(start, rows + start)
                  ]
              )
      return data
  
imports: import copy
  import json
  import os
  import time
  import numpy
  import pandas
  import random
  from faker import Faker
  from sklearn import preprocessing
  from common.common_func import gen_unique_str
  from common.minio_comm import copy_files_to_minio
  from utils.util_log import test_log
label_desc: Use image node_id 15 for calling a global function with example usage: gen_data_by_data_field(data_field, rows, start, float_vector, dim, array_length) and returns: data