code: def test_data_container_should_iterate_through_data_using_minibatches():
      data_container = DACT(
          ids=[str(i) for i in range(100)],
          data_inputs=np.array(list(range(100))),
          expected_outputs=np.array(list(range(100, 200))),
      )
  
      batches = []
      for b in data_container.minibatches(batch_size=10):
          batches.append(b)
  
      for i, batch in enumerate(batches):
          assert np.array_equal(
              np.array(batch.data_inputs),
              np.array(list(range(i * 10, (i * 10) + 10))),
          )
          assert np.array_equal(
              np.array(batch.expected_outputs),
              np.array(
                  list(range((i * 10) + 100, (i * 10) + 100 + 10))
              ),
          )
  
imports: import numpy
  from neuraxle.data_container import DACT, ListDataContainer
label_desc: Use image node_id 4 for calling a global function with example usage: test_data_container_should_iterate_through_data_using_minibatches() without return types