code: def test_min_max_sum_per_partition(self):
      dp_engine, budget_accountant = self._create_dp_engine_default(
          epsilon=1000, return_accountant=True
      )
      data = [1] * 1000 + [-1] * 1005
      params = pipeline_dp.AggregateParams(
          metrics=[pipeline_dp.Metrics.SUM],
          max_partitions_contributed=1,
          min_sum_per_partition=-3,
          max_sum_per_partition=1,
          max_contributions_per_partition=1,
      )
      extractors = pipeline_dp.DataExtractors(
          privacy_id_extractor=lambda _: 0,
          partition_extractor=lambda _: 0,
          value_extractor=lambda x: x,
      )
  
      output = dp_engine.aggregate(
          data, params, extractors, public_partitions=[0]
      )
  
      budget_accountant.compute_budgets()
      output = list(output)
      self.assertLen(output, 1)
      self.assertAlmostEqual(output[0][1].sum, -3, delta=0.1)
  
imports: import sys
  import unittest
  from typing import List, Optional, Tuple
  from unittest.mock import patch
  import numpy
  import apache_beam
  import apache_beam.testing.test_pipeline
  import apache_beam.testing.util
  import pydp.algorithms.partition_selection
  from absl.testing import absltest
  from absl.testing import parameterized
  import pipeline_dp
  from pipeline_dp import aggregate_params
  from pipeline_dp import budget_accounting
  from pipeline_dp import dp_computations
  from pipeline_dp.budget_accounting import NaiveBudgetAccountant
  from pipeline_dp.pipeline_backend import PipelineBackend
  from pipeline_dp.pipeline_functions import collect_to_container
  from pipeline_dp.report_generator import ReportGenerator
label_desc: Use image node_id 40 for calling the DpEngineTest obj's underlying member method code with example usage: obj.test_min_max_sum_per_partition() without return types