old_contents: from .base import Benchmark, benchmark, pandas_only, non_pandas_only
  from Orange.data import Table
  from Orange.preprocess import Discretize
  from Orange.preprocess.discretize import EqualFreq
  
  # noinspection PyBroadException
  try:
      from Orange.data.filter import FilterContinuous, FilterDiscrete, Values
  except:
      # legacy only
      pass
  
  
  # noinspection PyStatementEffect
  class BenchBasic(Benchmark):
      def setUp(self):
          self.setup_test_string = "sttss"
          self.iris = Table('iris')
          self.adult = Table('adult')
          self.discretizer = Discretize(EqualFreq(n=3))
  
      def function_setup(self):
          self.func_setup_str = "fsstr"
  
      @benchmark(number=100)
      def bench_iris_read(self):
          Table('iris')
  
      @benchmark(number=5, warmup=1)
      def bench_adult_read(self):
          Table('adult')
  
      @benchmark(number=100)
      def bench_iris_create_X(self):
          self.iris.X
  
      @benchmark(number=50)
      def bench_adult_create_X(self):
          self.adult.X
  
      @pandas_only
      @benchmark(number=20)
      def bench_adult_filter_pandas(self):
          self.adult[(self.adult.age > 30) & (self.adult.workclass == 'Private')]
  
      @non_pandas_only
      @benchmark(number=20)
      def bench_adult_filter_pre_pandas(self):
          age_filter = FilterContinuous(self.adult.domain["age"], FilterContinuous.Greater, 30)
          workclass_filter = FilterDiscrete(self.adult.domain["workclass"], [0])
          combined = Values([age_filter, workclass_filter])
          combined(self.adult)
  
      @benchmark(number=50)
      def bench_iris_basic_stats(self):
          self.iris._compute_basic_stats()
  
      @benchmark(number=20)
      def bench_iris_distributions(self):
          self.iris._compute_distributions()
  
      @benchmark()
      def bench_iris_contingency(self):
          self.iris._compute_contingency()
  
      @benchmark()
      def bench_iris_discretize(self):
          self.discretizer(self.iris)
  
      @pandas_only
      @benchmark()
      def bench_iris_iteration_pandas(self):
          for _, _ in self.iris.iterrows():
              pass
  
      @non_pandas_only
      @benchmark()
      def bench_iris_iteration_pre_pandas(self):
          for _ in self.iris:
              pass
  
new_contents: from .base import Benchmark, benchmark, pandas_only, non_pandas_only
  from Orange.data import Table
  from Orange.preprocess import Discretize
  from Orange.preprocess.discretize import EqualFreq
  
  # noinspection PyBroadException
  try:
      from Orange.data.filter import FilterContinuous, FilterDiscrete, Values
  except:
      # legacy only
      pass
  
  
  # noinspection PyStatementEffect
  class BenchBasic(Benchmark):
      def setUp(self):
          self.iris = Table('iris')
          self.adult = Table('adult')
          self.discretizer = Discretize(EqualFreq(n=3))
  
      @benchmark(number=100)
      def bench_iris_read(self):
          Table('iris')
  
      @benchmark(number=5, warmup=1)
      def bench_adult_read(self):
          Table('adult')
  
      @benchmark(number=100)
      def bench_iris_create_X(self):
          self.iris.X
  
      @benchmark(number=50)
      def bench_adult_create_X(self):
          self.adult.X
  
      @pandas_only
      @benchmark(number=20)
      def bench_adult_filter_pandas(self):
          self.adult[(self.adult.age > 30) & (self.adult.workclass == 'Private')]
  
      @non_pandas_only
      @benchmark(number=20)
      def bench_adult_filter_pre_pandas(self):
          age_filter = FilterContinuous(self.adult.domain["age"], FilterContinuous.Greater, 30)
          workclass_filter = FilterDiscrete(self.adult.domain["workclass"], [0])
          combined = Values([age_filter, workclass_filter])
          combined(self.adult)
  
      @benchmark(number=50)
      def bench_iris_basic_stats(self):
          self.iris._compute_basic_stats()
  
      @benchmark(number=20)
      def bench_iris_distributions(self):
          self.iris._compute_distributions()
  
      @benchmark()
      def bench_iris_contingency(self):
          self.iris._compute_contingency()
  
      @benchmark()
      def bench_iris_discretize(self):
          self.discretizer(self.iris)
  
      @pandas_only
      @benchmark()
      def bench_iris_iteration_pandas(self):
          for _, _ in self.iris.iterrows():
              pass
  
      @non_pandas_only
      @benchmark()
      def bench_iris_iteration_pre_pandas(self):
          for _ in self.iris:
              pass
  
subject: Remove some leftovers.