old_contents: import pytest  # type: ignore
  
  from ppb_vector import Vector2
  from utils import *
  
  
  class V1(Vector2):
      """Arbitrary subclass of Vector2."""
      pass
  
  class V11(V1):
      """Subclass of V1."""
      pass
  
  class V2(Vector2):
      """Arbitrary subclass of Vector2, distinct from V1."""
      pass
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  def test_binop_same(op):
      # Normalize for reflect
      a = op(V1(1, 2), V1(3, 4).normalize())
  
      assert isinstance(a, V1)
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  def test_binop_different(op):
      # Normalize for reflect
      a = op(V1(1, 2), V2(3, 4).normalize())
      b = op(V2(1, 2), V1(3, 4).normalize())
      assert isinstance(a, (V1, V2))
      assert isinstance(b, (V1, V2))
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  def test_binop_subclass(op):
      # Normalize for reflect
      a = op(V1(1, 2), V11(3, 4).normalize())
      b = op(V11(1, 2), V1(3, 4).normalize())
      assert isinstance(a, V11)
      assert isinstance(b, V11)
  
  
  @pytest.mark.parametrize('op', SCALAR_OPS)
  def test_vnumop(op):
      a = op(V1(1, 2), 42)
      assert isinstance(a, V1)
  
  
  @pytest.mark.parametrize('op', UNARY_OPS)
  def test_monop(op):
      a = op(V1(1, 2))
      assert isinstance(a, V1)
  
  
  @pytest.mark.parametrize('op', BINARY_OPS + BINARY_SCALAR_OPS + BOOL_OPS) # type: ignore
  def test_binop_vectorlike(op):
      """Test that `op` accepts a vector-like second parameter."""
      x = Vector2(1, 0)
      y = Vector2(0, 1)
      result = op(x, y)
  
      for y_like in vector_likes(y):
          assert op(x, y_like) == result
  
new_contents: import pytest  # type: ignore
  from hypothesis import event, given, strategies as st
  
  from ppb_vector import Vector2
  from utils import *
  
  
  class V1(Vector2):
      """Arbitrary subclass of Vector2."""
      pass
  
  class V11(V1):
      """Subclass of V1."""
      pass
  
  class V2(Vector2):
      """Arbitrary subclass of Vector2, distinct from V1."""
      pass
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  @given(x=st.builds(V1, vectors()), y=st.builds(V1, units()))
  def test_binop_same(op, x: V1, y: V2):
      assert isinstance(op(x, y), V1)
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  @given(x=vectors(), y=units())
  def test_binop_different(op, x: Vector2, y: Vector2):
      assert isinstance(op(V1(x), V2(y)), (V1, V2))
      assert isinstance(op(V2(x), V1(y)), (V1, V2))
  
  
  @pytest.mark.parametrize('op', BINARY_OPS)
  @given(x=st.builds(V1, vectors()), y=st.builds(V1, units()))
  def test_binop_subclass(op, x: V1, y: V1):
      assert isinstance(op(V11(x), y), V11)
      assert isinstance(op(x, V11(y)), V11)
  
  
  @pytest.mark.parametrize('op', SCALAR_OPS)
  @given(x=st.builds(V1, vectors()), scalar=floats())
  def test_vnumop(op, x: V1, scalar: float):
      try:
          assert isinstance(op(x, scalar), V1)
      except (ValueError, ZeroDivisionError) as e:
          event(type(e).__name__)
          pass
  
  
  @pytest.mark.parametrize('op', UNARY_OPS)
  @given(x=st.builds(V1, vectors()))
  def test_monop(op, x):
      try:
          assert isinstance(op(x), V1)
      except (ValueError, ZeroDivisionError) as e:
          event(type(e).__name__)
          pass
  
  
  @pytest.mark.parametrize('op', BINARY_OPS + BINARY_SCALAR_OPS + BOOL_OPS) # type: ignore
  @given(x=vectors(), y=units())
  def test_binop_vectorlike(op, x: Vector2, y: Vector2):
      """Test that `op` accepts a vector-like second parameter."""
      result = op(x, y)
  
      for y_like in vector_likes(y):
          assert op(x, y_like) == result
  
subject: Replace hardcoded values with Hypothesis parameters