diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py
index 1ad23121..e885482e 100644
--- a/GPy/testing/cython_tests.py
+++ b/GPy/testing/cython_tests.py
@@ -1,8 +1,7 @@
 import numpy as np
-import scipy as sp
 from GPy.util import choleskies
 import GPy
-import unittest
+import pytest
 
 from ..util.config import config
 
@@ -25,32 +24,32 @@ These tests make sure that the pure python and cython codes work the same
 """
 
 
-@unittest.skipIf(
+@pytest.skipIf(
     not choleskies_cython_working,
     "Cython cholesky module has not been built on this machine",
 )
-class CythonTestChols(np.testing.TestCase):
-    def setUp(self):
+class CythonTestChols:
+    def setup(self):
         self.flat = np.random.randn(45, 5)
         self.triang = np.array([np.eye(20) for i in range(3)])
 
     def test_flat_to_triang(self):
         L1 = choleskies._flat_to_triang_pure(self.flat)
         L2 = choleskies._flat_to_triang_cython(self.flat)
-        np.testing.assert_allclose(L1, L2)
+        assert np.allclose(L1, L2), "Triang mismatch!"
 
     def test_triang_to_flat(self):
         A1 = choleskies._triang_to_flat_pure(self.triang)
         A2 = choleskies._triang_to_flat_cython(self.triang)
-        np.testing.assert_allclose(A1, A2)
+        assert np.allclose(A1, A2), "Flat mismatch!"
 
 
-@unittest.skipIf(
+@pytest.skipIf(
     not stationary_cython_working,
     "Cython stationary module has not been built on this machine",
 )
-class test_stationary(np.testing.TestCase):
-    def setUp(self):
+class TestStationary:
+    def setup(self):
         self.k = GPy.kern.RBF(10)
         self.X = np.random.randn(300, 10)
         self.Z = np.random.randn(20, 10)
@@ -59,40 +58,45 @@ class test_stationary(np.testing.TestCase):
         self.dKxz = np.random.randn(300, 20)
 
     def test_square_gradX(self):
+        self.setup()
         g1 = self.k._gradients_X_cython(self.dKxx, self.X)
         g2 = self.k._gradients_X_pure(self.dKxx, self.X)
-        np.testing.assert_allclose(g1, g2)
+        assert np.allclose(g1, g2), "Gradient mismatch on square X!"
 
     def test_rect_gradx(self):
+        self.setup()
         g1 = self.k._gradients_X_cython(self.dKxz, self.X, self.Z)
         g2 = self.k._gradients_X_pure(self.dKxz, self.X, self.Z)
-        np.testing.assert_allclose(g1, g2)
+        assert np.allclose(g1, g2), "Gradient mismatch on rect X!"
 
     def test_square_lengthscales(self):
+        self.setup()
         g1 = self.k._lengthscale_grads_pure(self.dKxx, self.X, self.X)
         g2 = self.k._lengthscale_grads_cython(self.dKxx, self.X, self.X)
-        np.testing.assert_allclose(g1, g2)
+        assert np.allclose(g1, g2), "Gradient mismatch on square lengthscale!"
 
     def test_rect_lengthscales(self):
+        self.setup()
         g1 = self.k._lengthscale_grads_pure(self.dKxz, self.X, self.Z)
         g2 = self.k._lengthscale_grads_cython(self.dKxz, self.X, self.Z)
-        np.testing.assert_allclose(g1, g2)
+        assert np.allclose(g1, g2), "Gradient mismatch on rect lengthscale!"
 
 
-@unittest.skipIf(
+@pytest.skipIf(
     not choleskies_cython_working,
     "Cython cholesky module has not been built on this machine",
 )
-class test_choleskies_backprop(np.testing.TestCase):
-    def setUp(self):
+class TestCholeskiesBackprop:
+    def setup(self):
         a = np.random.randn(10, 12)
         A = a.dot(a.T)
         self.L = GPy.util.linalg.jitchol(A)
         self.dL = np.random.randn(10, 10)
 
-    def test(self):
+    def test_backprop(self):
+        self.setup()
         r1 = choleskies._backprop_gradient_pure(self.dL, self.L)
         r2 = choleskies_cython.backprop_gradient(self.dL, self.L)
         r3 = choleskies_cython.backprop_gradient_par_c(self.dL, self.L)
-        np.testing.assert_allclose(r1, r2)
-        np.testing.assert_allclose(r1, r3)
+        assert np.allclose(r1, r2), "Gradient mismatch!"
+        assert np.allclose(r1, r3), "Gradient mismatch!"