diff --git a/examples/python/solve_without_api.py b/examples/python/solve_without_api.py
index 9e84676fc..85e9e82b4 100644
--- a/examples/python/solve_without_api.py
+++ b/examples/python/solve_without_api.py
@@ -41,7 +41,7 @@ def generate_mixed_qp(n, seed=1):
 # solve the problem using the dense backend
 
 results2 = proxsuite.proxqp.dense.solve(
-    H.toarray(), g, A.toarray(), b, C.toarray(), l, u
+    H.toarray(order="C"), g, A.toarray(order="C"), b, C.toarray(order="C"), l, u
 )
 # Note finally, that the matrices are in sparse format, when using the dense backend you
 # should convert them in dense format
diff --git a/examples/python/solve_without_api_and_option.py b/examples/python/solve_without_api_and_option.py
index 9e1cea272..e7534c153 100644
--- a/examples/python/solve_without_api_and_option.py
+++ b/examples/python/solve_without_api_and_option.py
@@ -20,7 +20,9 @@ def generate_mixed_qp(n, seed=1):
     P += (abs(s) + 1e-02) * spa.eye(n)
     P = spa.coo_matrix(P)
     q = np.random.randn(n)
-    A = spa.random(m, n, density=0.15, data_rvs=np.random.randn, format="csc").toarray()
+    A = spa.random(m, n, density=0.15, data_rvs=np.random.randn, format="csc").toarray(
+        order="C"
+    )
     v = np.random.randn(n)  # Fictitious solution
     delta = np.random.rand(m)  # To get inequality
     u = A @ v