diff --git a/pkgs/development/python-modules/bayespy/default.nix b/pkgs/development/python-modules/bayespy/default.nix
index ff3d8cfce2c3..7ec5dc5ec7d5 100644
--- a/pkgs/development/python-modules/bayespy/default.nix
+++ b/pkgs/development/python-modules/bayespy/default.nix
@@ -23,6 +23,10 @@ buildPythonPackage rec {
       url = "https://github.com/bayespy/bayespy/commit/9be53bada763e19c2b6086731a6aa542ad33aad0.patch";
       hash = "sha256-KYt/0GcaNWR9K9/uS2OXgK7g1Z+Bayx9+IQGU75Mpuo=";
     })
+
+    # Fix deprecated numpy types
+    # https://sources.debian.org/src/python-bayespy/0.5.22-5/debian/patches/pr127-Fix-deprecated-numpy-types.patch/
+    ./pr127-Fix-deprecated-numpy-types.patch
   ];
 
   nativeCheckInputs = [ pytestCheckHook nose glibcLocales ];
diff --git a/pkgs/development/python-modules/bayespy/pr127-Fix-deprecated-numpy-types.patch b/pkgs/development/python-modules/bayespy/pr127-Fix-deprecated-numpy-types.patch
new file mode 100644
index 000000000000..160a15eddb0b
--- /dev/null
+++ b/pkgs/development/python-modules/bayespy/pr127-Fix-deprecated-numpy-types.patch
@@ -0,0 +1,129 @@
+Description: Fix deprecated numpy types
+From: Antti Mäkinen <antti.makinen@danfoss.com>
+Bug: https://github.com/bayespy/bayespy/pull/127
+Bug-Debian: https://bugs.debian.org/1027220
+
+--- a/bayespy/inference/vmp/nodes/categorical_markov_chain.py
++++ b/bayespy/inference/vmp/nodes/categorical_markov_chain.py
+@@ -171,7 +171,7 @@ class CategoricalMarkovChainDistribution
+         # Explicit broadcasting
+         P = P * np.ones(plates)[...,None,None,None]
+         # Allocate memory
+-        Z = np.zeros(plates + (self.N,), dtype=np.int)
++        Z = np.zeros(plates + (self.N,), dtype=np.int64)
+         # Draw initial state
+         Z[...,0] = random.categorical(p0, size=plates)
+         # Create [0,1,2,...,len(plate_axis)] indices for each plate axis and
+--- a/bayespy/inference/vmp/nodes/concatenate.py
++++ b/bayespy/inference/vmp/nodes/concatenate.py
+@@ -70,7 +70,7 @@ class Concatenate(Deterministic):
+         )
+ 
+         # Compute start indices for each parent on the concatenated plate axis
+-        self._indices = np.zeros(len(nodes)+1, dtype=np.int)
++        self._indices = np.zeros(len(nodes)+1, dtype=np.int64)
+         self._indices[1:] = np.cumsum([int(parent.plates[axis])
+                                        for parent in self.parents])
+         self._lengths = [parent.plates[axis] for parent in self.parents]
+--- a/bayespy/inference/vmp/nodes/tests/test_binomial.py
++++ b/bayespy/inference/vmp/nodes/tests/test_binomial.py
+@@ -43,7 +43,7 @@ class TestBinomial(TestCase):
+         X = Binomial(10, 0.7*np.ones((4,3)))
+         self.assertEqual(X.plates,
+                          (4,3))
+-        n = np.ones((4,3), dtype=np.int)
++        n = np.ones((4,3), dtype=np.int64)
+         X = Binomial(n, 0.7)
+         self.assertEqual(X.plates,
+                          (4,3))
+--- a/bayespy/inference/vmp/nodes/tests/test_multinomial.py
++++ b/bayespy/inference/vmp/nodes/tests/test_multinomial.py
+@@ -43,7 +43,7 @@ class TestMultinomial(TestCase):
+         X = Multinomial(10, 0.25*np.ones((2,3,4)))
+         self.assertEqual(X.plates,
+                          (2,3))
+-        n = 10 * np.ones((3,4), dtype=np.int)
++        n = 10 * np.ones((3,4), dtype=np.int64)
+         X = Multinomial(n, [0.1, 0.3, 0.6])
+         self.assertEqual(X.plates,
+                          (3,4))
+--- a/bayespy/inference/vmp/nodes/tests/test_take.py
++++ b/bayespy/inference/vmp/nodes/tests/test_take.py
+@@ -89,7 +89,7 @@ class TestTake(TestCase):
+ 
+         # Test matrix indices, no shape
+         X = GaussianARD(1, 1, plates=(3,), shape=(2,))
+-        Y = Take(X, np.ones((4, 5), dtype=np.int))
++        Y = Take(X, np.ones((4, 5), dtype=np.int64))
+         self.assertEqual(
+             Y.plates,
+             (4, 5),
+@@ -113,7 +113,7 @@ class TestTake(TestCase):
+ 
+         # Test vector indices with more plate axes
+         X = GaussianARD(1, 1, plates=(4, 2), shape=())
+-        Y = Take(X, np.ones(3, dtype=np.int))
++        Y = Take(X, np.ones(3, dtype=np.int64))
+         self.assertEqual(
+             Y.plates,
+             (4, 3),
+@@ -125,7 +125,7 @@ class TestTake(TestCase):
+ 
+         # Test take on other plate axis
+         X = GaussianARD(1, 1, plates=(4, 2), shape=())
+-        Y = Take(X, np.ones(3, dtype=np.int), plate_axis=-2)
++        Y = Take(X, np.ones(3, dtype=np.int64), plate_axis=-2)
+         self.assertEqual(
+             Y.plates,
+             (3, 2),
+@@ -141,7 +141,7 @@ class TestTake(TestCase):
+             ValueError,
+             Take,
+             X,
+-            np.ones(3, dtype=np.int),
++            np.ones(3, dtype=np.int64),
+             plate_axis=0,
+         )
+ 
+--- a/bayespy/utils/tests/test_linalg.py
++++ b/bayespy/utils/tests/test_linalg.py
+@@ -126,7 +126,7 @@ class TestBandedSolve(misc.TestCase):
+         # Random sizes of the blocks
+         #D = np.random.randint(5, 10, size=N)
+         # Fixed sizes of the blocks
+-        D = 5*np.ones(N, dtype=np.int)
++        D = 5*np.ones(N, dtype=np.int64)
+ 
+         # Some helpful variables to create the covariances
+         W = [np.random.randn(D[i], 2*D[i])
+--- a/bayespy/utils/misc.py
++++ b/bayespy/utils/misc.py
+@@ -355,7 +355,7 @@ class TestCase(unittest.TestCase):
+                     ]
+                 )
+             ]
+-        ).astype(np.int)
++        ).astype(int)
+ 
+         def pack(x):
+             return [
+--- a/bayespy/utils/random.py
++++ b/bayespy/utils/random.py
+@@ -284,7 +284,7 @@ def categorical(p, size=None):
+         for ind in inds:
+             z[ind] = np.searchsorted(P[ind], x[ind])
+ 
+-    return z.astype(np.int)
++    return z.astype(int)
+ 
+ 
+ def multinomial(n, p, size=None):
+@@ -313,7 +313,7 @@ def multinomial(n, p, size=None):
+     for i in misc.nested_iterator(size):
+         x[i] = np.random.multinomial(n[i], p[i])
+ 
+-    return x.astype(np.int)
++    return x.astype(int)
+ 
+ 
+ def gamma(a, b, size=None):