add support for unbounded integers in blob serialization

Author: dimitri-yatsenko

datajoint/blob.py

@@ -264,11 +264,11 @@ def read_sparse_array(self):
         raise DataJointError('datajoint-python does not yet support sparse arrays. Issue (#590)')
 
     def read_int(self):
-        return int(self.read_value('int64'))
+        return int.from_bytes(self.read_value('int64'), byteorder='little', signed=True)
 
     @staticmethod
     def pack_int(v):
-        return b"\x0a" + np.array(v, dtype='int64').tobytes()
+        return b"\x0a" + v.to_bytes((v.bit_length() + 7 + (v < 0)) // 8, byteorder='little', signed=True)
 
     def read_bool(self):
         return bool(self.read_value('bool'))

tests/test_blob.py

@@ -32,7 +32,7 @@ def test_pack():
     x = None
     assert_true(unpack(pack(x)) is None, "None did not match")
 
-    x = 7
+    x = -255
     y = unpack(pack(x))
     assert_true(x == y and isinstance(y, int) and not isinstance(y, np.ndarray), "Native int did not match")