diff --git a/pyerrors/fits.py b/pyerrors/fits.py
index d9f963d9..20a5ee32 100644
--- a/pyerrors/fits.py
+++ b/pyerrors/fits.py
@@ -240,13 +240,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
 
             loc_priors = []
             for i_n, i_prior in enumerate(priors):
-                if isinstance(i_prior, Obs):
-                    loc_priors.append(i_prior)
-                elif isinstance(i_prior, str):
-                    loc_val, loc_dval = _extract_val_and_dval(i_prior)
-                    loc_priors.append(cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(i_n) + f"_{np.random.randint(2147483647):010d}"))
-                else:
-                    raise TypeError("Prior entries need to be 'Obs' or 'str'.")
+                loc_priors.append(_construct_prior_obs(i_prior, i_n))
 
             prior_mask = np.arange(len(priors))
             output.priors = loc_priors
@@ -260,13 +254,8 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
                     prior_mask.append(pos)
                 else:
                     raise TypeError("Prior position needs to be an integer.")
-                if isinstance(prior, Obs):
-                    loc_priors.append(prior)
-                elif isinstance(prior, str):
-                    loc_val, loc_dval = _extract_val_and_dval(prior)
-                    loc_priors.append(cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(pos) + f"_{np.random.randint(2147483647):010d}"))
-                else:
-                    raise TypeError("Prior entries need to be 'Obs' or 'str'.")
+                loc_priors.append(_construct_prior_obs(prior, pos))
+
                 output.priors[pos] = loc_priors[-1]
             if max(prior_mask) >= n_parms:
                 raise ValueError("Prior position out of range.")
@@ -823,3 +812,13 @@ def _extract_val_and_dval(string):
     else:
         factor = 1
     return float(split_string[0]), float(split_string[1][:-1]) * factor
+
+
+def _construct_prior_obs(i_prior, i_n):
+    if isinstance(i_prior, Obs):
+        return i_prior
+    elif isinstance(i_prior, str):
+        loc_val, loc_dval = _extract_val_and_dval(i_prior)
+        return cov_Obs(loc_val, loc_dval ** 2, '#prior' + str(i_n) + f"_{np.random.randint(2147483647):010d}")
+    else:
+        raise TypeError("Prior entries need to be 'Obs' or 'str'.")