use cached_property is available

Author: basnijholt

adaptive/learner/integrator_coeffs.py

@@ -1,12 +1,16 @@
 # Based on an adaptive quadrature algorithm by Pedro Gonnet
 
-import functools
 from collections import defaultdict
 from fractions import Fraction
 
 import numpy as np
 import scipy.linalg
 
+try:
+    from functools import cached_property
+except ImportError:
+    from adaptive.utils import cached_property
+
 
 def legendre(n):
     """Return the first n Legendre polynomials.
@@ -142,10 +146,6 @@ def calc_V(x, n):
     return np.array(V).T
 
 
-def cached_property(f):
-    return property(functools.lru_cache(None)(f))
-
-
 class Coefficients:
     def __init__(self) -> None:
         self.is_set = False

adaptive/utils.py

@@ -83,3 +83,7 @@ def __call__(self, *args, **kwargs):
                     msg = f"The attribute '{name}' should be of type {type_}, not {type(x)}."
                     raise TypeError(msg)
         return obj
+
+
+def cached_property(f):
+    return property(functools.lru_cache(None)(f))