remove custom cached prop and replace with builtin

ecoscope/base/__init__.py

@@ -7,7 +7,6 @@
 )
 from ecoscope.base.base import EcoDataFrame, Relocations, Trajectory
 from ecoscope.base.utils import (
-    cachedproperty,
     create_meshgrid,
     groupby_intervals,
     hex_to_rgba,
@@ -23,7 +22,6 @@
     "RelocsSpeedFilter",
     "TrajSegFilter",
     "Trajectory",
-    "cachedproperty",
     "create_meshgrid",
     "groupby_intervals",
     "hex_to_rgba",

ecoscope/base/base.py

@@ -13,7 +13,7 @@
     RelocsSpeedFilter,
     TrajSegFilter,
 )
-from ecoscope.base.utils import cachedproperty
+from functools import cached_property
 
 
 class EcoDataFrame(gpd.GeoDataFrame):
@@ -285,13 +285,13 @@ def apply_reloc_filter(self, fix_filter=None, inplace=False):
         if not inplace:
             return frame
 
-    @cachedproperty
+    @cached_property
     def distance_from_centroid(self):
         # calculate the distance between the centroid and the fix
         gs = self.geometry.to_crs(crs=self.estimate_utm_crs())
         return gs.distance(gs.unary_union.centroid)
 
-    @cachedproperty
+    @cached_property
     def cluster_radius(self):
         """
         The cluster radius is the largest distance between a point in the relocationss and the
@@ -300,7 +300,7 @@ def cluster_radius(self):
         distance = self.distance_from_centroid
         return distance.max()
 
-    @cachedproperty
+    @cached_property
     def cluster_std_dev(self):
         """
         The cluster standard deviation is the standard deviation of the radii from the centroid

ecoscope/base/utils.py

@@ -74,33 +74,6 @@ def create_meshgrid(
     return gs.to_crs(out_crs)
 
 
-class cachedproperty:  # noqa
-    """
-    The ``cachedproperty`` is used similar to :class:`property`, except
-    that the wrapped method is only called once. This is commonly used
-    to implement lazy attributes.
-    """
-
-    def __init__(self, func):
-        self.func = func
-
-    def __doc__(self):
-        return getattr(self.func, "__doc__")
-
-    def __isabstractmethod__(self):
-        return getattr(self.func, "__isabstractmethod__", False)
-
-    def __get__(self, obj, objtype=None):
-        if obj is None:
-            return self
-        value = obj.__dict__[self.func.__name__] = self.func(obj)
-        return value
-
-    def __repr__(self):
-        cls = self.__class__.__name__
-        return f"<{cls} func={self.func}>"
-
-
 def groupby_intervals(df, col, intervals):
     """
     Parameters