backports.cached_property

Introduction

Python 3.8 adds a great decorator to functools: cached_property. Technically all required APIs were available since Python 3.6, but releases until 3.8 don't have it and users need to live with this reality.

Therefore, this package backports said feature to Python 3.6 and 3.7.

How to use

Simply do

from backports.cached_property import cached_property

and it will work as documented upstream (see copy below).

The implementation of our cached_property backport is very close to that of the future Python 3.8 standard library. For Python >= 3.8, the actual cached_property from functools is passed through, of course.

class cached_property

Transform a method of a class into a property whose value is computed once and then cached as a normal attribute for the life of the instance. Similar to property, with the addition of caching. Useful for expensive computed properties of instances that are otherwise effectively immutable.

class DataSet:
    def __init__(self, sequence_of_numbers):
        self._data = sequence_of_numbers

    @cached_property
    def stdev(self):
        return statistics.stdev(self._data)

    @cached_property
    def variance(self):
        return statistics.variance(self._data)

Note

This decorator requires that the __dict__ attribute on each instance be a mutable mapping. This means it will not work with some types, such as metaclasses (since the __dict__ attributes on type instances are read-only proxies for the class namespace), and those that specify __slots__ without including __dict__ as one of the defined slots (as such classes don't provide a __dict__ attribute at all).