from joblib import Memory mem = Memory(location='cache_dir', verbose=0) @mem.cache def my_func(x): # do some expensive computations return resultIn this example, the Memory function creates a cache directory called "cache_dir" where it stores the results of the my_func function. The @mem.cache decorator is used to make the function use caching functionality. Joblib.memory can be used to speed up the execution of complicated functions with many parameters and costly computations. By storing the results of function calls in cache, we can avoid redundant computation and, as a result, speed up the execution of our code. Joblib is a package library that is used to create parallel computing patterns for Python.