Dffective dumping
joblib, which is optimized for handling NumPy arrays and large objects efficiently.
from joblib import dump, load # Save a model dump(model, 'model.joblib') # Load the model loaded_model = load('model.joblib')
Optimizing Workflows with Computation Caching
from joblib import Memory memory = Memory('cache_dir') @memory.cache def expensive_function(x): return sum(range(x))