DOC remove caching in wikipedia_principal_eigenvector example
@@ -42,8 +42,6 @@ import numpy as np
from scipy import sparse
-from joblib import Memory
-
from sklearn.decomposition import randomized_svd
from urllib.request import urlopen
@@ -74,8 +72,6 @@ for url, filename in resources:
# #############################################################################
# Loading the redirect files
-memory = Memory(cachedir=".")
-
def index(redirects, index_map, k):
"""Find the index of an article name after redirect resolution"""
@@ -124,8 +120,6 @@ def get_redirects(redirects_filename):
return redirects
-# disabling joblib as the pickling of large dicts seems much too slow
-#@memory.cache
def get_adjacency_matrix(redirects_filename, page_links_filename, limit=None):
"""Extract the adjacency graph as a scipy sparse matrix
