I have 2 lists of int and sparse matrix : list_index = [1,1,2,3,3,4,4,5] and matrix_user = [sparse1, sparse2, sparse3, sparse4, sparse5, sparse6]
I want to have a list of sublist, each sublist is made of a list of int and a sparse matrix : [ [[1,1,2,3,3],[sparse1, sparse2, sparse3, sparse4]] , [[4,4,5],[sparse5, sparse6]] , ......] of length ~ 90 (to run in parallel later one) whith each sublist[0] containing not overlapping value.
To cut the 2 input lists into 90 sections I do the following :
# cut the data into chunk to run in parallel
list_index = dfuser['idx'].tolist()
matrix_user = encoder.fit_transform(dfuser[['col1','col2']].values)
sizechunk = 90
sizelist = int(len(list_index)/sizechunk)
if len(list_index)%sizechunk!=0 : sizelist += 1
list_all = []
for i in range(sizechunk) :
if i*sizelist > len(list_index) : continue
if (i+1)*sizelist < len(list_index) : list_all.append( [list_index[i*sizelist:(i+1)*sizelist] , matrix_user_encoded.tocsr()[i*sizelist:(i+1)*sizelist] ] )
else : list_all.append( [list_index[i*sizelist:] , matrix_user_encoded.tocsr()[i*sizelist:] ])
This give me a list of 90 chunks : [ [[1,1,2,3],[sparse1, sparse2, sparse3]] , [[3, 4,4,5],[sparse4, sparse5, sparse6]] , ......]
Then I filter in order each sublist have different index value :
i=0
size_list = len(list_all)
while i<size_list-1 :
last_elem = list_all[i][0][len(list_all[i][0])-1]
first_elem = list_all[i+1][0][0]
first_sparse = list_all[i+1][1][0]
while first_elem==last_elem :
list_all[i][0].append(first_elem)
list_all[i][1] = sp.vstack((list_all[i][1],first_sparse))
list_all[i+1][0] = list_all[i+1][0][1:]
list_all[i+1][1] = list_all[i+1][1][1:]
if len(list_all[i+1][0])==0 :
list_all.remove(list_all[i+1])
size_list -= 1
if i+1==size_list : break
first_elem = list_all[i+1][0][0]
i +=1
It works but as I have lots of input (~18 millions entries) it takes 6h !!!!!
I need my program to run in less than 2h as it needs to be called multiple times a day. Does a python command exists to cut my 2 lists depending on the pattern of the first sublist ?
Thank you for your help!
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