Parallelize a list consolidation in Python -


i have sorted list of "box definitions" consolidate. list looks like:

big_list = [\ # ... # ... [3, 4, 5, 4, 5, 6, 65],\ [3, 4, 5, 4, 5, 6, 60],\ [3, 4, 5, 4, 5, 6, 55],\ [3, 4, 5, 4, 5, 6, 52],\ [3, 4, 5, 4, 5, 6, 23],\ [3, 4, 5, 4, 5, 6, 17],\ [3, 4, 5, 4, 5, 6, 0],\ [5, 8, 9, 6, 9, 10, 90],\ [5, 8, 9, 6, 9, 10, 84],\ [5, 8, 9, 6, 9, 10, 32],\ [5, 8, 9, 6, 9, 10, 0],\ # ... # ... [750, 800, 900, 751, 801, 901, 97],\ [750, 800, 900, 751, 801, 901, 24],\ [750, 800, 900, 751, 801, 901, 17],\ [750, 800, 900, 751, 801, 901, 16],\ [750, 800, 900, 751, 801, 901, 0]\ # ... # ... ]

where box "format" is: [x1, y1, z1, x2, y2, z2, attribute], , can assume dx=1, dy=1, dz=1

also, can assume list has been sorted like:

big_list=sorted(big_list, key=lambda n:n[6], reverse=true) big_list=sorted(big_list, key=lambda n:n[2]) big_list=sorted(big_list, key=lambda n:n[1]) big_list=sorted(big_list, key=lambda n:n[0])

the list may several millions of items long, , reduce list discrete "box" gets highest "attribute"...so in case like:

reduced_big_list = [\ [3, 4, 5, 4, 5, 6, 65],\ [5, 8, 9, 6, 9, 10, 90],\ [750, 800, 900, 751, 801, 901, 97]\ ]

the method using on list like:

i = 0  while < len(big_list)-1:      if big_list[i][0]==big_list[i+1][0]\      , big_list[i][1]==big_list[i+1][1]\      , big_list[i][2]==big_list[i+1][2] \      , big_list[i][6] >= big_list[i+1][6]:           del big_list[i+1]      else:           i=i+1

the problem when list "long" (10 million+ "boxes"), process very, slow.

is there clever way parallelize list "decimation" process or perhaps quicken process?

the slowness call del, moves items of complete tail of list 1 step. in case, don't use del. make instead new list, starting empty list , appending items want keep.


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