How to convert 3d array as string - python-3.x

I need to convert a 3d array I have in Python3 into a string with a specific format. My current 3d array is below:
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]
I need this as a string, but also want to replace any instance of 0 and make it into the string '----'. If a value is not 0, then leave it.
I tried using join: ''.join(str(e) for e in myArray)
but the format did not come out as I wanted.
I expected my results to look like this:
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
1 ---- ---- ---- ---- ---- ----
But my format turned out like this using the join method:
[[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]][[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]][[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]][[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]]


You need to loop over all of the layers of lists in your nested list. This will require nested list comprehension. Try this:
'\n\n'.join('\n'.join(' '.join(str(x or '----')for x in y)for y in z)for z in myArray)
Note the x or '----' bit. That will evaluate to the first Truthy value. Since zeroes are Falsey, you'll get the dashes if x is zero, or the actual value if it's not.


First, I have more formally defined your 3D array:
mylist = [[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]],
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]],
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]],
[[1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0], [1, 0, 0, 0, 0]]]
This way I have a list of lists of lists, instead of 4 lists of lists that happen to be written in a row, with this format, we can just loop through every element and continue adding to some string as we go:
abcd = ""
for i in mylist:
for j in i:
for k in j:
if(k): # might as well say if k is not 0
abcd = abcd +str(k)
else:
abcd = abcd +'---'
abcd = abcd + "\n"
abcd = abcd + "\n"
print(abcd)
This will give the desired output, but #mypetlion's method is nicer and more pythonic

Related

Difference between dp = [[0]*8]*8 and dp2 = [([0]*8) for i in range(8)] [duplicate]

This question already has answers here:
List of lists changes reflected across sublists unexpectedly
(17 answers)
Closed 8 months ago.
What is the diference between defining with dp = [[0]*8]*8 and dp2 = [([0]*8) for i in range(8)] ? They seem to be equal but when I set one value in one case and the other they set it diferently. Why ?
Thanks
>>> dp = [[0]*8]*8
>>> dp
[[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]]
>>> dp2 = [([0]*8) for i in range(8)]
>>> dp2
[[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]]
>>> dp[1][4] = 1
>>> dp2[1][4] = 1
>>> dp
[[0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0]]
>>> dp2
[[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]]
>>>

They are not equal
dp = [[0]*8]*8 here there is only one inner list obejct. It's like below
a=[0]*8
dp=[a,a,a,a,a,a,a,a]
That's why when you change item in dp[1] all others are changed. There is only one inner list. dp holds multiple refereces for that same list object.
dp2 = [([0]*8) for i in range(8)] here multiple inner list objects are created. It's like below,
dp2=[[0]*8,[0]*8,[0]*8,[0]*8,[0]*8,[0]*8,[0]*8,[0]*8]
That's why you can change only 1 element without affecting others

How to optimize the following function

I'm having a bottleneck issue with the following function. Takes too long to process the list of lists. The list that I am about to detail, has millions of lists (could hold up to almost 40M lists).
The function iterates over the list of lists and for every list where its 10th element contains a -1, gets its index position. Then checks if for the same index position of the -1, in the 1st, 2nd and 3rd elements of the list the same index position has value 0, if so that list most be deleted.
Let us see an example with just one list:
list_item = [[0], [0, 0, 1], [0, 1, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]]
As we can see, the 10th element (I'm considering the very first list item as 0), [-1, 0, 0], -1 is in index position 0. Items 1st, 2nd and 3rd ([0, 0, 1], [0, 1, 0], [0, 0, 0]) have 0 for the same index position as -1, hence the whole list must be deleted fro the list.
import copy
def filter_vnf_departures(states):
""" Filters out states where the VNF departure can not occur """
temp = states.copy()
for state in states:
vnf_index = [i for i, e in enumerate(state[10]) if e == -1]
if -1 in state[10]:
ec1 = state[1][vnf_index[0]]
ec2 = state[2][vnf_index[0]]
cdc = state[3][vnf_index[0]]
if ec1 == 0 and ec2 == 0 and cdc == 0:
temp.remove(state)
return temp
Let me, as an example, detail an input list to the function. For obvious reasons, this list is very small compared to the ones that I have to deal.
input_list = [[[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]]]
And this is the out put list that the function must return:
output_list = [[[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]]]
Can the function be optimized so it processes everything faster?

This seems to be faster when I try via timeit:
def filter_vnf_departures2a(states):
for state in states:
if sum(state[10]) != -1:
yield state
continue
vnf_index = state[10].index(-1)
if state[1][vnf_index] or state[2][vnf_index] or state[3][vnf_index]:
yield state
Though I personally like this second alternative. It seems faster than the original, but slower than the first alternative above.
def filter_vnf_departures2b(states):
for state in states:
vnf_index = next((i for i,v in enumerate(state[10]) if v == -1), None)
if vnf_index is None or state[1][vnf_index] or state[2][vnf_index] or state[3][vnf_index]:
yield state
Given:
input_list = [[[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, -1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, -1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]]]
output_list = [[[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [-1, 0, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 1, 0]], [[1], [1, 0, 0], [1, 0, 0], [0, 0, 0], [1, 0, 0], [1, 0, 0], [1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]]]
def filter_vnf_departures(states):
temp = copy.copy(states)
for state in states:
vnf_index = [i for i, e in enumerate(state[10]) if e == -1]
if sum(state[10]) == -1:
ec1 = state[1][vnf_index[0]]
ec2 = state[2][vnf_index[0]]
cdc = state[3][vnf_index[0]]
if ec1 == 0 and ec2 == 0 and cdc == 0:
temp.remove(state)
return temp
Then I get:
print(filter_vnf_departures(input_list) == list(filter_vnf_departures2a(input_list)))
print(filter_vnf_departures(input_list) == list(filter_vnf_departures2b(input_list)))
as:
True
True

Returning a filtered version of the list as opposed to a full copy with elements removed should be faster.
Something like:
return [s for s in states if keep(s)]
where keep is a function that returns True is state s is to be kept and False otherwise.

How to change only the diagonal elements of a 2D list?

So I am trying to create an NxN 2D array and then change its diagonal elemets to 1. Here is my code:
arr=[1,1,1,2,2,2]
table=[[0]*len(arr)]*len(arr)
for i in range(0,len(arr)):
table[i][i]=1
print(table)
However, whenever I run this code, I get this output:
[[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1]]
I am looking to get this:
[[1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]]
I have been staring at my code for hours and I cannot figure out what's wrong

The interesting thing about this is that you are really only editing one list in the for loop, but there are just five pointers to that list. (In this case, the list would be [0, 0, 0, 0, 0, 0].) You can see this by printing the id of each list in table by using id():
>>> for t in table:
print(id(t))
2236544254464
2236544254464
2236544254464
2236544254464
2236544254464
2236544254464
Your numbers are likely different than mine, but they are all the same number, nevertheless. You also can see that the edits to one list are applied to the others in table by putting a print(table) statement after each index assignment statement.
So in order to 'fix' this, I would recommend using list comprehension instead. For example:
table = [[0]*len(arr) for _ in range(len(arr))]
If you checkout the ids of each list:
>>> for t in table:
print(id(t))
2236544617664
2236544616064
2236544616320
2236544615872
2236544618368
2236544622720
Since they are different, you can now use the method for changing only the diagonals:
>>> for i in range(0,len(arr)):
table[i][i]=1
>>> table
[[1, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]]

Your 2D "array" contains 6 lists which are the same list. Changes to any of those lists will also be reflected in the other lists. Consider this:
>>> l = [0] * 6
>>> x = [l]
>>> l[0] = 1
>>> l
[1, 0, 0, 0, 0, 0]
>>> x
[[1, 0, 0, 0, 0, 0]]
>>> x = [l, l, l]
>>> x
[[1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0]]
>>> x[-1][-1] = 100
>>> x
[[1, 0, 0, 0, 0, 100], [1, 0, 0, 0, 0, 100], [1, 0, 0, 0, 0, 100]]
This is because the list x contains the list l, so any changes to l are also seen through the reference to the same list in x.
The problem is when multiplying mutable objects because it creates multiple references to the same mutable object.
You should initialise your table like this:
table = [[0 for j in range(len(arr))] for i in range(len(arr))]
or
table = [[0] * len(arr) for i in range(len(arr))]
which, despite the use of multiplication, works because each list is different.

You can create your table and populate it simultaneously in nested loops:
arr=[1,1,1,2,2,2]
table = []
for i in range(len(arr)):
table.append([0]*len(arr))
for j in range(len(arr)):
if i == j:
table[i][j] = 1
print(table)
#[[1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 1]]

Interesting.
Try to use numpy to avoid list trap:
import numpy as np
org_row = [0]*5
l = [org_row]*5
x = np.array(l, np.int32)
for i in range(len(x)):
x[i][i]=1
print(x)
output>:
output>
[[1 0 0 0 0]
[0 1 0 0 0]
[0 0 1 0 0]
[0 0 0 1 0]
[0 0 0 0 1]]

Why does recursion not continue?

I have two list. first list is a maze. It start 'O' and must be finished 'X'.
maze_list=[[0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 1, 'O'],
[0, 0, 1, 0, 1, 0],
[0, 1, 1, 1, 1, 0],
['X', 1, 0, 1, 0, 0],
[0, 1, 0, 1, 1, 1]]
path_list=[[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]]
This part is finding start position.
column_size=len(maze_list)
row_size=len(maze_list[0])
def find_SF_position(X):
liste=[]
for i in range(column_size):
for j in range(column_size):
if maze_list[i][j]==X:
liste.append(i)
liste.append(j)
return liste
s_p=find_SF_position('O') #[1,5]
f_p=find_SF_position('X') #[4,0]
This part is main algorithm. x is for horizontal position. y is for vertical position
def solve_maze(maze,road,x,y):
global column_size
global row_size
road[y][x]=1
print(y,x)
#left
if x>0 and maze[y][x-1]==1 and road[y][x-1]==0:
return solve_maze(maze,road,x-1,y)
#up
if y>0 and maze[y-1][x]==1 and road[y][x-1]==0:
return solve_maze(maze,road,x,y-1)
#right
if x>row_size and maze[y][x+1]==1 and road[y][x-1]==0:
return solve_maze(maze,road,x+1,y)
#down
if y>column_size and maze[y+1][x]==1 and road[y][x-1]==0:
return solve_maze(maze,road,x,y+1)
if maze[x][y]=='X':
return path_list
solve_maze(maze_list,path_list,s_p[1],s_p[0])
print(path_list)
I can't understand why it isn't working. It's start 'O'(maze_list[1,5]), it fill maze_list[1,4] then stop.
Finally path_list must be like this
path_list=[[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 1, 0],
[0, 1, 1, 1, 1, 0],
[1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]]

You have a few problems in your code:
First your right and down conditions are reversed: x can never be greater than row_size. What you want to check is that x is not on the right border, meaning: x < row_size - 1. Same logic goes for the down case
Seems like you have a little copy-paste issue there: for example the road condition for up should be: road[y-1][x]==0. Same logic goes to all other cases.
Your condition to finding the end has a problematic logic: You check if the current cell is the 'X', but each step is only taken if there is 1 in the next cell, so how will you get to the 'X'? For example, after fixing above errors, the output I got was:
[0, 0, 0, 0, 0, 0]
[0, 0, 0, 0, 1, 1]
[0, 0, 0, 0, 1, 0]
[0, 1, 1, 1, 1, 0]
[0, 1, 0, 0, 0, 0]
[0, 1, 0, 0, 0, 0]
As you can see, the 'X' was missed as the condition for down was taken at (4, 1) and a dead-end was reached
Lastly, what happens if you reach a dead-end? Your algorithm always takes the first step with conditions met, but what happens when you encounter an intersection? You need to check all possible paths. That's the point of recursion. The way you did it now doesn't add much over a loop.

ValueError: Unknown label type for classification_report

I'm trying to evaluate the model for multiclass classification using classification_report module of the sklean package.
Dimensions of y_pred: (1000,36)
Dimensions of y_test: (1000,36)
I tried calling the classification_report on the 2 arrays i.e y_test and y_pred
def display_results(y_test,y_pred,column_name=labels):
print(classification_report(y_test,y_pred,target_names=labels))
With this code I get:
ValueError: Unknown label type: (array([[1, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 1, 1, 0],
...,
[1, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 0, 0, 0]]), array([[1, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 0, 0, 0],
...,
[1, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[1, 0, 0, ..., 0, 0, 0]]))
I was expecting to get the Precision, Recall, F1 and the total average metrics for all the columns based on the labels passed to the function.

For your error you need np.hstack
Works best where you have multiclass-multioutput from a classifier
from sklearn.utils.multiclass import type_of_target
type_of_target(y_test)
type_of_target(y_pred)
>>'multiclass-multioutput'
So, your solution is
print(classification_report(np.hstack(y_test),np.hstack(y_pred)))

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