Python slicing

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  • a[start:stop] items start through stop-1
  • a[start:] items start through the rest of the array
  • a[:stop] items from the beginning through stop-1
  • a[:] a copy of the whole array
  • a[-1] last item in the array
  • a[-2:] last two items in the array
  • a[:-2] everything except the last two items
  • a[::-1] all items in the array, reversed
  • a[1::-1] the first two items, reversed
  • a[-3::-1] everything except the last two items, reversed
  • a[:-3:-1] the last two items, reversed
  • a[::2] extracts elements of list at even positions
  • a[1::2] extracts elements of list at odd positions
  • a[::3] similar to above
  • a[1::3] similar to above

If we adopt the notation [start:stop:step], start is always inclusive, stop is always exclusive.

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a = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 

print(a[5:2])      # []
print(a[5:2:1])    # []
print(a[5:2:-1])   # [6, 5, 4] 
print(a[-5:-8:-1]) # [6, 5, 4] 
print(a[-5:-8:1])  # []
print(a[-5:-8])    # [] 
print(a[-2:-9:-2]) # [9, 7, 5, 3]    
print(a[-2:-9:-3]) # [9, 6, 3]

One can substitute None for any of the empty spaces. For example [None:None] makes a whole copy. This is useful when you need to specify the end of the range using a variable and need to include the last item.

Slicing builtin types returns a copy but that’s not universal. Notably, [slicing NumPy arrays] (https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html) returns a view that shares memory with the original.