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Numpy syntax comes to mind. The extra commas often aren’t valid pure Python but are required for some operations on numpy arrays. I don’t know how this works un

Numpy syntax comes to mind. The extra commas often aren’t valid pure Python but are required for some operations on numpy arrays. I don’t know how this works under the hood, but expect it’s a state machine under the numpy ndarray looking for the extra commas and such. i.e. some_array[0:5,0] which isn’t valid pure Python notation.

kzrdude 5y ago
Extra commas are "valid in pure python" in the following sense that I can demonstrate. Open ipython3 In [3]: class Test: ...: def __getitem__(self, index): ...: print(index) ...: In [4]: Test()[1, 2, 1:3, ..., :] (1, 2, slice(1, 3, None), Ellipsis, slice(None, None, None)) It's valid and we get the complicated tuple of integers, slices, ellipsis etc as printed. Numpy has existed for a long time. Its needs have been taken care of in upstream Python, to a big extent, and other libraries can use the same features.
- ohyoutravel 5y ago
  Interesting! Neither myself nor my coworkers could get the snippet I posted working outside the context of an ndarray, so I had speculated at that time that it there was something else going on under the hood. You seem to have a much better grasp of Python than us, would you mind posting an example where the snipped I posted successfully accesses data from an array in pure Python? That way I can not only take the L, but correct the record and learn something in the process.
  - kzrdude 5y ago
    This program is quick & lazy but it uses a 1D python list and pretends it's a 2D list. It implements 2D slicing, giving you a square subset just like ndarray. It doesn't intend to be all correct or nice or useful. https://www.pythonmorsels.com/p/2rk5t/ https://www.pythonmorsels.com/p/2rk5t/ Is laziness a virtue? I reused the slicing implementation in `range(foo)[index]` so I didn't need to do that logic myself.
    - ohyoutravel 5y ago
      Very nice!

kzrdude 5y ago

Extra commas are "valid in pure python" in the following sense that I can demonstrate. Open ipython3 In [3]: class Test: ...: def __getitem__(self, index): ...: print(index) ...: In [4]: Test()[1, 2, 1:3, ..., :] (1, 2, slice(1, 3, None), Ellipsis, slice(None, None, None)) It's valid and we get the complicated tuple of integers, slices, ellipsis etc as printed. Numpy has existed for a long time. Its needs have been taken care of in upstream Python, to a big extent, and other libraries can use the same features.

ohyoutravel 5y ago
Interesting! Neither myself nor my coworkers could get the snippet I posted working outside the context of an ndarray, so I had speculated at that time that it there was something else going on under the hood. You seem to have a much better grasp of Python than us, would you mind posting an example where the snipped I posted successfully accesses data from an array in pure Python? That way I can not only take the L, but correct the record and learn something in the process.
- kzrdude 5y ago
  This program is quick & lazy but it uses a 1D python list and pretends it's a 2D list. It implements 2D slicing, giving you a square subset just like ndarray. It doesn't intend to be all correct or nice or useful. https://www.pythonmorsels.com/p/2rk5t/ https://www.pythonmorsels.com/p/2rk5t/ Is laziness a virtue? I reused the slicing implementation in `range(foo)[index]` so I didn't need to do that logic myself.
  - ohyoutravel 5y ago
    Very nice!