Immutable numpy array?

Is there a simple way to create an immutable NumPy array?

If one has to derive a class from ndarray to do this, what’s the minimum set of methods that one has to override to achieve immutability?

Answers:

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Method 1

You can make a numpy array unwriteable:

a = np.arange(10)
a.flags.writeable = False
a[0] = 1
# Gives: ValueError: assignment destination is read-only

Also see the discussion in this thread:

http://mail.scipy.org/pipermail/numpy-discussion/2008-December/039274.html

and the documentation:

http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flags.html

Method 2

I have a subclass of Array at this gist: https://gist.github.com/sfaleron/9791418d7023a9985bb803170c5d93d8

It makes a copy of its argument and marks that as read-only, so you should only be able to shoot yourself in the foot if you are very deliberate about it. My immediate need was for it to be hashable, so I could use them in sets, so that works too. It isn’t a lot of code, but about 70% of the lines are for testing, so I won’t post it directly.

Note that it’s not a drop-in replacement; it won’t accept any keyword args like a normal Array constructor. Instances will behave like Arrays, though.

Method 3

Setting the flag directly didn’t work for me, but using ndarray.setflags did work:

a = np.arange(10)
a.setflags(write=False)
a[0] = 1  # ValueError

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0