API / BUG: copy non-Index arrays in Index construction to avoid data corruption
Would close https://github.com/pandas-dev/pandas/issues/34364 and https://github.com/pandas-dev/pandas/issues/42934

The idea here is that since the Index is assumed to be immutable and caches things like the hashtable, we should avoid that a user can actually mutate those values through normal pandas functionality by making a copy when creating an Index from array-like data. 
I made the exception for an object that is already an Index (since this is immutable, you can't mutate this through normal pandas functionality, and typically this will already made a copy when first being created). This should avoid too many copies on repeated `ensure_index` calls.

Still need to add more tests (covering the segfault case), docs, and do the same in the Index subclasses' `__new__`, in case we want something like this.


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@phofl I should have first looked at the tests you already added in https://github.com/pandas-dev/pandas/pull/51803 .., but so this might be duplicating part of the ones you also wrote (and if we want to do this, I can probably take some of the tests you added there) Do we want to distinguish priority-wise between the segfaults generated in #34364 vs more general incorrect-but-not-segfaulting cases that can occur when a user modifies `index._values`?

The general case I think is hard-bordering-on-impossible unless we make a copy in the index.pyx code that the user cannot access.  Unless we're willing to go that far, my inclination is to avoid making extra copies to avoid the perf hit since this is a reasonably rare problem (that becomes even more rare with CoW IIUC).

For the segfault I wonder if we can use a hashing mechanism that doesn't depend on interning? Do you have an idea how to fix just the segfault? How easy / feasible is the "use a hashing mechanism that doesn't depend on interning" idea? (I am not familiar with our hashing code, so genuinely don't know)

And I also think the incorrect behaviour is quite problematic. Actually, with a segfault you know something went wrong and you need to fix "something" (although finding out the "something" can be hard in this case, since you don't have a clear error). While with the incorrect behaviour, you just can get silently wrong results in your analysis.

> The general case I think is hard-bordering-on-impossible unless we make a copy in the index.pyx code that the user cannot access. 

I am doing the copy here on Index construction, to avoid doing a copy when creating the engine (which I think decreases the overall number of extra copies) This pull request is stale because it has been open for thirty days with no activity. Please [update](https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#updating-your-pull-request) and respond to this comment if you're still interested in working on this. @jorisvandenbossche what's the status here? We can close, that’s not an issue anymore with copy on write In 3.0