Support NumPy 2.0 about polars

[ritchie46]

Yes, we must pin numpy 1.0 until then.

[ritchie46]

If blocked, it isn't p-high at the moment. :D

[stinodego]

If blocked, it isn't p-high at the moment. :D

Indeed. We should have something to mark "high importance" though - which this certainly is.

[braaannigan]

I've encountered a seg fault where another library is converting a Polars dataframe to numpy with numpy 2.0.0 and polars 0.20.31.
Downstream issue is here: Nixtla/mlforecast#354

import polars as pl
df = pl.from_repr("""┌───────────┬─────────────────────┬────────────┐
│ unique_id ┆ ds                  ┆ y          │
│ ---       ┆ ---                 ┆ ---        │
│ cat       ┆ datetime[ns]        ┆ f64        │
╞═══════════╪═════════════════════╪════════════╡
│ id_00     ┆ 2000-01-01 00:00:00 ┆ 17.519167  │
│ id_00     ┆ 2000-01-02 00:00:00 ┆ 87.799695  │
│ id_00     ┆ 2000-01-03 00:00:00 ┆ 177.442975 │
│ id_00     ┆ 2000-01-04 00:00:00 ┆ 232.70411  │
│ id_00     ┆ 2000-01-05 00:00:00 ┆ 317.510474 │
│ id_19     ┆ 2000-03-09 00:00:00 ┆ 28.541985  │
│ id_19     ┆ 2000-03-10 00:00:00 ┆ 33.841384  │
│ id_19     ┆ 2000-03-11 00:00:00 ┆ 38.878866  │
│ id_19     ┆ 2000-03-12 00:00:00 ┆ 43.675512  │
│ id_19     ┆ 2000-03-13 00:00:00 ┆ 49.603114  │
└───────────┴─────────────────────┴────────────┘""")
df["ds"].to_numpy()

This gives a seg fault.

[braaannigan]

@ritchie46
In fact this is enough to produce a seg fault:

import datetime

import polars as pl

pl.Series([datetime.datetime.now()]).to_numpy()

[stinodego]

Yes, we are familiar. Nothing we can do about it at the moment, see the linked issue.

[jmoralez]

Nothing we can do about it at the moment

You could also pin numpy here

polars/py-polars/pyproject.toml

Line 52 in 14dd2ca

numpy = ["numpy >= 1.16.0"]

in case you're planning a release soon, that'd ensure compatibility when installing polars[numpy]