Checks
Reproducible example
from sklearn.datasets import fetch_openml
co2 = fetch_openml(data_id=41187, as_frame=True)
import polars as pl
co2_data = pl.DataFrame(co2.frame[["year", "month", "day", "co2"]]).select(
pl.date("year", "month", "day"), "co2"
)
co2_data["date"].to_numpy()Log output
The gdb back-trace:
Thread 1 "python" received signal SIGSEGV, Segmentation fault.
0x00007fffad715f3c in numpy::datetime::TypeDescriptors::from_unit ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
(gdb) bt
#0 0x00007fffad715f3c in numpy::datetime::TypeDescriptors::from_unit ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#1 0x00007fffacbf8854 in <alloc::vec::Vec<T> as numpy::convert::IntoPyArray>::into_pyarray_bound ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#2 0x00007fffad209daf in polars::interop::numpy::to_numpy_series::series_to_numpy_with_copy ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#3 0x00007fffad204fac in polars::interop::numpy::to_numpy_series::series_to_numpy ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#4 0x00007fffad4a41e5 in polars::interop::numpy::to_numpy_series::<impl polars::series::PySeries>::__pymethod_to_numpy__ ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#5 0x00007fffacb342a1 in pyo3::impl_::trampoline::trampoline ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#6 0x00007fffad4a4511 in polars::interop::numpy::to_numpy_series::_::__INVENTORY::trampoline ()
from /home/lesteve/micromamba/envs/del312/lib/python3.12/site-packages/polars/polars.abi3.so
#7 0x00005555557836a1 in method_vectorcall_VARARGS_KEYWORDS (
func=0x7fffb0b12840, args=0x7ffff7f9c120, nargsf=<optimized out>,
kwnames=<optimized out>)
at /usr/local/src/conda/python-3.12.4/Objects/descrobject.c:365
#8 0x0000555555775c9f in _PyObject_VectorcallTstate (
kwnames=0x7fffaaecf880, nargsf=9223372036854775809,
args=0x7ffff7f9c120, callable=0x7fffb0b12840,
tstate=0x555555bf2078 <_PyRuntime+459704>)
at /usr/local/src/conda/python-3.12.4/Include/internal/pycore_call.h:92
#9 PyObject_Vectorcall (callable=0x7fffb0b12840, args=0x7ffff7f9c120,
nargsf=9223372036854775809, kwnames=0x7fffaaecf880)
at /usr/local/src/conda/python-3.12.4/Objects/call.c:325
#10 0x0000555555667f20 in _PyEval_EvalFrameDefault (
tstate=<optimized out>, frame=0x7ffff7f9c0a0,
throwflag=<optimized out>) at Python/bytecodes.c:2714
#11 0x000055555581b6fe in PyEval_EvalCode (co=co@entry=0x7ffff7be41d0,
globals=globals@entry=0x7ffff7ca1e40,
locals=locals@entry=0x7ffff7ca1e40)
at /usr/local/src/conda/python-3.12.4/Python/ceval.c:578
#12 0x000055555583f7ba in run_eval_code_obj (
tstate=tstate@entry=0x555555bf2078 <_PyRuntime+459704>,
co=co@entry=0x7ffff7be41d0, globals=globals@entry=0x7ffff7ca1e40,
locals=locals@entry=0x7ffff7ca1e40)
at /usr/local/src/conda/python-3.12.4/Python/pythonrun.c:1722
#13 0x000055555583aa9b in run_mod (mod=mod@entry=0x555555cbde88,
filename=filename@entry=0x7ffff7c5a830,
globals=globals@entry=0x7ffff7ca1e40,
locals=locals@entry=0x7ffff7ca1e40,
flags=flags@entry=0x7fffffffb3c0, arena=arena@entry=0x7ffff7bc3c50)
at /usr/local/src/conda/python-3.12.4/Python/pythonrun.c:1743
#14 0x00005555558537b0 in pyrun_file (fp=fp@entry=0x555555bf5590,
filename=filename@entry=0x7ffff7c5a830, start=start@entry=257,
globals=globals@entry=0x7ffff7ca1e40,
locals=locals@entry=0x7ffff7ca1e40, closeit=closeit@entry=1,
flags=0x7fffffffb3c0)Issue description
Seen in scikit-learn examples when upgrading to numpy 2 see scikit-learn/scikit-learn#29388.
Created a smaller reproducer that still needs scikit-learn. I am sure you could craft a reproducer without scikit-learn.
To create the environment run the snippet:
conda create -n del312 python=3.12 -y
pip install polars numpy pandas scikit-learn
Installing numpy<2 fixes the issue pip install 'numpy<2'
Expected behavior
No error
Installed versions
Details
--------Version info---------
Polars: 1.0.0
Index type: UInt32
Platform: Linux-6.9.5-arch1-1-x86_64-with-glibc2.39
Python: 3.12.4 | packaged by conda-forge | (main, Jun 17 2024, 10:23:07) [GCC 12.3.0]
----Optional dependencies----
adbc_driver_manager: <not installed>
cloudpickle: <not installed>
connectorx: <not installed>
deltalake: <not installed>
fastexcel: <not installed>
fsspec: <not installed>
gevent: <not installed>
great_tables: <not installed>
hvplot: <not installed>
matplotlib: <not installed>
nest_asyncio: <not installed>
numpy: 2.0.0
openpyxl: <not installed>
pandas: 2.2.2
pyarrow: <not installed>
pydantic: <not installed>
pyiceberg: <not installed>
sqlalchemy: <not installed>
torch: <not installed>
xlsx2csv: <not installed>
xlsxwriter: <not installed>
Checks
Reproducible example
Log output
Issue description
Seen in scikit-learn examples when upgrading to numpy 2 see scikit-learn/scikit-learn#29388.
Created a smaller reproducer that still needs scikit-learn. I am sure you could craft a reproducer without scikit-learn.
To create the environment run the snippet:
Installing
numpy<2fixes the issuepip install 'numpy<2'Expected behavior
No error
Installed versions
Details