%FILENAME%
python-polars-1.35.1-1-x86_64.pkg.tar.zst

%NAME%
python-polars

%BASE%
python-polars

%VERSION%
1.35.1-1

%DESC%
Blazingly fast DataFrames library using Apache Arrow Columnar Format as memory model

%CSIZE%
1163145

%ISIZE%
11394240

%MD5SUM%
335ad592c017a71f65d9066bee190248

%SHA256SUM%
cf8fb57f0d20acfad2cd1b3978573e4bd388471b4deafe3cb23864b30b796a7f

%PGPSIG%
iHUEABYKAB0WIQQ4EAwkN2zV9u1P9LRpGEAMJwMEDAUCaQSmugAKCRBpGEAMJwMEDNOPAQDH0Iw19JwQFqCJEC49oDzSxzbi8jUDGqBkMlLv89vXCQEArRcE9um7Z8qnVKSqLBZ2t7FCvocOAi9OI9vqm79ymQM=

%URL%
https://www.pola.rs/

%LICENSE%
MIT

%ARCH%
x86_64

%BUILDDATE%
1761911799

%PACKAGER%
Bert Peters <bertptrs@archlinux.org>

%DEPENDS%
python
python-numpy
python-polars-runtime-64

%OPTDEPENDS%
python-pandas: for interoperability with pandas frames
python-pyarrow: for interoperability with arrow types
python-pytz: to enable conversion to python datetimes with timezones
python-fsspec: to transparently open files locally or remotely

%MAKEDEPENDS%
maturin
rustup
python-installer
python-build
python-wheel
python-setuptools

%CHECKDEPENDS%
python-pytest
python-pytest-xdist
python-matplotlib
python-hypothesis
python-pandas
python-pyarrow
python-pydantic
python-fsspec
python-sqlalchemy
python-zstandard
python-cloudpickle
python-aiosqlite
python-boto3
python-orjson

