Package: pyranges / 0.0.111+ds-9

Metadata

Package Version Patches format
pyranges 0.0.111+ds-9 3.0 (quilt)

Patch series

view the series file
Patch File delta Description
fix_dtype.patch | (download)

pyranges/methods/concat.py | 3 2 + 1 - 0 !
1 file changed, 2 insertions(+), 1 deletion(-)

 explicitly case variable to category dtype
reorder.patch | (download)

setup.py | 2 1 + 1 - 0 !
1 file changed, 1 insertion(+), 1 deletion(-)

 add patch to fix ftbfs
numpy_1.24.patch | (download)

pyranges/pyranges.py | 6 3 + 3 - 0 !
tests/hypothesis_helper.py | 2 1 + 1 - 0 !
tests/test_binary.py | 2 1 + 1 - 0 !
3 files changed, 5 insertions(+), 5 deletions(-)

 adapt to numpy 1.24
Bug-Debian: https://bugs.debian.org/1028852
healthcheck all.patch | (download)

tests/test_unary.py | 2 1 + 1 - 0 !
1 file changed, 1 insertion(+), 1 deletion(-)

 fix deprecated healthcheck.all() decorator parameter.
 The HealthCheck.all() method has been deprecated in favor of specifying in a
 list which checks to ignore in a subsequent test function.  The error message
 suggests use of HealthCheck.return_value.  Other options are documented on
 Python hypothesis module documentation[1].  It is worth noting the attribute
 return_value itself is marked as deprecated, so we might as well just buy us
 some time until a possibly more appropriate fix.
 .
 [1]: https://hypothesis.readthedocs.io/en/latest/settings.html#health-checks

no_install_depends_cython.patch | (download)

setup.py | 2 1 + 1 - 0 !
1 file changed, 1 insertion(+), 1 deletion(-)

 no runtime dependency from cython
Bug-Debian: https://bugs.debian.org/1058012
pandas2.0.patch | (download)

pyranges/pyranges.py | 2 1 + 1 - 0 !
tests/test_binary.py | 4 2 + 2 - 0 !
tests/test_unary.py | 6 2 + 4 - 0 !
3 files changed, 5 insertions(+), 7 deletions(-)

 fix for pandas 2.0
Bug-Debian: https://bugs.debian.org/1044064
fix test_unary.patch | (download)

tests/test_unary.py | 2 1 + 1 - 0 !
1 file changed, 1 insertion(+), 1 deletion(-)

 fix expected cluster result.
 Somehow, the statement in its original form ceased to reflect the change of
 dtype to numpy's int32 for the expected result, causing a test failure because
 the reference data now has wrongly int64 numpy dtype.  Slightly changing the
 way the assignation of the smaller dtype is done fixes the problem.