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Currently we have Flags.Any, which is set for all ArrayTypes, in order to make sure that for each ArrayType “at”,
at.flags & ~Flags(0) is truthy, and
not (at.flags & Flags(0)) is true.
This isn’t trivially the case, since each flag represents an attribute, and its absence the inverse attribute, so there is always one group that has no flags set. With the current set of flags (sparse, gpu, dask, disk), this group contains numpy.ndarray)
Alternatives:
don’t use Flags(0) as default for skip, but None instead (unintuitive, one would expect skip=Flags(0) to skip nothing)
use a flag that is the inverse of another, e.g. Flags.Dense (there is no longer one obvious way to do things, e.g. shall we skip sparse or select dense?)
switch the flags to NoDask and NoDisk, so that Flags(0) represents a combination that can never exist (might be elegant if there were were words to express these concepts without negation)
The text was updated successfully, but these errors were encountered:
Continued from #30 (comment) (cc @ilan-gold)
Currently we have
Flags.Any
, which is set for allArrayType
s, in order to make sure that for eachArrayType
“at”,at.flags & ~Flags(0)
is truthy, andnot (at.flags & Flags(0))
is true.This isn’t trivially the case, since each flag represents an attribute, and its absence the inverse attribute, so there is always one group that has no flags set. With the current set of flags (sparse, gpu, dask, disk), this group contains
numpy.ndarray
)Alternatives:
Flags(0)
as default forskip
, butNone
instead (unintuitive, one would expectskip=Flags(0)
to skip nothing)Flags.Dense
(there is no longer one obvious way to do things, e.g. shall we skip sparse or select dense?)NoDask
andNoDisk
, so thatFlags(0)
represents a combination that can never exist (might be elegant if there were were words to express these concepts without negation)The text was updated successfully, but these errors were encountered: