import dascore as dc
spool = dc.get_example_spool("random_das")
df = spool.get_contents()
assert not [x for x in df.columns if str(x).startswith("_")]
assert df["data_size"].iloc[0] == spool[0].sizeget_contents
get_contents(
self ,
)-> ‘pd.DataFrame’
Get a dataframe of the spool contents.
Note
Each call returns a caller-owned dataframe; mutating it never changes the spool. Use frame.copy(deep=True) when an eager block copy is needed.
The columns the index keeps for itself are not part of the frame: everything returned is public, so no column name starts with an underscore. A few are private only because the chunk planner polices public columns; those are presented under their public names rather than dropped (dascore.utils.pd.PRESENTERS lists them), so the frame states each patch’s dtype and data_size – the samples its data array holds. A row which does not know its size states none: a merged or subdivided chunk output, or a patch a selection trims.