Add polars-bio as a benchmarkable interval tool.
What it is: a Python genomics library built on polars / Apache Arrow / DataFusion, offering genomic range operations (overlap/intersect) via a DataFrame API. Installed with pip install polars-bio; overlap is exposed as polars_bio.overlap(df1, df2, ...).
Integration points (follow the existing intervaltree / awk pattern — a small CLI wrapper invoked through tool_call):
Add polars-bio as a benchmarkable interval tool.
What it is: a Python genomics library built on polars / Apache Arrow / DataFusion, offering genomic range operations (overlap/intersect) via a DataFrame API. Installed with
pip install polars-bio; overlap is exposed aspolars_bio.overlap(df1, df2, ...).Integration points (follow the existing
intervaltree/awkpattern — a small CLI wrapper invoked throughtool_call):segmeter/tools/intersect_polars_bio.pythat takes-t target -q query -o outputand writes BED-format overlaps, mirroringsegmeter/tools/intersect_intervaltree.py.polars_biobranch inquery_callthat runs the wrapper viatool_call.segmeter/calls.py(near theintervaltreebranch, ~line 270)"polars_bio"to the--toolargparse choices.segmeter/main.py:35-37polars_bio_sortedtoidx_based_toolsand anindex_callbranch.segmeter/benchmark.py:24-27,segmeter/calls.py:41-wa-style format the precision check expects (first 3 cols = interval), so TP/FP/FN scoring stays comparable.