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read_gtf returns a Polars DataFrame by default, so the pandas-style boolean-mask indexing in the first example raises ValueError. The StringTie example keyed its dict by seqname and filtered on "gene" features, which StringTie GTFs don't contain, so it always produced an empty dict. Use DataFrame.filter, key transcript FPKMs by transcript_id, note result_type="pandas", and show a gene_id lookup. Closes #13 Claude-Session: https://claude.ai/code/session_01DctgBZ5rJiuNzpWXqrNguT
This was referenced Sep 14, 2026
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Superseded by #93 and #95, which document the current pandas-default API and retain working gene and transcript examples. Both refreshed branches pass all 213 tests and their documentation builds.
The Polars-default change below describes the older 2.x API.
Both README examples fail with the current
read_gtf.read_gtfreturns a Polars DataFrame by default (result_type="polars",gtfparse/read_gtf.py:274). The pandas-styledf[df["feature"] == "gene"]raisesValueError: expected 20 values when selecting columns by boolean mask. Changed todf.filter(polars.col(...) == ...), with a note aboutresult_type="pandas".df["seqname"](the chromosome) and kept onlyfeature == "gene"rows. StringTie GTFs have onlytranscriptandexonrows (seetests/data/B16.stringtie.head.gtf), so the result was always{}. Changed to transcript FPKMs keyed bytranscript_id.gene_idlookup, which is what Example of how to find a feature by gene_id or transcript_id #13 asked for.I ran both snippets against
tests/data/ensembl_grch37.head.gtfandtests/data/B16.stringtie.head.gtfwith polars 1.43. Patch version bumped to 2.8.1 perAGENTS.md.Closes #13
https://claude.ai/code/session_01DctgBZ5rJiuNzpWXqrNguT