[GUIDE] Interoperability with Polars, DuckDB, and PyArrow (Zero-Copy Analytics)
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 75/100
- Issue type
- Documentation
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- python
- Domain
- documentation
Research direction
The guide file is to be created at doc/guides/interop_arrow_duckdb_polars.md. Start by examining the existing doc/guides/index.rst to understand the linking pattern. Review the blosc2.CTable API documentation for to_arrow() and from_arrow() methods. Write runnable examples for PyArrow round-trips, DuckDB queries, and Polars integration, ensuring they work with sample data. Finally, update the index file to link the new guide.
Written by the indexing model from the issue text.
Description
Blosc2 provides zero-copy Apache Arrow interoperability via CTable.to_arrow(), from_arrow(), and the PyCapsule protocol. Some data teams may want to leverage Blosc2 for high-ratio compressed columnar storage while running analytical queries using modern query engines like DuckDB and Polars.
Suggested Work
Create doc/guides/interop_arrow_duckdb_polars.md and link it from doc/guides/index.rst.
Provide runnable code examples showing:
- PyArrow Round-trip: Converting a
blosc2.CTableto apyarrow.Table/RecordBatchand back with zero copying where supported. - Direct SQL queries with DuckDB: Querying Blosc2 tables using DuckDB's Arrow scanner:
import duckdb import blosc2 table = blosc2.open("dataset.b2z") res = duckdb.arrow(table.to_arrow()).filter("price > 100").aggregate("avg(score)").df() - Polars Integration: Ingesting a Blosc2 table into Polars (
pl.from_arrow(table.to_arrow())) and converting Polars DataFrames into Blosc2 CTables. - Performance & Memory Comparisons: Illustrating memory usage during queries on compressed Blosc2 tables vs. raw in-memory DataFrames.
- Dominant language
- Python
- Stars
- 211
- Forks
- 63
- Avg merge
- 2d 1h
- Merged PRs (30d)
- 9
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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