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      <title>Python PyArrow 實戰：Parquet、Schema 與跨工具資料交換</title>
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dedup note: Free-pick topic `python-pyarrow` is distinct from ../python-duckdb/, ../python-polars/, ../python-csv/, and ../streamlit-duckdb-dashboard/. Those posts cover SQL analytics over local files, DataFrame expression workflows, standard-library CSV streaming, and UI dashboards. This article focuses on PyArrow itself: Arrow Array/Table memory layout, explicit schema contracts, Parquet metadata, partitioned datasets, row group filtering, and clean exchange between pandas, Polars, DuckDB, and batch pipelines.
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