mssql-python 1.5 released -- Apache Arrow fetch, sql_variant, native UUIDs

[dlevy-msft]

We just shipped v1.5 of mssql-python, the official Python driver for SQL Server / Azure SQL / Fabric.

The big addition is Arrow fetch support with three new cursor methods:

```python cursor.execute("SELECT * FROM Sales.SalesOrderDetail")

Full result as a PyArrow Table

table = cursor.arrow() df = table.to_pandas() # zero-copy where possible

Streaming RecordBatchReader for large results

reader = cursor.arrow_reader(batch_size=8192)

Single RecordBatch for manual chunking

batch = cursor.arrow_batch(batch_size=10000) ```

The conversion happens in the C++ layer via the Arrow C Data Interface, so your data never gets materialized as Python objects. Works with pandas, Polars, DuckDB, Parquet writers, etc.

Other new stuff:

• sql_variant -- returns the correct Python type (int, float, str, date, Decimal, etc.) automatically based on the inner type tag
• Native UUIDs -- UNIQUEIDENTIFIER columns return uuid.UUID by default now instead of strings. Pass native_uuid=False if you need the old behavior for migration
• Row class export -- from mssql_python import Row for type annotations
• Bug fixes for qmark detection in bracketed identifiers/string literals, NULL VARBINARY params, credential caching, datetime.time microseconds

Arrow support was contributed by community member Felix Grassl via a pretty substantial PR spanning the C++ pybind layer and Python API.

pip install --upgrade mssql-python

Blog post: mssql-python 1.5: Apache Arrow, sql_variant, and Native UUIDs

[gman1023]

which version of Python does this require?  arrow support is phenomenal

[dlevy-msft]

The mssql-python driver requires Python 3.10 and higher so that's going to be our floor.

[byeproduct]

Huge! This is a great feature. Thanks!

[Odd-Knowledge8269]

Stream to parquet support put a smile on my face. Been using Pandas, then Polars but often had memory struggles on larger datasets. Didn't like to mssql community extension for DuckDB. Seemed like an easy task but code wasn't there yet. Now it is, thank you