turbodbc

What's Changed

• #354- Add support for pyarrow 8.0 by @alippai in https://github.com/blue-yonder/turbodbc/pull/356
• #354 - Add support for pyarrow 8.0 by @ldacey in https://github.com/blue-yonder/turbodbc/pull/355
• Add custom extension builder to setup.py by @Nicoretti in https://github.com/blue-yonder/turbodbc/pull/359

New Contributors

• @Nicoretti made their first contribution in https://github.com/blue-yonder/turbodbc/pull/359

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.5.3...4.5.4

What's Changed

• Only use oldest-supported-numpy in pyproject.toml by @xhochy in https://github.com/blue-yonder/turbodbc/pull/344

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.5.1...4.5.2

What's Changed

• Add conda-based pre-commit hooks by @xhochy in https://github.com/blue-yonder/turbodbc/pull/341
• Specify setup_requires by @xhochy in https://github.com/blue-yonder/turbodbc/pull/343

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.4.0...4.5.0

What's Changed

• Update 3rd parties by @alippai in https://github.com/blue-yonder/turbodbc/pull/340

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.3.1...4.4.0

What's Changed

• Release the GIL in python_parameter_set::flush by @smithcre in https://github.com/blue-yonder/turbodbc/pull/333
• Update to Arrow 7.0.0 by @alippai in https://github.com/blue-yonder/turbodbc/pull/338
• Add support for pyarrow 7.0.0 by @ldacey in https://github.com/blue-yonder/turbodbc/pull/337

New Contributors

• @smithcre made their first contribution in https://github.com/blue-yonder/turbodbc/pull/333

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.3.0...4.3.1

What's Changed

• Initialize PyDateTimeAPI in module initialization. by @adament in https://github.com/blue-yonder/turbodbc/pull/316
• Arrow 6.0.0 update by @alippai in https://github.com/blue-yonder/turbodbc/pull/326
• Add support for pyarrow 6 by @ldacey in https://github.com/blue-yonder/turbodbc/pull/325
• Add python 3.10 support by @alippai in https://github.com/blue-yonder/turbodbc/pull/327
• Update pybind11 to version 2.8.1 by @alippai in https://github.com/blue-yonder/turbodbc/pull/328
• fix rst syntax by @pacman82 in https://github.com/blue-yonder/turbodbc/pull/330

New Contributors

• @adament made their first contribution in https://github.com/blue-yonder/turbodbc/pull/316

Full Changelog: https://github.com/blue-yonder/turbodbc/compare/4.2.1...4.3.0

Support pyarrow 5

• Update package requirements so that pyarrow>0.17.1,<4.1 can be used.
• Set minimal Python version to 3.7 following NEP 29.

Update package requirements so pyarrow>0.17.1,<3.1 can be used.

Minimal Python version is now 3.6

• Support Arrow 0.16.x and 0.17.x, require at least 0.15.x
• Minimal NumPy version was bumped to 1.16

• Don't override but amend CMAKE_CXX_FLAGS
• Support Arrow 0.15.X

Highlights:

• Arrow 0.14.X support

Full changeling available: https://github.com/blue-yonder/turbodbc/blob/master/CHANGELOG.rst

Added support for with blocks for Cursor and Connection objects. This makes turbodbc conform with PEP 343 (thanks @AtomBaf)
Added new keyword argument force_extra_capacity_for_unicode to make_options(). If set to True, memory allocation is modified to operate under the assumption that the database driver reports field lengths in characters, rather than code units (thanks @yaxxie).

Highlights:

• Support for with statements for Cursor and Connection objects

Please see the Changelog for more details.

Highlights:

• Support for Apache Arrow 0.8.x
• fetchallarrow() optionally supports data-dependent integer types to save space when possible

Please see the Changelog for more details.

Highlights:

• Fixed a memory leak in the Cursor.fetchallarrow()

Please see the Changelog for more details.

Highlights:

• Cursor.executemanycolumns() supports Apache Arrow pyarrow.Table, allowing convenient inserts from pandas.DataFrame

Please see the Changelog for more details

Highlights:

• cursor.fetchallarrow() now supports representing string fields as Apache Arrow's dictionary arrays. This is helpful for string fields containing only a limited number of distinct entries, e.g., cities, countries, colors, etc.

Please see the changelog for more details