arraykit

The ArrayKit library provides utilities for creating and transforming NumPy arrays, implementing performance-critical StaticFrame operations as Python C extensions.

Code: https://github.com/static-frame/arraykit

Packages: https://pypi.org/project/arraykit

Dependencies

ArrayKit requires the following:

Python>=3.10
numpy>=1.24.3

What is New in ArrayKit

1.12.0

Added map_object() and prepare_iter_for_array().

1.11.0

Added group_reduce().

1.10.0

Added TriMap.register_pairs().

1.9.0

Added FrozenAutoMap.get_all_fill() and TriMap.register_many_from_one().

1.8.0

Added fill_directional().

1.7.0

Added group_ordering().

1.6.0

Added factorize().

1.5.0

Added transition_slices_from_group().

1.4.0

Added write_array_to_file().

1.3.1

Improved slice_to_unit() integer extraction.

1.3.0

Added slice_to_unit().

1.2.1

Minor improvement in efficiency of string-to-float conversion in delimited_to_arrays().

1.2.0

Now building wheels for Python 3.14 and 3.14t.

1.1.0

Now building free-threaded compatible wheels for Python 3.13.

Added is_objectable() and is_objectable_dt64().

Added astype_array().

1.0.9

Updated types in pyi file.

1.0.8

NumPy datetime64 scalar lookups in AutoMap and FrozenAutoMap explicitly require matching units.

1.0.7

Updated build configuration.

1.0.6

Updated build configuration.

1.0.5

Updated build configuration.

1.0.4

Updated build configuration.

1.0.3

Updated build configuration.

1.0.2

Updated build configuration.

1.0.1

Updated build configuration.

1.0.0

Integrated AutoMap and FrozenAutoMap from arraymap.

Removed global integer cache from AutoMap and FrozenAutoMap for thread safety.

0.10.0

Now building wheels for Python 3.13.

0.9.0

Added TriMap.map_merge().

0.8.3

Corrected incorrect component of _TLabel in __init__.pyi.

0.8.2

Updated build configuration.

0.8.1

Updated build configuration.

0.8.0

Now building with NumPy 2.0.

0.7.2

Improved array_to_tuple_array() and array_to_tuple_iter() to preserve tuple in 1D arrays.

0.7.1

Extended array_to_tuple_array() and array_to_tuple_iter() to support 1D arrays.

0.7.0

Added array_to_tuple_array().

Added array_to_tuple_iter().

0.6.3

Optimized memory allocation strategy for nonzero_1d().

0.6.2

Extended nonzero_1d() to support non-contiguous arrays.

Optimizations to TriMap when mapping to object and flexible dtypes.

0.6.1

Enhancements and optimizations to TriMap.

Added nonzero_1d().

0.6.0

Added TriMap utility class for join optimization.

0.5.1

Restored functional wheels for Mac OS x86_64.

0.5.0

Now building wheels for 3.12.

Now building functional wheels for Mac OS arm64 / Apple Silicon.

0.4.11

Updated types in pyi file.

0.4.10

Updated types in pyi file.

Minimum supported Python set to 3.8.

Minimum supported NumPy set to 1.19.5.

0.4.9

Improved performance of first_true_1d() and first_true_2d().

0.4.8

Restored behavior of Blockndex.rows to return -1 when BlockIndex has zero rows.

0.4.7

Added BlockIndex.iter_block().

Corrected issue in BlockIndex.shape when the BlockIndex has zero rows.

0.4.6

Corrected handling of empty selections in BlockIndex.iter_contiguous().

0.4.5

Corrected handling of ascending in BlockIndex.iter_contiguous() with Boolean arrays.

0.4.4

Corrected deallocation routines in BlockIndex.iter_contiguous().

0.4.3

Added BlockIndex.iter_contiguous() with options for ascending and reduce sequences.

0.4.2

Added slice_to_ascending_slice().

Updated BlockIndex.shape to internally cache the shape tuple.

Corrected BlockIndex.iter_select() handling of negative integers in sequences.

0.4.1

Updated BlockIndex.register() to handle 0-column 2D arrays and return False.

Added BlockIndex.rows, BlockIndex.columns properties.

Updated unset BlockIndex.dtype to return a float dtype.

0.4.0

Added BlockIndex, a tool to be used by TypeBlocks for mapping realized column positions to arrays.

Corrected potential issue in AK_CPL_resize_buffer that could segfault for very large offsets.

0.3.4

Simplified implementation of NaTType identification in isna_element().

0.3.3

Corrected potential memory leak in isna_element().

0.3.2

Optimization to delimited_to_arrays() character reading per line.

0.3.1

Improvements to delimited_to_arrays(), including proper loading of float16 types.

Extended deepcopy_array() to permit memo as None.

Corrected all compiler warnings on Windows.

0.3.0

Added first_true_1d(), first_true_2d(). Added tools for performance graphing.

0.2.9

Corrected segmentation fault resulting from attempting to parse invalid datetime64 strings in AK_CPL_to_array_via_cast.

0.2.8

Added include_none argument to isna_element(); implemented identification of Pandas pd.Timestamp NaT.

0.2.7

Updated most-recent NumPy references to 1.23.5.

0.2.6

Maintenance release.

0.2.5

Optimization to numerical array creation in delimited_to_arrays().

0.2.4

Set NumPy minimum version at 1.18.5.

0.2.3

Extended arguments to and functionality in split_after_count() to support the complete CSV dialect interface.

Now building wheels for 3.11.

0.2.2

Refinements to ensure typed-parsed ints are always int64 in delimited_to_arrays().

0.2.1

Implemented count_iteration, split_after_count.

0.2.0

Implemented delimited_to_arrays, iterable_str_to_array_1d.

0.1.13

Now building Python 3.10 wheels.

0.1.12

Added get_new_indexers_and_screen.

0.1.10

Updated minimum NumPy to 1.18.5

0.1.9

Improvements to performance of array_deepcopy.

Added dtype_from_element.

0.1.8

Revised cross compile releases.

0.1.7

Added dtype_from_element().

0.1.6

Explicit imports in __init__.py for better static analysis.

0.1.5

Added isna_element().

0.1.3

Redesigned package structure for inclusion of py.typed and __init__.pyi.

array_deepcopy now accepts kwargs and makes the memo dict optional.

0.1.2

Maintenance release of the following interfaces:

immutable_filter mloc shape_filter column_2d_filter column_1d_filter row_1d_filter array_deepcopy resolve_dtype resolve_dtype_iter

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Release history Release notifications | RSS feed

This release

1.12.0

Aug 6, 2026

1.11.0

Aug 5, 2026

1.10.0

Aug 1, 2026

1.9.0

Jul 31, 2026

1.8.0

Jul 31, 2026

1.7.0

Jul 5, 2026

1.6.0

Jul 4, 2026

1.5.0

Jul 1, 2026

1.4.0

Jun 30, 2026

1.3.1

Jun 29, 2026

1.3.0

Jun 29, 2026

1.2.1

Feb 4, 2026

1.2.0

Oct 9, 2025

1.1.0

Jun 25, 2025

1.0.9

May 30, 2025

1.0.8

May 15, 2025

1.0.7

May 15, 2025

1.0.0 yanked

May 14, 2025

Reason this release was yanked:

Pre-built wheels not available

0.10.0

Nov 21, 2024

0.9.0

Aug 22, 2024

0.8.3

Aug 21, 2024

0.8.2

Jul 18, 2024

0.8.1

Jul 17, 2024

0.8.0

Jul 12, 2024

0.7.2

Jun 23, 2024

0.7.1

Jun 22, 2024

0.7.0

Jun 21, 2024

0.6.3

Jun 8, 2024

0.6.2

Jun 6, 2024

0.6.1

Jun 4, 2024

0.6.0

May 25, 2024

0.5.1

Dec 19, 2023

0.5.0

Dec 17, 2023

0.4.11

Sep 22, 2023

0.4.10

Sep 9, 2023

0.4.9

Jun 24, 2023

0.4.8

May 25, 2023

0.4.7

May 24, 2023

0.4.6

May 24, 2023

0.4.5

May 23, 2023

0.4.4

May 23, 2023

0.4.3

May 21, 2023

0.4.2

May 19, 2023

0.4.1

May 18, 2023

0.4.0

May 16, 2023

0.3.4

May 2, 2023

0.3.3

May 2, 2023

0.3.2

Apr 24, 2023

0.3.1

Mar 30, 2023

0.3.0

Mar 3, 2023

0.2.9

Feb 10, 2023

0.2.8

Feb 8, 2023

0.2.7

Jan 24, 2023

0.2.6

Dec 15, 2022

0.2.4

Nov 28, 2022

0.2.3

Nov 16, 2022

0.2.2

Oct 21, 2022

0.2.1

Oct 20, 2022

0.2.0

Oct 18, 2022

0.1.13

Aug 14, 2022

0.1.12

Jul 29, 2022

0.1.11

May 14, 2022

0.1.10

May 13, 2022

0.1.9

Sep 9, 2021

0.1.8

Jun 3, 2021

0.1.6

May 31, 2021

0.1.5

May 28, 2021

0.1.4

May 13, 2021

0.1.2

Apr 17, 2021

0.1.0

Feb 18, 2021

arraykit 1.12.0

arraykit

Dependencies

What is New in ArrayKit

1.12.0

1.11.0

1.10.0

1.9.0

1.8.0

1.7.0

1.6.0

1.5.0

1.4.0

1.3.1

1.3.0

1.2.1

1.2.0

1.1.0

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

1.0.1

1.0.0

0.10.0

0.9.0

0.8.3

0.8.2

0.8.1

0.8.0

0.7.2

0.7.1

0.7.0

0.6.3

0.6.2

0.6.1

0.6.0

0.5.1

0.5.0

0.4.11

0.4.10

0.4.9

0.4.8

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.9

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.13

0.1.12

0.1.10

0.1.9

0.1.8

0.1.7

0.1.6

0.1.5

0.1.3

0.1.2