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/InvestmentSystems/arraykit

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

Dependencies

ArrayKit requires the following:

• Python >= 3.7
• NumPy >= 1.18.5

What is New in ArrayKit

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