As per 350, Pandas integration will be deprecated. Starting in version 0.3.0, it won't be possible to use Awkward arrays as Pandas Series or DataFrame columns. We're also giving up on attempts to keep Matplotlib from iterating over non-numeric data. (These are part of a theme of removing sneaky tricks from the code, such as `awkward1._util.called_by_module`, for robustness.)
Updated to backward-incompatible changes in Arrow 1.0.0. Now Arrow 1.0.0 is the minimum version that works with Awkward.
Updated to changes in JupyterBooks to fix documentation.
ianna added a `numbers_to_type` function, which converts all numbers to a given type while maintaining an array's structure.
reikdas generated over three thousand unit tests for the kernels, which previously had only been tested as part of integration tests. Once the blacklist in the test generation framework is reduced to zero, line coverage of kernels will be 100%. Once the samples are carefully chosen in kernel-specification/samples.json, all the important cases will be tested as well. This testing framework will be extended to CUDA kernels as well.
nsmith- added class and class method decorators to simplify the process of adding high-level behaviors.
Internally, all of the "offset" parameters have been removed from kernel argument lists. Instead, correctly offset pointers are passed to these functions, so they can assume that they start from (relative) array index zero. Several previously fixed bugs have been traced to this and in the conversion, I found a few more suspicious spots—now we don't have to worry about it anymore.
Still built on pybind 2.4.3, though we might want to update that, especially if pybind supports the NumPy datetime dtypes.