0.0.5

Successfully reading TTree data:

• arrays and jagged arrays
• simpler Interpretation machinery (basket_array and finalized_array only), entry slicing still works
• aliases and computable expressions
• parallel multipart download → decompression pipeline
• caching
• backend libraries with library-dependent array grouping (dict of NumPy arrays, Awkward record array, Pandas DataFrame, etc.)

Not done:

• all the Interpretation classes, particularly objects and strings
• objects as record arrays
• iteration (in a TTree or across files)
• lazy arrays in Awkward
• branch → multiple columns in Pandas (e.g. fixed-width arrays and leaf-lists)
• extensive testing

0.0.4

Successfully reading in histograms (dynamically generated classes) and TTrees (custom/streamlined reading). Also defined behaviors as a counterpoint to models.

0.0.3

Keep testing deployment. The "Sources" have been added.

0.0.2

First test deployment.