HNX 2.0 now accepts metadata as core attributes of the edges and nodes of a
hypergraph. While the library continues to accept lists, dictionaries and
dataframes as basic inputs for hypergraph constructions, both cell
properties and edge and node properties can now be easily added for
retrieval as object attributes.

The core library has been rebuilt to take advantage of the flexibility and speed of Pandas Dataframes.
Dataframes offer the ability to store and easily access hypergraph metadata. Metadata can be used for filtering objects, and characterize their
distributions by their attributes.

Version 2.0 is not backwards compatible. Objects constructed using version
1.x can be imported from their incidence dictionaries.

What's New

The Hypergraph constructor now accepts nested dictionaries with incidence cell properties, pandas.DataFrames, and 2-column Numpy arrays.
Additional constructors accept incidence matrices and incidence dataframes.
Hypergraph constructors accept cell, edge, and node metadata.
Metadata available as attributes on the cells, edges, and nodes.
User-defined cell weights and default weights available to incidence matrix.
Meta data persists with restrictions and removals.
Meta data persists onto s-linegraphs as node attributes of Networkx graphs.
New hnxwidget available using pip install hnxwidget.

What's Changed

The static and dynamic distinctions no longer exist. All hypergraphs use the same underlying data structure, supported by Pandas dataFrames. All hypergraphs maintain a state_dict to avoid repeating computations.
Methods for adding nodes and hyperedges are currently not supported.
The nwhy optimizations are no longer supported.
Entity and EntitySet classes are being moved to the background. The Hypergraph constructor does not accept either.