ESRI is more complete than the open source implementations generally, but is not usable for large-scale geospatial analytics. I have not used Shapely but it appears to be based on the same geometry routines as PostGIS. If you look at the underlying implementations of most open source for geospatial algorithms, of which there are only a few, it is usually missing code paths for complex numerical analysis edge cases regardless of what the documentation says. (Sometimes there are even code comments to that effect.) At sufficient scale, you will find all the edge cases in real-world applications quickly even though you may not notice if you have nothing to compare it to. When we developed the first “analytics grade” ellipsoid geospatial geometry engine several years ago (an enormous technical undertaking involving a team of mathematicians), it created distress at some companies because the visible discrepancies relative to other geospatial analysis systems they were using were much larger than they imagined.

A challenge of open source software is that it largely only gets created when the technical complexity and expertise barrier is low enough. Above that threshold, the small number of people capable of contributing combined with the large number of man-hours required for a correct implementation is beyond the resources typically available to such a project. Geospatial is a good example of this pattern (database engines are another).