Create MapboxTilesRenderer for outputting TMS tile sets as a mbtiles file (a SQLite database following the MBTiles 1.3 specification).

Compute min/max of span in-place instead of building a list of all values, then computing using dask. Use dimensions of data array for label based indexing, instead of hard-coded x, y labels (which forced input coordinate columns to be named x, y).

Include capability to provide a local_cache_path. If provided, the aggregation for the super tiles will be stored locally as a NetCDF file (instead of keeping all these in memory, which eventually overflows memory at high zoom levels). This allows most of the processing to now be done completely out of core.

Use the netCDF4 library for writing/loading XArray DataArrays from cache, since it properly handles unsigned data types. Optional dependency that will raise an error if not installed when the caching feature is used.

Allow updates to an existing mbtiles file, inserting or replacing rows in the SQLite database and make SQL statements consistent.

calculate_zoom_level_stats moved to a parallel implementation with dask bags, that does not cache the super tiles in memory. If a local_cache_path is provided, the super tiles will be cached to disk as NetCDF files. Super tiles will then be either recomputed during the render_super_tiles function, or loaded from the local cache.

Note: If using the Datashader render_tiles, the scheduler for Dask should be configured to 'threads' (when running on local) to avoid Dask bag computations from copying the input DataFrame to multiple processes, which will increase memory overhead. If outputting tiles to the MBTiles format, the num_workers should be tuned to prevent the SQLite database from locking during transactions. Both of these can be configured using dask.config.set(scheduler='threads', num_workers=4).

Handle setup of output paths.