Simpleml

- Standarized formatting with Black
- Split up ORM into a standalone swappable backend
- Persistables maintain weakrefs for lineage
- Persistables are normal python objects now
- Hashing flag to reject non-serializable objects

- Path existence check for pandas serialization

- Changed internal dataset structure from mixins to direct inheritance
- Condensed all pandas dataset types into a single base class
- Adds support for dask datasets
- Placeholders for additional dataset libraries
- Adds hashing support for dask dataframes
- Refactored persistence ("save_patterns") package into standalone extensible framework
- Adds context manager support to registries for temporary overwrite
- Refactor pipelines into library based subclasses

*BREAKING CHANGES*
- Pandas dataset will default param `squeeze_return` to False (classes expecting to return a series will need to be updated)
- Numpy dataset is considered unstable and will be redesigned in a future release
- Onedrive, Hickle, and database save patterns are removed (functionality is still available but a composed pattern is not predefined. these can be trivially added in user code if needed)
- Changed pandas hash output to int from numpy.int64 (due to breaking change in NumpyHasher)
- Changed primitive deterministic hash from pickle to md5
- Extracted data iterators into utility wrappers. Pipelines no longer have flags to return iterators
- Random split defaults are computed at runtime instead of precalculated (affects hash)

- Added support to hasher for initialized objects
- Adds support for arbitrary dataset splits and sections
- Dataset hooks to validate dataframe setting
- Pipelines no longer cache dataset splits and proxy directly to dataset on every call
- Introduces pipeline splits as reproducible projections over dataset splits
- Database utility to recalculate hashes for existing persistables

*BREAKING CHANGES*
- Hash for an uninitialized class changed from repr(cls) to "cls.__module_.cls.__name_"
- Database migrations no longer recalculate hashes. That has to be done manually via a utility

- Dataset external file setter with validation hooks
- Pandas changes to always return dataframe copies (does not extend to underlying python objects! eg lists, objects, etc)
- Pandas Dataset Subclasses for Single and Multi label datasets
- PersistableLoader methods do not require name as a parameter

*BREAKING CHANGES*
- `PandasDataset` is deprecated and will be dropped in a future release. Use `SingleLabelPandasDataset` or `MultiLabelPandasDataset` instead
- Pandas Dataset Classes require dataframe objects of type pd.DataFrame and will validate input (containers of pd.DataFrames are no longer supported)

- Patch to support sqlalchemy >= 1.4 changes