Pydiverse-pipedag

- fixed python 3.9 compatibility (`traceback.format_exception` syntax changed)
- fixed deferred table copy when task is invalid (introduced with 0.2.2)
- fixed mssql to not reflect full schema while renamings happen
- fixed clearing of metadata tables for lazy tables and raw sql tables
- fixed mssql synonym resolution when reading input table for pandas task
- initial implementation of issue 62: make query canonical before hashing
- retry some DB calls in case they are aborted as deadlock victim

- added option `avoid_drop_create_schema` to table store configuration
- improve performance when working with IBM DB2 dialect (i.e. table locking)
- prevent table copying and schema swapping for 100% cache valid stages

- removed contextvars dependency (not needed for python >= 3.7 and broke conda-forge build)

- `SQLTableStore`: support for Microsoft SQL Server and IBM DB2 (Linux) database connection strings
- Support primary keys and indexes (can be configured with Table object and used in custom RawSql code)
- `RawSql`: support additional return type for `materialize` tasks which allows to emit raw SQL string including multiple create statements (currently, views/functions/procedures are only supported for dialect mssql).
This feature should only be used for getting legacy code running in pipedag before converting it to programatically generated or manual SELECT statements.
- Support pytsql library for executing raw SQL scripts with `dialect=mssql` (i.e. supports PRINT capture)
- Manual Cache Invalidation for source nodes:
`materialize(cache=f)` parameter can take an arbitrary function that gets the same arguments as the task function and returns a hash.
If the hash is different from for the previous run, the task is considered cache invalid.
- New configuration file format pipedag.yaml can be used to configure multiple pipedag instances: see docs/reference/config.rst

Initial release.

- `materialize` annotations
- flow definition with nestable stages
- zookeeper synchronization
- postgres database backend
- Prefect 1.x and 2.x support
- multi-processing/multi-node support for state exchange between `materialize` tasks
- support materialization for: pandas, sqlalchemy, raw sql text, pydiverse.transform