* Move requirements handling to conda to work with the
 data-engineering workflows for deploying python in analytics.

* Update version number to 2.0.0.dev, major version bump due
 to significant changes in how the project is built (but not
 the underlying functionality)

* Updates pyspark from 2.1.0 to 3.1.2.

* Keeps xgboost at 0.90 for now which limits supported python version
 to <=3.7.

* Removed custom mypy stubs, they don't seem worth maintaining

* Updates elasticsearch to 7.10.1, matching elasticsearch deployed
 in production and gaining library provided mypy types.

* Minor updates to match code with mypy analysis of updated libraries
 and types. Mostly things like converting a generator to a list,
 updating ltr elasticsearch client for the new headers parameter passed
 by @query_params, and using queue.Queue generics directly.

* Update SCM information in pom.xml, along with updating scala and
 spark dependencies for spark 3.1.2.

Change-Id: I16c9550091e22eacccec8f2f21...