chore(main): release 0.6.0

[github-actions]

0.6.0 (2026-03-18)

Features

• PySpark is now an optional dependency (27e864b)

  Users running PySpark in managed environments (Databricks, EMR, etc.) typically have PySpark
  pre-installed and cannot or do not want the library to reinstall it. PySpark is now optional
  and must be explicitly requested:

  pip install dataframe-expectations           # pandas only
  pip install dataframe-expectations[pyspark]  # includes pyspark
  

  pandas, pydantic, and tabulate remain hard dependencies. Importing dataframe_expectations
  no longer touches PySpark at all when it isn't installed — all PySpark imports are deferred
  behind @lru_cache helpers that return a proxy raising a clear ImportError only when a
  PySpark code path is actually executed.

• PySpark tests isolated by marker (ef847ed)

  All PySpark test cases are decorated with @pytest.mark.pyspark and separated into their own
  parametrize blocks. --strict-markers is now enforced so unregistered markers cause an
  immediate failure. Tests can be run without PySpark present:

  pytest -m "not pyspark"   # no PySpark required
  pytest -m pyspark          # requires PySpark
  

• CI updated to cover three install scenarios

  Job	How PySpark is present	Tests run
  tests-without-pyspark	Not installed	-m "not pyspark"
  tests-with-pyspark-extra	pip install .[pyspark]	All
  tests-with-external-pyspark	Pre-installed externally	All

  The tests-with-external-pyspark job specifically validates that the library works correctly
  when PySpark is already present in the environment and was not installed by this package.

[ryanseq-gyg]

LGTM