Great-expectations

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0.6.0

* Add support for SparkDFDataset and caching (HUGE work from cselig)
* Migrate distributional expectations to new testing framework
* Add support for two new expectations: expect_column_distinct_values_to_contain_set
and expect_column_distinct_values_to_equal_set (thanks RoyalTS)
* FUTURE BREAKING CHANGE: The new cache mechanism for Datasets, \
when enabled, causes GE to assume that dataset does not change between evaluation of individual expectations. \
We anticipate this will become the future default behavior.
* BREAKING CHANGE: Drop official support for python 2 and pandas < 0.22

0.5.1

* Fix issue where no result_format available for expect_column_values_to_be_null caused error
* Use vectorized computation in pandas (443, 445; thanks RoyalTS)

0.5.0

* Restructured class hierarchy to have a more generic DataAsset parent that maintains expectation logic separate from the tabular organization of Dataset expectations
* Added new FileDataAsset and associated expectations (416 thanks anhollis)
* Added support for date/datetime type columns in some SQLAlchemy expectations (413)
* Added support for a multicolumn expectation, expect multicolumn values to be unique (408)
* Optimization: You can now disable `partial_unexpected_counts` by setting the `partial_unexpected_count` value to 0 in the result_format argument, and we do not compute it when it would not be returned. (431, thanks eugmandel)
* Fix: Correct error in unexpected_percent computations for sqlalchemy when unexpected values exceed limit (424)
* Fix: Pass meta object to expectation result (415, thanks jseeman)
* Add support for multicolumn expectations, with `expect_multicolumn_values_to_be_unique` as an example (406)
* Add dataset class to from_pandas to simplify using custom datasets (404, thanks jtilly)
* Add schema support for sqlalchemy data context (410, thanks rahulj51)
* Minor documentation, warning, and testing improvements (thanks zdog).

0.4.5

* Add a new autoinspect API and remove default expectations.
* Improve details for expect_table_columns_to_match_ordered_list (379, thanks rlshuhart)
* Linting fixes (thanks elsander)
* Add support for dataset_class in from_pandas (thanks jtilly)
* Improve redshift compatibility by correcting faulty isnull operator (thanks avanderm)
* Adjust partitions to use tail_weight to improve JSON compatibility and
support special cases of KL Divergence (thanks anhollis)
* Enable custom_sql datasets for databases with multiple schemas, by
adding a fallback for column reflection (387, thanks elsander)
* Remove `IF NOT EXISTS` check for custom sql temporary tables, for
Redshift compatibility (372, thanks elsander)
* Allow users to pass args/kwargs for engine creation in
SqlAlchemyDataContext (369, thanks elsander)
* Add support for custom schema in SqlAlchemyDataset (370, thanks elsander)
* Use getfullargspec to avoid deprecation warnings.
* Add expect_column_values_to_be_unique to SqlAlchemyDataset
* Fix map expectations for categorical columns (thanks eugmandel)
* Improve internal testing suite (thanks anhollis and ccnobbli)
* Consistently use value_set instead of mixing value_set and values_set (thanks njsmith8)

0.4.4

* Improve CLI help and set CLI return value to the number of unmet expectations
* Add error handling for empty columns to SqlAlchemyDataset, and associated tests
* Fix broken support for older pandas versions (346)
* Fix pandas deepcopy issue (342)

0.4.3

* Improve type lists in expect_column_type_to_be[_in_list] (thanks smontanaro and ccnobbli)
* Update cli to use entry_points for conda compatibility, and add version option to cli
* Remove extraneous development dependency to airflow
* Address SQlAlchemy warnings in median computation
* Improve glossary in documentation
* Add 'statistics' section to validation report with overall validation results (thanks sotte)
* Add support for parameterized expectations
* Improve support for custom expectations with better error messages (thanks syk0saje)
* Implement expect_column_value_lenghts_to_[be_between|equal] for SQAlchemy (thanks ccnobbli)
* Fix PandasDataset subclasses to inherit child class

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