Great-expectations

* BREAKING CHANGE: move all reader options from the top-level batch_kwargs object to a sub-dictionary called
"reader_options" for SparkDFDatasource and PandasDatasource. This means it is no longer possible to specify
supplemental reader-specific options at the top-level of `get_batch`, `yield_batch_kwargs` or `build_batch_kwargs`
calls, and instead, you must explicitly specify that they are reader_options, e.g. by a call such as:
`context.yield_batch_kwargs(data_asset_name, reader_options={'encoding': 'utf-8'})`.
* BREAKING CHANGE: move all query_params from the top-level batch_kwargs object to a sub-dictionary called
"query_params" for SqlAlchemyDatasource. This means it is no longer possible to specify supplemental query_params at
the top-level of `get_batch`, `yield_batch_kwargs` or `build_batch_kwargs`
calls, and instead, you must explicitly specify that they are query_params, e.g. by a call such as:
`context.yield_batch_kwargs(data_asset_name, query_params={'schema': 'foo'})`.
* Add support for filtering validation result suites and validation result pages to show only failed expectations in
generated documentation
* Add support for limit parameter to batch_kwargs for all datasources: Pandas, SqlAlchemy, and SparkDF; add support
to generators to support building batch_kwargs with limits specified.
* Include raw_query and query_params in query_generator batch_kwargs
* Rename generator keyword arguments from data_asset_name to generator_asset to avoid ambiguity with normalized names
* Consistently migrate timestamp from batch_kwargs to batch_id
* Include batch_id in validation results
* Fix issue where batch_id was not included in some generated datasets
* Fix rendering issue with expect_table_columns_to_match_ordered_list expectation
* Add support for GCP, including BigQuery and GCS
* Add support to S3 generator for retrieving directories by specifying the `directory_assets` configuration
* Fix warning regarding implicit class_name during init flow
* Expose build_generator API publicly on datasources
* Allow configuration of known extensions and return more informative message when SubdirReaderGenerator cannot find
relevant files.
* Add support for allow_relative_error on internal dataset quantile functions, and add support for
build_continuous_partition_objec in Redshift
* Fix truncated scroll bars in value_counts graphs

* Improved the tutorials that walk new users through the process of creating expectations and validating data
* Changed the flow of the init command - now it creates the scaffolding of the project and adds a datasource. After that users can choose their path.
* Added a component with links to useful tutorials to the index page of the Data Docs website
* Improved the UX of adding a SQL datasource in the CLI - now the CLI asks for specific credentials for Postgres, MySQL, Redshift and Snowflake, allows continuing debugging in the config file and has better error messages
* Added batch_kwargs information to DataDocs validation results
* Fixed an issue affecting file stores on Windows

* Fix a bug in data-docs' rendering of mostly parameter
* Correct wording for expect_column_proportion_of_unique_values_to_be_between
* Set charset and meta tags to avoid unicode decode error in some browser/backend configurations
* Improve formatting of empirical histograms in validation result data docs
* Add support for using environment variables in `config_variables_file_path`
* Documentation improvements and corrections

* Add easier support for customizing data-docs css
* Use higher precision for rendering 'mostly' parameter in data-docs; add more consistent locale-based
formatting in data-docs
* Fix an issue causing visual overlap of large numbers of validation results in build-docs index
* Documentation fixes (thanks DanielOliver!) and improvements
* Minor CLI wording fixes
* Improved handling of MySql temporary tables
* Improved detection of older config versions

* Fix an issue where version was reported as '0+unknown'

Version 0.8.0 is a significant update to Great Expectations, with many improvements focused on configurability and usability. See the migrating versions guide for more details on specific changes, which include several breaking changes to configs and APIs.

Highlights include:

1. Validation Operators and Actions. Validation operators make it easy to integrate GE into a variety of pipeline runners. They offer one-line integration that emphasizes configurability. See the validation operators and actions feature guide for more information.

- The DataContext `get_batch` method no longer treats `expectation_suite_name` or `batch_kwargs` as optional; they must be explicitly specified.
- The top-level GE validate method allows more options for specifying the specific data_asset class to use.

2. First-class support for plugins in a DataContext, with several features that make it easier to configure and
maintain DataContexts across common deployment patterns.

- **Environments**: A DataContext can now manage `environment_and_secrets` more easily thanks to more dynamic and flexible variable substitution.
- **Stores**: A new internal abstraction for DataContexts, `stores_reference`, make extending GE easier by consolidating logic for reading and writing resources from a database, local, or cloud storage.
- **Types**: Utilities configured in a DataContext are now referenced using `class_name` and `module_name` throughout the DataContext configuration, making it easier to extend or supplement pre-built resources. For now, the "type" parameter is still supported but expect it to be removed in a future release.

3. Partitioners: Batch Kwargs are clarified and enhanced to help easily reference well-known chunks of data using a partition_id. Batch ID and Batch Fingerprint help round out support for enhanced metadata around data assets that GE validates. See `batch_identifiers` for more information. The `GlobReaderGenerator`, `QueryGenerator`, `S3Generator`, `SubdirReaderGenerator`, and `TableGenerator` all support partition_id for easily accessing data assets.

4. Other Improvements:

- We're beginning a long process of some under-the-covers refactors designed to make GE more maintainable as we begin adding additional features.
- Restructured documentation: our docs have a new structure and have been reorganized to provide space for more easily adding and accessing reference material. Stay tuned for additional detail.
- The command build-documentation has been renamed build-docs and now by default opens the Data Docs in the users' browser.