to support a much wider array of use cases and to use more natural language rather than introducing
GreatExpectations concepts earlier. You can more easily configure different backends and datasources, take advantage of guided walkthroughs to find and profile data, and share project configurations with colleagues.
If you have already completed the `init` flow using a previous version of Great Expectations, you do not need to
rerun the command. However, **there are some small changes to your configuration that will be required**. See
[migrating versions](https://docs.greatexpectations.io/en/latest/reference/migrating_versions.html) for details.
CLI Command Improvements
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With this release we have introduced a consistent naming pattern for accessing subcommands based on the noun (a Great Expectations object like `suite` or `docs`) and verb (an action like `edit` or `new`). The new user experience will allow us to more naturally organize access to CLI tools as new functionality is added.
Expectation Suite Naming and Namespace Changes
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Defining shared expectation suites and validating data from different sources is much easier in this release. The
DataContext, which manages storage and configuration of expectations, validations, profiling, and data docs, no
longer requires that expectation suites live in a datasource-specific “namespace.” Instead, you should name suites
with the logical name corresponding to your data, making it easy to share them or validate against different data
sources. For example, the expectation suite "npi" for National Provider Identifier data can now be shared across
teams who access the same logical data in local systems using Pandas, on a distributed Spark cluster, or via a
relational database.
Batch Kwargs, or instructions for a datasource to build a batch of data, are similarly freed from a required
namespace, and you can more easily integrate Great Expectations into workflows where you do not need to use a
BatchKwargsGenerator (usually because you have a batch of data ready to validate, such as in a table or a known
directory).
The most noticeable impact of this API change is in the complete removal of the DataAssetIdentifier class. For
example, the `create_expectation_suite` and `get_batch` methods now no longer require a data_asset_name parameter, relying only on the expectation_suite_name and batch_kwargs to do their job. Similarly, there is no more asset name normalization required. See the upgrade guide for more information.
Metrics and Evaluation Parameter Stores
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Metrics have received much more love in this release of Great Expectations! We've improved the system for declaring evaluation parameters that support dependencies between different expectation suites, so you can easily identify a particular field in the result of one expectation to use as the input into another. And the MetricsStore is now much more flexible, supporting a new ValidationAction that makes it possible to select metrics from a validation result to be saved in a database where they can power a dashboard.
Internal Type Changes and Improvements
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Finally, in this release, we have done a lot of work under the hood to make things more robust, including updating
all of the internal objects to be more strongly typed. That change, while largely invisible to end users, paves the
way for some really exciting opportunities for extending Great Expectations as we build a bigger community around
the project.
We are really excited about this release, and encourage you to upgrade right away to take advantage of the more
flexible naming and simpler API for creating, accessing, and sharing your expectations. As always feel free to join
us on Slack for questions you don't see addressed!