[DOCS] DSB-64 removes outdated v2/v3 references from the docs (#7519)

docs/docusaurus/docs/contributing/contributing_test.md

@@ -144,7 +144,7 @@ The test fixture files are stored in subdirectories of `tests/test_definitions/`
 * multicolumn_map_expectations
 * other_expectations
 
-By convention, the name of the the file is the name of the Expectation, with a .json suffix. Creating a new json file will automatically add the new Expectation tests to the test suite.
+By convention, the name of the file is the name of the Expectation, with a .json suffix. Creating a new json file will automatically add the new Expectation tests to the test suite.
 
 Note: If you are implementing a new Expectation, but don’t plan to immediately implement it for all execution environments, you should add the new test to the appropriate list(s) in the `candidate_test_is_on_temporary_notimplemented_list_v2_api` method within `tests/test_utils.py`. Often, we see Expectations developed first for pandas, then later extended to SqlAlchemy and Spark.
 

docs/docusaurus/docs/deployment_patterns/how_to_use_great_expectations_with_airflow.md

@@ -32,9 +32,9 @@ To import the GreatExpectationsOperator in your Airflow project, run the followi
 pip install airflow-provider-great-expectations==0.1.1
 ```
 
-It’s recommended to specify a version when installing the package. To make use of the latest Great Expectations V3 API, you need to specify a version >= `0.1.0`.
+It’s recommended to specify a version when installing the package. To make use of the latest Great Expectations provider for Airflow, you need to specify a version >= `0.1.0`.
 
-> *The Great Expectations V3 API requires Airflow 2.1+. If you're still running Airflow 1.x, you need to upgrade to at least 2.1 before using v0.1.0+ of the GreatExpectationsOperator.*
+> *The current Great Expectations release requires Airflow 2.1+. If you're still running Airflow 1.x, you need to upgrade to at least 2.1 before using v0.1.0+ of the GreatExpectationsOperator.*
 
 
 ## Using the `GreatExpectationsOperator`

docs/docusaurus/docs/deployment_patterns/how_to_use_great_expectations_with_google_cloud_platform_and_bigquery.md

@@ -52,15 +52,6 @@ Relevant documentation for the components can also be found here:
 - [How to host and share Data Docs on GCS](../guides/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_gcs.md)
 - Optionally, you can also use a [Secret Manager for GCP Credentials](../guides/setup/configuring_data_contexts/how_to_configure_credentials.md)
 
-:::note Note on V3 Expectations for BigQuery
-
-  A small number of V3 Expectations have not been migrated to BigQuery, and will be very soon. These include:
-
-  - `expect_column_quantile_values_to_be_between`
-  - `expect_column_kl_divergence_to_be_less_than`
-
-:::
-
 ## Part 1: Local Configuration of Great Expectations that connects to Google Cloud Platform
 
 ### 1. If necessary, upgrade your Great Expectations version

docs/docusaurus/docs/guides/connecting_to_your_data/how_to_choose_between_working_with_a_single_or_multiple_batches_of_data.md

@@ -12,7 +12,7 @@ By the end of this guide, you will know when it will be most beneficial to be wo
 
 <Prerequisites>
 
-- [Understand the basics of Datasources in the V3 (Batch Request) API](../../terms/datasource.md)
+- [Understand the basics of Datasources](../../terms/datasource.md)
 - [Understand the basics of requesting data with a Batch Requests](./how_to_get_one_or_more_batches_of_data_from_a_configured_datasource.md)
 
 </Prerequisites>

docs/docusaurus/docs/guides/connecting_to_your_data/how_to_choose_which_dataconnector_to_use.md

@@ -10,7 +10,7 @@ This guide demonstrates how to choose which <TechnicalTag tag="data_connector" t
 
 <Prerequisites>
 
-- [Understand the basics of Datasources in the V3 (Batch Request) API](../../terms/datasource.md)
+- [Understand the basics of Datasources](../../terms/datasource.md)
 - Learned how to configure a [Data Context using test_yaml_config](../setup/configuring_data_contexts/how_to_configure_datacontext_components_using_test_yaml_config.md)
 
 </Prerequisites>

docs/docusaurus/docs/guides/connecting_to_your_data/how_to_configure_a_runtimedataconnector.md

@@ -6,11 +6,11 @@ import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
 
-This guide demonstrates how to configure a RuntimeDataConnector and only applies to the V3 (Batch Request) API. A `RuntimeDataConnector` allows you to specify a <TechnicalTag tag="batch" text="Batch" /> using a Runtime <TechnicalTag tag="batch_request" text="Batch Request" />, which is used to create a Validator. A <TechnicalTag tag="validator" text="Validator" /> is the key object used to create <TechnicalTag tag="expectation" text="Expectations" /> and <TechnicalTag tag="validation" text="Validate" /> datasets.
+This guide demonstrates how to configure a RuntimeDataConnector. A `RuntimeDataConnector` allows you to specify a <TechnicalTag tag="batch" text="Batch" /> using a Runtime <TechnicalTag tag="batch_request" text="Batch Request" />, which is used to create a Validator. A <TechnicalTag tag="validator" text="Validator" /> is the key object used to create <TechnicalTag tag="expectation" text="Expectations" /> and <TechnicalTag tag="validation" text="Validate" /> datasets.
 
 <Prerequisites>
 
-- [Understand the basics of Datasources in the V3 (Batch Request) API](../../terms/datasource.md)
+- [Understand the basics of Datasources](../../terms/datasource.md)
 - Learned how to configure a [Data Context using test_yaml_config](../setup/configuring_data_contexts/how_to_configure_datacontext_components_using_test_yaml_config.md)
 
 </Prerequisites>

docs/docusaurus/docs/guides/setup/configuring_metadata_stores/how_to_configure_an_expectation_store_in_azure_blob_storage.md

@@ -117,8 +117,4 @@ If you followed Step 4, the output should include the Expectation we copied to A
 
 ```bash
 great_expectations suite list
-
-Using v2 (Batch Kwargs) API
-1 Expectation Suite found:
-- exp1
 ```

docs/docusaurus/docs/guides/validation/checkpoints/components_how_to_create_a_new_checkpoint/_preface.mdx

@@ -2,9 +2,3 @@ import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
 
 
 This guide will help you create a new <TechnicalTag tag="checkpoint" text="Checkpoint" />, which allows you to couple an <TechnicalTag tag="expectation_suite" text="Expectation Suite" /> with a data set to <TechnicalTag tag="validation" text="Validate" />.
-
-:::note
-
-As of Great Expectations version 0.13.7, we have updated and improved the Checkpoints feature. You can continue to use your existing legacy Checkpoint workflows if you’re working with concepts from the Batch Kwargs (v2) API. If you’re using concepts from the BatchRequest (v3) API, please refer to the new Checkpoints guides.
-
-:::

docs/docusaurus/docs/guides/validation/checkpoints/components_how_to_create_a_new_checkpoint/_steps_for_checkpoints_.mdx

@@ -4,7 +4,7 @@
 This how-to guide assumes you have already:
 
 * [Set up a working deployment of Great Expectations](../../../../tutorials/getting_started/tutorial_overview.md)
-* [Configured a Datasource using the BatchRequest (v3) API](../../../../tutorials/getting_started/tutorial_connect_to_data.md)
+* [Configured a Datasource](../../../../tutorials/getting_started/tutorial_connect_to_data.md)
 * [Created an Expectation Suite](../../../../tutorials/getting_started/tutorial_create_expectations.md)
 
 :::

docs/docusaurus/docs/guides/validation/checkpoints/how_to_configure_a_new_checkpoint_using_test_yaml_config.md

@@ -11,7 +11,7 @@ This how-to guide demonstrates advanced examples for configuring a <TechnicalTag
 <Prerequisites>
 
 - [Set up a working deployment of Great Expectations](../../../tutorials/getting_started/tutorial_overview.md)
-- [Configured a Datasource using the v3 API](../../../tutorials/getting_started/tutorial_connect_to_data.md)
+- [Configured a Datasource](../../../tutorials/getting_started/tutorial_connect_to_data.md)
 - [Created an Expectation Suite](../../../tutorials/getting_started/tutorial_create_expectations.md)
 
 </Prerequisites>
@@ -57,7 +57,7 @@ From here you can continue to edit your Checkpoint. After each change you should
 
 ### 5. Save your edited Checkpoint
 
-Once you have made all of the changes you planned to implement and your last `test_yaml_config()` check passed, you are ready to save the Checkpoint you've created.  At this point, run the remaining cells in your Jupyter Notebook.  
+Once you have made all the changes you planned to implement and your last `test_yaml_config()` check passed, you are ready to save the Checkpoint you've created.  At this point, run the remaining cells in your Jupyter Notebook.  
 
 Your checkpoint will be saved by the cell that contains the command:
 

docs/docusaurus/docs/integrations/integration_datahub.md

@@ -93,12 +93,9 @@ The Validation Results would show up in Validation tab on Dataset page in DataHu
 ## Further discussion
 
 ### Things to consider
-Currently this integration only supports v3 API Datasources using `SqlAlchemyExecutionEngine`.
-
 This integration does not support
 
-- v2 Datasources such as `SqlAlchemyDataset`
-- v3 Datasources using an Execution Engine other than `SqlAlchemyExecutionEngine` (Spark, Pandas)
+- Datasources using an Execution Engine other than `SqlAlchemyExecutionEngine` (Spark, Pandas)
 - Cross-dataset Expectations (those involving > 1 table)
 
 ### When things don't work

docs/docusaurus/docs/reference/expectations/implemented_expectations.md

@@ -62,4 +62,4 @@ out the missing implementations!
 |`expect_column_pair_cramers_phi_value_to_be_less_than` *                        | Y          | N       | N         |
 |`expect_multicolumn_sum_to_equal`                                               | Y          | Y       | Y         |
 
-`*` This Expectation has not yet been migrated to the v3 (Batch Request) API.
+`*` This Expectation has not yet been migrated versions above GX v 0.13.x.

docs/docusaurus/docs/terms/data_connector.md

@@ -149,14 +149,6 @@ A **Batch Spec** is an Execution Engine-specific description of the Batch define
 
 A Data Connector is responsible for working with an Execution Engine to translate Batch Definitions into a Batch Spec that enables Great Expectations to access the data using that Execution Engine.
 
-
-
-## API basics
-
-:::info API note
-In the updated V3 Great Expectations API, Data Connectors replace the Batch Kwargs Generators from the V2 Great Expectations API.
-:::
-
 ### How to access
 
 Other than specifying a Data Connector when you configure a Datasource, you will not need to directly interact with one.  Great Expectations will handle using them behind the scenes.

docs_rtd/_templates/layout.html

@@ -211,7 +211,7 @@
             <a class="header-item" href="https://greatexpectations.io/integrations"
               >INTEGRATIONS</a
             >
-          </li>          
+          </li>
           <li>
             <a class="header-item" href="https://docs.greatexpectations.io/docs/"
               >DOCUMENTATION</a
@@ -241,7 +241,7 @@
             <a class="header-item" href="https://jobs.greatexpectations.io/"
               >CAREERS</a
             >
-          </li>      
+          </li>
         </ul>
       </div>
     </div>
@@ -254,14 +254,14 @@
     width: 100%;
 "
   >
-    NOTE: This is Legacy V2 documentation.
+    NOTE: This is a legacy site for documentation from Great Expectations version 0.13.0 and earlier.
     <a
       href="https://docs.greatexpectations.io/docs/"
       style="text-decoration: underline; color: black; font-weight: bold;"
     >
-      See New Documentation
+       See the new documentation
     </a>
-    for V3 and newer
+     for the more recent and current versions of GX.
   </center>
 </div>