[DOCS] CLI Clean-up (#7904)

Co-authored-by: Rob Gray <104205257+kwcanuck@users.noreply.github.com>

docs/docusaurus/docs/guides/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_a_filesystem.md

@@ -3,9 +3,6 @@ title: How to host and share Data Docs on a filesystem
 ---
 import Prerequisites from '../../connecting_to_your_data/components/prerequisites.jsx'
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 This guide will explain how to host and share <TechnicalTag relative="../../../" tag="data_docs" text="Data Docs" /> on a filesystem.
 
@@ -36,20 +33,9 @@ data_docs_sites:
 
 ### 2. Test that your configuration is correct by building the site
 
-Use the following <TechnicalTag relative="../../../" tag="cli" text="CLI" /> command: ``great_expectations docs build --site-name local_site``. If successful, the CLI will open your newly built Data Docs site and provide the path to the index page.
-
-```bash
-> great_expectations docs build --site-name local_site
-
-The following Data Docs sites will be built:
-
- - local_site: file:///great_expectations/uncommitted/data_docs/local_site/index.html
-
-Would you like to proceed? [Y/n]: Y
-
-Building Data Docs...
+Run the the following Python code to build and open your Data Docs:
 
-Done building Data Docs
+``` python name="tests/integration/docusaurus/reference/glossary/data_docs.py data_docs"
 ```
 
 ## Additional notes

docs/docusaurus/docs/guides/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_amazon_s3.md

@@ -9,9 +9,6 @@ import ApplyThePolicy from './components_how_to_host_and_share_data_docs_on_amaz
 import AddANewS3SiteToTheDataDocsSitesSectionOfYourGreatExpectationsYml from './components_how_to_host_and_share_data_docs_on_amazon_s3/_add_a_new_s3_site_to_the_data_docs_sites_section_of_your_great_expectationsyml.mdx'
 import TestThatYourConfigurationIsCorrectByBuildingTheSite from './components_how_to_host_and_share_data_docs_on_amazon_s3/_test_that_your_configuration_is_correct_by_building_the_site.mdx'
 import AdditionalNotes from './components_how_to_host_and_share_data_docs_on_amazon_s3/_additional_notes.mdx'
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 <Preface />
 

docs/docusaurus/docs/guides/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_azure_blob_storage.md

@@ -3,9 +3,6 @@ title: How to host and share Data Docs on Azure Blob Storage
 ---
 import Prerequisites from '../../connecting_to_your_data/components/prerequisites.jsx'
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 This guide will explain how to host and share <TechnicalTag relative="../../../" tag="data_docs" text="Data Docs" /> on Azure Blob Storage. 
 Data Docs will be served using an Azure Blob Storage static website with restricted access.
@@ -55,7 +52,7 @@ data_docs_sites:
       base_directory: uncommitted/data_docs/local_site/
     site_index_builder:
       class_name: DefaultSiteIndexBuilder
-  az_site:  # this is a user-selected name - you may select your own
+  new_site_name:  # this is a user-selected name - you can select your own
     class_name: SiteBuilder
     store_backend:
        class_name: TupleAzureBlobStoreBackend
@@ -97,26 +94,12 @@ The most common authentication methods are supported:
 ### 4. Build the Azure Blob Data Docs site
 
 You can create or modify an <TechnicalTag tag="expectation_suite" text="Expectation Suite" /> and this will build the Data Docs website.
-Or you can use the following <TechnicalTag relative="../../../" tag="cli" text="CLI" /> command: ``great_expectations docs build --site-name az_site``.
-
-```bash
-> great_expectations docs build --site-name az_site
-
- The following Data Docs sites will be built:
-
- - az_site: https://<your-storage-account>.blob.core.windows.net/$web/index.html
 
- Would you like to proceed? [Y/n]: y
+Run the the following Python code to build and open your Data Docs:
 
- Building Data Docs...
-
- Done building Data Docs
+``` python name="tests/integration/docusaurus/reference/glossary/data_docs.py data_docs_site"
 ```
 
-If successful, the CLI will provide the object URL of the index page. 
-You may secure the access of your website using an IP filtering mechanism.
-
-
 ### 5. Limit the access to your company
 
 - On your Azure Storage Account Settings click on **Networking**

docs/docusaurus/docs/guides/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_gcs.md

@@ -3,9 +3,6 @@ title: How to host and share Data Docs on GCS
 ---
 import Prerequisites from '../../connecting_to_your_data/components/prerequisites.jsx'
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 This guide will explain how to host and share <TechnicalTag relative="../../../" tag="data_docs" text="Data Docs" /> on Google Cloud Storage. We recommend using IP-based access, which is achieved by deploying a simple Google App Engine app. Data Docs can also be served on Google Cloud Storage if the contents of the bucket are set to be publicly readable, but this is strongly discouraged.
 
@@ -58,7 +55,7 @@ We recommend placing it in your project directory, for example ``great_expectati
 
 ### 4. Deploy your Google App Engine app
 
-Issue the following <TechnicalTag relative="../../../" tag="cli" text="CLI" /> command from within the app directory created above:
+Run the following CLI command from within the app directory you created previously:
 
 ```bash name="tests/integration/docusaurus/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_gcs.py gcloud app deploy"
 ```
@@ -76,14 +73,9 @@ You may also replace the default ``local_site`` if you would only like to mainta
 
 ### 7. Build the GCS Data Docs site
 
-Use the following CLI command: 
-
-```bash name="tests/integration/docusaurus/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_gcs.py build data docs command"
-```
-
-If successful, the CLI will provide the object URL of the index page. Since the bucket is not public, this URL will be inaccessible. Rather, you will access the Data Docs site using the App Engine app configured above.
+Run the the following Python code to build and open your Data Docs:
 
-```bash name="tests/integration/docusaurus/setup/configuring_data_docs/how_to_host_and_share_data_docs_on_gcs.py build data docs output"
+``` python name="tests/integration/docusaurus/reference/glossary/data_docs.py data_docs_site"
 ```
 
 ### 8. Test that everything was configured properly by launching your App Engine app

docs/docusaurus/docs/guides/setup/installation/local.md

@@ -9,9 +9,6 @@ import InstallGreatExpectations from './components_local/_install_great_expectat
 import VerifyGeInstallSucceeded from './components_local/_verify_ge_install_succeeded.mdx'
 import NextSteps from '/docs/guides/setup/components/install_nextsteps.md'
 import InstallCongratulations from '/docs/guides/setup/components/install_congrats.md'
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 <Preface />
 

docs/docusaurus/docs/guides/setup/optional_dependencies/cloud/how_to_set_up_gx_to_work_with_data_on_aws_s3.md

@@ -9,9 +9,6 @@ keywords: [Great Expectations, Data Context, Filesystem, Amazon Web Services S3]
 
 import TechnicalTag from '/docs/term_tags/_tag.mdx';
 import Prerequisites from '/docs/components/_prerequisites.jsx'
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 <!-- ## Prerequisites -->
 import PrereqInstalledAwsCli from '/docs/components/prerequisites/_aws_installed_the_aws_cli.mdx'

docs/docusaurus/docs/guides/setup/optional_dependencies/cloud/how_to_set_up_gx_to_work_with_data_on_gcs.md

@@ -9,9 +9,6 @@ keywords: [Great Expectations, Data Context, Filesystem, GCS, Google Cloud Stora
 
 import TechnicalTag from '/docs/term_tags/_tag.mdx';
 import Prerequisites from '/docs/components/_prerequisites.jsx'
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 <!-- ## Prerequisites -->
 import PrereqGcpServiceAccount from '/docs/components/prerequisites/_gcp_service_account.md'

docs/docusaurus/docs/guides/validation/advanced/how_to_deploy_a_scheduled_checkpoint_with_cron.md

@@ -3,9 +3,6 @@ title: How to deploy a scheduled Checkpoint with cron
 ---
 import Prerequisites from '../../connecting_to_your_data/components/prerequisites.jsx'
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 This guide will help you deploy a scheduled <TechnicalTag tag="checkpoint" text="Checkpoint" /> with cron.
 
@@ -22,10 +19,9 @@ This guide will help you deploy a scheduled <TechnicalTag tag="checkpoint" text=
 
 ### 1. Verify Checkpoint suitability
 
-First, verify that your Checkpoint is runnable via shell:
+Run the following command to verify that your Checkpoint runs:
 
-```bash
-great_expectations checkpoint run my_checkpoint
+```python name="tests/integration/docusaurus/reference/glossary/checkpoints.py retrieve_and_run"
 ```
 
 ### 2. Get `great_expectations` full path

docs/docusaurus/docs/guides/validation/validation_actions/how_to_collect_openlineage_metadata_using_a_validation_action.md

@@ -4,9 +4,6 @@ title: How to collect OpenLineage metadata using an Action
 
 import Prerequisites from '../../../guides/connecting_to_your_data/components/prerequisites.jsx';
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 [OpenLineage](https://openlineage.io) is an open framework for collection and analysis of data lineage. It tracks the movement of data over time, tracing relationships between datasets. Data engineers can use data lineage metadata to determine the root cause of failures, identify performance bottlenecks, and simulate the effects of planned changes.
 
@@ -57,11 +54,10 @@ action_list:
 
 ### 3.  Test your Action by Validating a Batch of data.
 
-Run your Checkpoint to Validate a <TechnicalTag tag="batch" text="Batch" /> of data and emit lineage events to the OpenLineage backend.  This can be done from the command line:
+Run the following command to retrieve and run a Checkpoint to Validate a <TechnicalTag tag="batch" text="Batch" /> of data and then emit lineage events to the OpenLineage backend:
 
- ```bash
- % great_expectations checkpoint run <checkpoint_name>
- ```
+```python name="tests/integration/docusaurus/reference/glossary/checkpoints.py retrieve_and_run"
+```
 
 :::note Reminder
 Our [guide on how to Validate data by running a Checkpoint](../how_to_validate_data_by_running_a_checkpoint.md) has more detailed instructions for this step, including instructions on how to run a checkpoint from a Python script instead of from the <TechnicalTag tag="cli" text="CLI" />.

docs/docusaurus/docs/guides/validation/validation_actions/how_to_update_data_docs_as_a_validation_action.md

@@ -4,9 +4,6 @@ title: How to update Data Docs after Validating a Checkpoint
 
 import Prerequisites from '../../../guides/connecting_to_your_data/components/prerequisites.jsx';
 import TechnicalTag from '@site/docs/term_tags/_tag.mdx';
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
 
 This guide will explain how to use an <TechnicalTag tag="action" text="Action" /> to update <TechnicalTag tag="data_docs" text="Data Docs" /> sites with new <TechnicalTag tag="validation_result" text="Validation Results" /> from running a <TechnicalTag tag="checkpoint" text="Checkpoint" />.
 
@@ -73,17 +70,14 @@ The ``StoreValidationResultAction`` Action must appear before  ``UpdateDataDocsA
 
 Test that your new Action is configured correctly:
 
-Run the Checkpoint from your code or the <TechnicalTag tag="cli" text="CLI" /> and verify that no errors are thrown.
+Run the following command to run the Checkpoint and verify that no errors are returned:
 
 ```python
 import great_expectations as gx
 context = gx.get_context()
 checkpoint_name = "your checkpoint name here"
 context.run_checkpoint(checkpoint_name=checkpoint_name)
 ```
-```bash
-$ great_expectations checkpoint run <your checkpoint name>
-```
 
 Finally, check your Data Docs sites to confirm that a new Validation Result has been added.
 

docs/docusaurus/docs/integrations/integration_datahub.md

@@ -5,10 +5,6 @@ authors:
     url: https://datahubproject.io
 ---
 
-import CLIRemoval from '/docs/components/warnings/_cli_removal.md'
-
-<CLIRemoval />
-
 :::info
 * Maintained By: DataHub
 * Status: Beta
@@ -85,8 +81,9 @@ action_list:
 
 #### 3. Run the GX checkpoint
 
-```bash
-great_expectations checkpoint run my_checkpoint #replace my_checkpoint with your checkpoint name
+Run the following command to retrieve and run a Checkpoint:
+
+```python name="tests/integration/docusaurus/reference/glossary/checkpoints.py retrieve_and_run"
 ```
 
 #### 4. Hurray!

tests/integration/docusaurus/reference/glossary/checkpoints.py

@@ -0,0 +1,44 @@
+from great_expectations.datasource.fluent import Datasource
+from great_expectations.datasource.fluent import DataAsset
+from great_expectations.checkpoint import SimpleCheckpoint
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/checkpoints.py setup">
+import great_expectations as gx
+
+context = gx.get_context()
+# </snippet>
+
+# to open Data Docs, we need validation results which we get by creating a suite and running a checkpoint
+datasource: Datasource = context.get_datasource("taxi_datasource")
+asset: DataAsset = datasource.get_asset("yellow_tripdata")
+batch_request = asset.build_batch_request()
+validator = context.get_validator(batch_request=batch_request)
+
+validator.expect_column_values_to_not_be_null("pickup_datetime")
+validator.expect_column_values_to_be_between("passenger_count", auto=True)
+
+taxi_suite = validator.get_expectation_suite()
+taxi_suite.expectation_suite_name = "taxi_suite"
+
+context.add_expectation_suite(expectation_suite=taxi_suite)
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/checkpoints.py create_and_run">
+checkpoint = SimpleCheckpoint(
+    name="taxi_checkpoint",
+    data_context=context,
+    batch_request=batch_request,
+    expectation_suite_name="taxi_suite",
+)
+checkpoint.run()
+# </snippet>
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/checkpoints.py save">
+context.add_checkpoint(checkpoint=checkpoint)
+# </snippet>
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/checkpoints.py retrieve_and_run">
+checkpoint = context.get_checkpoint("taxi_checkpoint")
+checkpoint.run()
+# </snippet>
+
+assert True

tests/integration/docusaurus/reference/glossary/data_docs.py

@@ -0,0 +1,41 @@
+import great_expectations as gx
+from great_expectations.datasource.fluent import Datasource
+from great_expectations.datasource.fluent import DataAsset
+from great_expectations.checkpoint import SimpleCheckpoint
+
+context = gx.get_context()
+
+# to open data docs, we need validation results which we get by creating a suite and running a checkpoint
+datasource: Datasource = context.get_datasource("taxi_datasource")
+asset: DataAsset = datasource.get_asset("yellow_tripdata")
+batch_request = asset.build_batch_request()
+validator = context.get_validator(batch_request=batch_request)
+
+validator.expect_column_values_to_not_be_null("pickup_datetime")
+validator.expect_column_values_to_be_between("passenger_count", auto=True)
+
+taxi_suite = validator.get_expectation_suite()
+taxi_suite.expectation_suite_name = "taxi_suite"
+
+context.add_expectation_suite(expectation_suite=taxi_suite)
+
+checkpoint = SimpleCheckpoint(
+    name="taxi_checkpoint",
+    data_context=context,
+    batch_request=batch_request,
+    expectation_suite_name="taxi_suite",
+)
+checkpoint.run()
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/data_docs.py data_docs">
+context.build_data_docs()
+context.open_data_docs()
+# </snippet>
+
+# <snippet name="tests/integration/docusaurus/reference/glossary/data_docs.py data_docs_site">
+site_name = "new_site_name"
+context.build_data_docs(site_names=site_name)
+context.open_data_docs(site_name=site_name)
+# </snippet>
+
+assert True