Merge pull request #574 from hkad98/PSDK-172

Rename 'insight' to 'visualization'

Reviewed-by: Jan Kadlec
             https://github.com/hkad98

Makefile

@@ -100,7 +100,6 @@ remove-cassettes:
 
 .PHONY: new-docs
 new-docs:
-	git submodule update --init --recursive --depth 1; \
 	cd docs; \
 	npm install; \
 	hugo server

docker-compose.yaml

@@ -41,6 +41,12 @@ services:
       HEADER_HOST: localhost
     command: ["python3", "upload_demo_layout.py"]
 
+  docs:
+    build:
+      context: .
+      dockerfile: docs/Dockerfile
+    ports:
+      - "1313:1313"
 
 volumes:
   gooddata-cn-ce-data:

docs/Dockerfile

@@ -0,0 +1,14 @@
+FROM node:20.11.1-bookworm-slim
+
+RUN npm install -g [email protected]
+
+COPY docs docs
+
+RUN apt-get update && \
+    apt-get install -y git make golang-go curl
+
+WORKDIR docs
+RUN npm install
+
+# accessible on http://localhost:1313/docs/
+ENTRYPOINT ["hugo", "server", "--bind", "0.0.0.0"]

docs/content/en/docs/_index.md

@@ -52,25 +52,28 @@ Integrate GoodData analytics into your continuous delivery practices by, for exa
 
 ```python
 # Reads visualizations from workspace
-insights = sdk.insights.get_insights("123")
+visualizations = sdk.visualizations.get_visualizations("123")
 
 # Iterate through visualizations and check if they are valid
-for insight in insights:
+for visualization in visualizations:
     try:
-        sdk.tables.for_insight("123", insight)
+        sdk.visualizations.for_visualization("123", visualization)
     except Exception:
-        print(f"Visualization {insight.title} is broken.")
+        print(f"Visualization {visualization.title} is broken.")
 
 ```
 
 #### Create data pipelines
 
-Export your data, levarage services like machine learning to transform your data and import the data back into GoodData to visualize the results and gain insights. In the Example below, we demonstrate GoodPandas, which can leverage machine learning practices.
+Export your data,
+levarage services like machine learning to transform your data
+and import the data back into GoodData to visualize the results and gain visualizations.
+In the Example below, we demonstrate GoodPandas, which can leverage machine learning practices.
 ```python
 pandas = GoodPandas(os.getenv('HOST'), os.getenv('TOKEN'))
 df = pandas.data_frames(workspace_id="123")
 
-campaign_spend = df.for_insight("campaign_spend")
+campaign_spend = df.for_visualization("campaign_spend")
 
 # Now you have a dataframe with data from your visualization
 # You can do linear regression, clustering, predictions, analysis, etc.

docs/content/en/docs/execution/exports/_index.md

@@ -11,7 +11,7 @@ Create dashboard exports or automate your pipelines. Can be for [example](#examp
 
 * [export_pdf](./export_pdf/)
 * [export_tabular](./export_tabular/)
-* [export_tabular_by_insight_id](./export_tabular_by_insight_id/)
+* [export_tabular_by_visualization_id](./export_tabular_by_visualization_id/)
 
 
 ## Example
@@ -58,10 +58,10 @@ def send_mail(send_from, send_to, subject, text, files, server):
 
 
 def export_tabular():
-    # Export a particular insight in the desired format (CSV / XLSX)
-    sdk.export.export_tabular_by_insight_id(
+    # Export a particular visualization in the desired format (CSV / XLSX)
+    sdk.export.export_tabular_by_visualization_id(
         workspace_id = "demo",
-        insight_id = "revenue",
+        visualization_id = "revenue",
         file_format = "CSV",
         file_name = "revenue_export.csv"
     )

docs/content/en/docs/execution/exports/export_tabular_by_insight_id.md → docs/content/en/docs/execution/exports/export_tabular_by_visualization_id.md

@@ -1,13 +1,13 @@
 ---
-title: "export_tabular_by_insight_id"
-linkTitle: "export_tabular_by_insight_id"
+title: "export_tabular_by_visualization_id"
+linkTitle: "export_tabular_by_visualization_id"
 weight: 110
 superheading: "export."
 ---
 
-``export_tabular_by_insight_id(
+``export_tabular_by_visualization_id(
         workspace_id: str,
-        insight_id: str,
+        visualization_id: str,
         file_format: str,
         file_name: Optional[str] = None,
         settings: Optional[ExportSettings] = None,
@@ -17,16 +17,16 @@ superheading: "export."
         max_retry: float = 5.0,
     )``
 
-    Exports the tabular data for an Insight by its ID.
+    Exports the tabular data for an visualization by its ID.
 
 
 
 {{% parameters-block  title="Parameters" %}}
 {{< parameter p_name="workspace_id" p_type="string" >}}
 The ID of the GoodData Workspace.
 {{< /parameter >}}
-{{< parameter p_name="insight_id" p_type="string" >}}
-The ID of the GoodData Insight.
+{{< parameter p_name="visualization_id" p_type="string" >}}
+The ID of the GoodData visualization.
 {{< /parameter >}}
 {{< parameter p_name="file_format" p_type="string" >}}
 The format of the file to be exported.
@@ -63,7 +63,7 @@ host = "https://www.example.com"
 token = "<your_personal_access_token>"
 sdk = GoodDataSdk.create(host, token)
 
-sdk.export.export_tabular_by_insight_id(
-        workspace_id="demo", insight_id="campaign_spend", file_format="CSV")
+sdk.export.export_tabular_by_visualization_id(
+        workspace_id="demo", visualization_id="campaign_spend", file_format="CSV")
 
 ```

docs/content/en/docs/pandas-overview.md

@@ -92,9 +92,9 @@ non_indexed_df = frames.not_indexed(
     )
 )
 
-# create data frame based on the contents of the insight. if the insight contains labels and
+# create data frame based on the contents of the visualization. if the visualization contains labels and
 #  measures, the data frame will contain index or hierarchical index.
-insight_df = frames.for_insight('insight_id')
+df = frames.for_visualization('visualization_id')
 
 # create data frame based on the content of the items dict. if the dict contains both labels
 # and measures, the frame will contain index or hierarchical index.

docs/content/en/docs/workspace-content/workspace-content/_index.md

@@ -19,7 +19,7 @@ Within a multitenant workspace hierarchy, the analytical model of a parent works
 ### Entity methods
 
 * [get_full_catalog](./get_full_catalog/)
-* [get_insights](./get_insights/)
+* [get_visualizations](./get_visualizations/)
 * [get_metrics_catalog](./get_metrics_catalog/)
 * [get_facts_catalog](./get_facts_catalog/)
 * [get_attributes_catalog](./get_attributes_catalog/)
@@ -32,7 +32,7 @@ Within a multitenant workspace hierarchy, the analytical model of a parent works
 
 ### Table methods
 
-* [for_insight](./for_insight/)
+* [for_visualization](./for_visualization/)
 * [for_items](./for_items/)
 
 ## Example

docs/content/en/docs/workspace-content/workspace-content/for_insight.md → docs/content/en/docs/workspace-content/workspace-content/for_visualization.md

@@ -1,22 +1,22 @@
 ---
-title: "for_insight"
-linkTitle: "for_insight"
+title: "for_visualization"
+linkTitle: "for_visualization"
 weight: 10
 superheading: "tables."
 ---
 
 
 
-``for_insight(workspace_id: str, insight: Insight)``
+``for_visualization(workspace_id: str, visualization: Visualization)``
 
-Gets data as an ExecutionTable from the given visualization.
+Get data as an ExecutionTable from the given visualization.
 
-{{% parameters-block  title="Parameters" %}}
+{{% parameters-block title="Parameters" %}}
 {{< parameter p_name="workspace_id" p_type="string" >}}
 Workspace identification string e.g. "demo"
 {{< /parameter >}}
-{{< parameter p_name="insight" p_type="Insight" >}}
-Insight object, representing a visualization.
+{{< parameter p_name="visualization" p_type="Visualization" >}}
+Visualization object, representing a visualization.
 {{< /parameter >}}
 {{% /parameters-block %}}
 
@@ -30,9 +30,9 @@ Visualization data wrapper object.
 
 ```python
 # Get visualization
-campaign_spend_insight = sdk.insights.get_insight(workspace_id="123", insight_id="campaign_spend")
+campaign_spend = sdk.visualizations.get_visualization(workspace_id="123", visualization_id="campaign_spend")
 # Get the visualization as Execution Table
-sdk.tables.for_insight(workspace_id="123", insight=campaign_spend_insight)
+sdk.tables.for_visualization(workspace_id="123", visualization=campaign_spend)
 
 # ExecutionTable(
 #   response=Execution(

docs/content/en/docs/workspace-content/workspace-content/get_visualization.md

@@ -0,0 +1,35 @@
+---
+title: "get_visualization"
+linkTitle: "get_visualization"
+weight: 15
+superheading: "visualizations."
+---
+
+
+
+``get_visualization(workspace_id: str, visualization_id: str)``
+
+Get a single visualization from a workspace.
+
+
+{{% parameters-block  title="Parameters" %}}
+{{< parameter p_name="workspace_id" p_type="string" >}}
+Workspace identification string e.g. "demo"
+{{< /parameter >}}
+{{< parameter p_name="visualization_id" p_type="string" >}}
+Visualization identifier string e.g. "bikes"
+{{< /parameter >}}
+{{% /parameters-block %}}
+
+{{% parameters-block title="Returns"%}}
+{{< parameter p_type="Visualization" >}}
+A single Visualization object contains side loaded metadata about the entities it references
+{{< /parameter >}}
+{{% /parameters-block %}}
+
+## Example
+
+```python
+# Get all visualizations
+visualizations = sdk.visualizations.get_visualizations(workspace_id="123")
+```

docs/content/en/docs/workspace-content/workspace-content/get_visualizations.md

@@ -0,0 +1,29 @@
+---
+title: "get_visualizations"
+linkTitle: "get_visualizations"
+weight: 15
+superheading: "visualizations."
+---
+
+``get_visualizations(workspace_id: str)``
+
+Get a list of visualization objects.
+
+{{% parameters-block title="Parameters" %}}
+{{< parameter p_name="workspace_id" p_type="string" >}}
+Workspace identification string e.g. "demo"
+{{< /parameter >}}
+{{% /parameters-block %}}
+
+{{% parameters-block title="Returns"%}}
+{{< parameter p_type="list[Visualization]" >}}
+All available visualizations, each visualization will contain side loaded metadata about the entities it references
+{{< /parameter >}}
+{{% /parameters-block %}}
+
+## Example
+
+```python
+# Get all visualizations
+visualizations = sdk.visualizations.get_visualizations(workspace_id="123")
+```

gooddata-dbt/README.md

@@ -56,8 +56,8 @@ The plugin provides the following use cases:
   - Reads content of `gooddata_layout` folder and deploys analytics model to GoodData
 - store_analytics
   - Reads analytics model from GoodData instance and stores it to disk to `gooddata_layout` folder
-- test_insights
-  - Lists all insights(reports) from GoodData instance, and executes each report to validate it
+- test_visualizations
+  - Lists all visualizations execution from GoodData instance, and executes each report to validate it
 - dbt_cloud
   - Runs dbt cloud job through their API. Alternative to running dbt-core locally.
   - If running in CI pipeline, it can also notify about performance degradations in a form of GitHub/Gitlab comment.

gooddata-dbt/gooddata_dbt/args.py

@@ -190,8 +190,8 @@ def parse_arguments(description: str) -> argparse.Namespace:
     set_gooddata_upper_case_args(store_analytics)
     store_analytics.set_defaults(method="store_analytics")
 
-    test_insights = subparsers.add_parser("test_insights")
-    set_environment_id_arg(test_insights)
-    test_insights.set_defaults(method="test_insights")
+    test_visualizations = subparsers.add_parser("test_visualizations")
+    set_environment_id_arg(test_visualizations)
+    test_visualizations.set_defaults(method="test_visualizations")
 
     return parser.parse_args()