Merge branch 'main' into feature/feedback-form

.github/workflows/deploy-demo.yml

@@ -65,7 +65,7 @@ jobs:
       - name: Update demo-project build directory with the latest changes
         run: |
           cd demo-project
-          if ! (kedro viz build |& tee /dev/stderr | grep -i -q "Success!"); then
+          if ! (kedro viz build --include-previews |& tee /dev/stderr | grep -i -q "Success!"); then
             exit 1
           fi
         shell: bash

RELEASE.md

@@ -16,6 +16,7 @@ Please follow the established format:
 - Add feedback component for slicing pipeline. (#2085)
 - Fixes design issues in metadata panel. (#2009)
 - Fix missing run command in metadata panel for task nodes. (#2055)
+- Add `UnavailableDataset` as a default dataset for `--lite` mode. (#2083)
 
 # Release 9.2.0
 

docs/source/kedro-viz_visualisation.md

@@ -238,4 +238,23 @@ import '@quantumblack/kedro-viz/lib/styles/styles.min.css';
 const MyApp = () => <div style={{height: `100vh`}}><KedroViz data={json} options={options} /></div>;
 ``` 
 
-For more information on how to use kedro as React component with all possible props please refer to [Kedro-Viz on npm](https://www.npmjs.com/package/@quantumblack/kedro-viz)
+For more information on how to use Kedro as a React component with all possible props, see [Kedro-Viz on NPM](https://www.npmjs.com/package/@quantumblack/kedro-viz)
+
+## Kedro-Viz in Visual Studio Code Extension
+
+To visualize Kedro project using Kedro-Viz in Visual Studio Code, follow these steps:
+
+1. **Install Kedro Extension**:
+Download Kedro extension from [marketplace](https://marketplace.visualstudio.com/items?itemName=kedro.Kedro) into Visual Studio Code.
+
+2. **Setup Kedro Extension**:
+Follow steps from [how-to-use-kedro-extension](https://github.com/kedro-org/vscode-kedro)
+
+3. **Open the Command Palette**: 
+Press `Cmd` + `Shift` + `P` (on macOS) or `Ctrl` + `Shift` + `P` (on Windows/Linux).
+
+4. **Run Kedro-Viz**:
+Type `kedro: Run Kedro Viz` and select the command.
+This will launch Kedro-Viz and display your pipeline visually within the extension.
+
+![Kedro Viz in VSCode](./images/viz-in-vscode.gif)

package/README.md

@@ -272,6 +272,12 @@ For more information on how to use Kedro-Viz as a React component, follow this [
 
 **_Our documentation contains [additional examples on how to visualise with Kedro-Viz.](https://docs.kedro.org/en/stable/visualisation/index.html)_**
 
+## Kedro-Viz in Visual Studio Code Extension
+
+To visualize Kedro project using Kedro-Viz in Visual Studio Code, please install Kedro extension in Visual Studio Code.
+
+For more information on how to use Kedro-Viz in Visual Studio Code, follow this [guide](https://marketplace.visualstudio.com/items?itemName=kedro.Kedro)
+
 ## Feature Flags
 
 Kedro-Viz uses features flags to roll out some experimental features. The following flags are currently in use:

package/kedro_viz/api/rest/responses.py

@@ -144,7 +144,7 @@ class DataNodeMetadataAPIResponse(BaseAPIResponse):
 
 
 class TranscodedDataNodeMetadataAPIReponse(BaseAPIResponse):
-    filepath: str
+    filepath: Optional[str] = None
     original_type: str
     transcoded_types: List[str]
     run_command: Optional[str] = None

package/kedro_viz/data_access/managers.py

@@ -8,12 +8,12 @@
 import networkx as nx
 from kedro.io import DataCatalog
 from kedro.io.core import DatasetError
-from kedro.io.memory_dataset import MemoryDataset
 from kedro.pipeline import Pipeline as KedroPipeline
 from kedro.pipeline.node import Node as KedroNode
 from sqlalchemy.orm import sessionmaker
 
 from kedro_viz.constants import DEFAULT_REGISTERED_PIPELINE_ID, ROOT_MODULAR_PIPELINE_ID
+from kedro_viz.integrations.utils import UnavailableDataset
 from kedro_viz.models.flowchart import (
     DataNode,
     GraphEdge,
@@ -325,9 +325,7 @@ def add_dataset(
             # Kedro Viz in lite mode. The `get_dataset` function
             # of DataCatalog calls AbstractDataset.from_config
             # which tries to create a Dataset instance from the pattern
-
-            # pylint: disable=abstract-class-instantiated
-            obj = MemoryDataset()  # type: ignore[abstract]
+            obj = UnavailableDataset()
 
         layer = self.catalog.get_layer_for_dataset(dataset_name)
         graph_node: Union[DataNode, TranscodedDataNode, ParametersNode]

package/kedro_viz/integrations/kedro/abstract_dataset_lite.py

@@ -0,0 +1,32 @@
+"""``AbstractDatasetLite`` is a custom implementation of Kedro's ``AbstractDataset``
+to provide an UnavailableDataset instance when running Kedro-Viz in lite mode.
+"""
+
+import logging
+from typing import Any, Optional
+
+from kedro.io.core import AbstractDataset, DatasetError
+
+from kedro_viz.integrations.utils import UnavailableDataset
+
+logger = logging.getLogger(__name__)
+
+
+class AbstractDatasetLite(AbstractDataset):
+    """``AbstractDatasetLite`` is a custom implementation of Kedro's ``AbstractDataset``
+    to provide an UnavailableDataset instance by overriding ``from_config`` of ``AbstractDataset``
+    when running Kedro-Viz in lite mode.
+    """
+
+    @classmethod
+    def from_config(
+        cls: type,
+        name: str,
+        config: dict[str, Any],
+        load_version: Optional[str] = None,
+        save_version: Optional[str] = None,
+    ) -> AbstractDataset:
+        try:
+            return AbstractDataset.from_config(name, config, load_version, save_version)
+        except DatasetError:
+            return UnavailableDataset()