Merge branch 'main' into bugfix/1293-SSR-bug

README.md

@@ -3,7 +3,7 @@
 <br />
 <p align="center">
 
-![Kedro-Viz Pipeline Visualisation](./.github/img/banner.png)
+![Kedro-Viz Pipeline Visualisation](https://raw.githubusercontent.com/kedro-org/kedro-viz/main/.github/img/banner.png)
 
 </p>
 

RELEASE.md

@@ -6,6 +6,14 @@ Please follow the established format:
 - Include the ID number for the related PR (or PRs) in parentheses
 -->
 
+# Release 6.4.1
+
+## Major features and improvements
+
+## Bug fixes and other changes
+
+- Fix to search for a '<lambda' Python function in the sidebar. (#1497)
+
 # Release 6.4.0
 
 ## Major features and improvements

package/kedro_viz/api/rest/responses.py

@@ -63,6 +63,7 @@ class Config:
 class DataNodeAPIResponse(BaseGraphNodeAPIResponse):
     layer: Optional[str]
     dataset_type: Optional[str]
+    stats: Optional[Dict]
 
     class Config:
         schema_extra = {
@@ -75,6 +76,7 @@ class Config:
                 "type": "data",
                 "layer": "primary",
                 "dataset_type": "kedro.extras.datasets.pandas.csv_dataset.CSVDataSet",
+                "stats": {"rows": 10, "columns": 2, "file_size": 2300},
             }
         }
 

package/kedro_viz/api/rest/router.py

@@ -49,12 +49,10 @@ async def get_single_node_metadata(node_id: str):
         return TaskNodeMetadata(node)
 
     if isinstance(node, DataNode):
-        dataset_stats = data_access_manager.get_stats_for_data_node(node)
-        return DataNodeMetadata(node, dataset_stats)
+        return DataNodeMetadata(node)
 
     if isinstance(node, TranscodedDataNode):
-        dataset_stats = data_access_manager.get_stats_for_data_node(node)
-        return TranscodedDataNodeMetadata(node, dataset_stats)
+        return TranscodedDataNodeMetadata(node)
 
     return ParametersNodeMetadata(node)
 

package/kedro_viz/data_access/managers.py

@@ -9,6 +9,7 @@
 from kedro.io import DataCatalog
 from kedro.pipeline import Pipeline as KedroPipeline
 from kedro.pipeline.node import Node as KedroNode
+from kedro.pipeline.pipeline import _strip_transcoding
 from sqlalchemy.orm import sessionmaker
 
 from kedro_viz.constants import DEFAULT_REGISTERED_PIPELINE_ID, ROOT_MODULAR_PIPELINE_ID
@@ -102,17 +103,14 @@ def add_dataset_stats(self, stats_dict: Dict):
 
         self.dataset_stats = stats_dict
 
-    def get_stats_for_data_node(
-        self, data_node: Union[DataNode, TranscodedDataNode]
-    ) -> Dict:
-        """Returns the dataset statistics for the data node if found else returns an
-        empty dictionary
+    def get_stats_for_data_node(self, data_node_name: str) -> Union[Dict, None]:
+        """Returns the dataset statistics for the data node if found
 
         Args:
-            The data node for which we need the statistics
+            The data node name for which we need the statistics
         """
 
-        return self.dataset_stats.get(data_node.name, {})
+        return self.dataset_stats.get(data_node_name, None)
 
     def add_pipeline(self, registered_pipeline_id: str, pipeline: KedroPipeline):
         """Iterate through all the nodes and datasets in a "registered" pipeline
@@ -278,6 +276,7 @@ def add_dataset(
                 layer=layer,
                 tags=set(),
                 dataset=obj,
+                stats=self.get_stats_for_data_node(_strip_transcoding(dataset_name)),
                 is_free_input=is_free_input,
             )
         graph_node = self.nodes.add_node(graph_node)

package/kedro_viz/models/flowchart.py

@@ -178,6 +178,7 @@ def create_data_node(
         layer: Optional[str],
         tags: Set[str],
         dataset: AbstractDataset,
+        stats: Optional[Dict],
         is_free_input: bool = False,
     ) -> Union["DataNode", "TranscodedDataNode"]:
         """Create a graph node of type DATA for a given Kedro DataSet instance.
@@ -188,6 +189,8 @@ def create_data_node(
             tags: The set of tags assigned to assign to the graph representation
                 of this dataset. N.B. currently it's derived from the node's tags.
             dataset: A dataset in a Kedro pipeline.
+            stats: The dictionary of dataset statistics, e.g.
+                {"rows":2, "columns":3, "file_size":100}
             is_free_input: Whether the dataset is a free input in the pipeline
         Returns:
             An instance of DataNode.
@@ -201,6 +204,7 @@ def create_data_node(
                 tags=tags,
                 layer=layer,
                 is_free_input=is_free_input,
+                stats=stats,
             )
 
         return DataNode(
@@ -210,6 +214,7 @@ def create_data_node(
             layer=layer,
             kedro_obj=dataset,
             is_free_input=is_free_input,
+            stats=stats,
         )
 
     @classmethod
@@ -434,6 +439,9 @@ class DataNode(GraphNode):
     # the type of this graph node, which is DATA
     type: str = GraphNodeType.DATA.value
 
+    # statistics for the data node
+    stats: Optional[Dict] = field(default=None)
+
     def __post_init__(self):
         self.dataset_type = get_dataset_type(self.kedro_obj)
 
@@ -517,6 +525,9 @@ class TranscodedDataNode(GraphNode):
     # the type of this graph node, which is DATA
     type: str = GraphNodeType.DATA.value
 
+    # statistics for the data node
+    stats: Optional[Dict] = field(default=None)
+
     def has_metadata(self) -> bool:
         return True
 
@@ -541,7 +552,6 @@ class DataNodeMetadata(GraphNodeMetadata):
 
     # the underlying data node to which this metadata belongs
     data_node: InitVar[DataNode]
-    dataset_stats: InitVar[Dict]
 
     # the optional plot data if the underlying dataset has a plot.
     # currently only applicable for PlotlyDataSet
@@ -561,12 +571,12 @@ class DataNodeMetadata(GraphNodeMetadata):
     stats: Optional[Dict] = field(init=False, default=None)
 
     # TODO: improve this scheme.
-    def __post_init__(self, data_node: DataNode, dataset_stats: Dict):
+    def __post_init__(self, data_node: DataNode):
         self.type = data_node.dataset_type
         dataset = cast(AbstractDataset, data_node.kedro_obj)
         dataset_description = dataset._describe()
         self.filepath = _parse_filepath(dataset_description)
-        self.stats = dataset_stats
+        self.stats = data_node.stats
 
         # Run command is only available if a node is an output, i.e. not a free input
         if not data_node.is_free_input:
@@ -625,11 +635,8 @@ class TranscodedDataNodeMetadata(GraphNodeMetadata):
 
     # the underlying data node to which this metadata belongs
     transcoded_data_node: InitVar[TranscodedDataNode]
-    dataset_stats: InitVar[Dict]
 
-    def __post_init__(
-        self, transcoded_data_node: TranscodedDataNode, dataset_stats: Dict
-    ):
+    def __post_init__(self, transcoded_data_node: TranscodedDataNode):
         original_version = transcoded_data_node.original_version
 
         self.original_type = get_dataset_type(original_version)
@@ -640,7 +647,7 @@ def __post_init__(
 
         dataset_description = original_version._describe()
         self.filepath = _parse_filepath(dataset_description)
-        self.stats = dataset_stats
+        self.stats = transcoded_data_node.stats
 
         if not transcoded_data_node.is_free_input:
             self.run_command = (

package/kedro_viz/server.py

@@ -44,9 +44,12 @@ def populate_data(
         data_access_manager.set_db_session(session_class)
 
     data_access_manager.add_catalog(catalog)
-    data_access_manager.add_pipelines(pipelines)
+
+    # add dataset stats before adding pipelines
     data_access_manager.add_dataset_stats(stats_dict)
 
+    data_access_manager.add_pipelines(pipelines)
+
 
 def run_server(
     host: str = DEFAULT_HOST,

package/test_requirements.txt

@@ -12,7 +12,7 @@ fastapi[all]>=0.73.0, <0.96.0
 isort~=5.11
 matplotlib~=3.5
 mypy~=1.0
-moto~=4.1.12 
+moto~=4.1.14 
 psutil==5.9.5  # same as Kedro for now
 pylint~=2.17
 pytest~=7.3

package/tests/test_api/test_rest/test_responses.py

@@ -108,6 +108,7 @@ def assert_example_data(response_data):
             "type": "data",
             "layer": "raw",
             "dataset_type": "pandas.csv_dataset.CSVDataSet",
+            "stats": None,
         },
         {
             "id": "f0ebef01",
@@ -118,6 +119,7 @@ def assert_example_data(response_data):
             "type": "parameters",
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "0ecea0de",
@@ -128,6 +130,7 @@ def assert_example_data(response_data):
             "type": "data",
             "layer": "model_inputs",
             "dataset_type": "pandas.csv_dataset.CSVDataSet",
+            "stats": {"columns": 12, "rows": 29768},
         },
         {
             "id": "7b140b3f",
@@ -150,6 +153,7 @@ def assert_example_data(response_data):
             "type": "parameters",
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "d5a8b994",
@@ -160,6 +164,7 @@ def assert_example_data(response_data):
             "type": "data",
             "layer": None,
             "dataset_type": "io.memory_dataset.MemoryDataset",
+            "stats": None,
         },
         {
             "id": "uk.data_processing",
@@ -170,6 +175,7 @@ def assert_example_data(response_data):
             "modular_pipelines": None,
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "uk.data_science",
@@ -180,6 +186,7 @@ def assert_example_data(response_data):
             "modular_pipelines": None,
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "uk",
@@ -190,6 +197,7 @@ def assert_example_data(response_data):
             "modular_pipelines": None,
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
     ]
     assert_nodes_equal(response_data.pop("nodes"), expected_nodes)
@@ -480,6 +488,7 @@ def assert_example_transcoded_data(response_data):
             "modular_pipelines": [],
             "layer": None,
             "dataset_type": "io.memory_dataset.MemoryDataset",
+            "stats": None,
         },
         {
             "id": "f0ebef01",
@@ -490,6 +499,7 @@ def assert_example_transcoded_data(response_data):
             "modular_pipelines": ["uk", "uk.data_processing"],
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "0ecea0de",
@@ -500,6 +510,7 @@ def assert_example_transcoded_data(response_data):
             "modular_pipelines": [],
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "2302ea78",
@@ -519,6 +530,7 @@ def assert_example_transcoded_data(response_data):
             "modular_pipelines": [],
             "layer": None,
             "dataset_type": None,
+            "stats": None,
         },
         {
             "id": "1d06a0d7",
@@ -529,6 +541,7 @@ def assert_example_transcoded_data(response_data):
             "modular_pipelines": [],
             "layer": None,
             "dataset_type": "io.memory_dataset.MemoryDataset",
+            "stats": None,
         },
     ]
 
@@ -572,7 +585,6 @@ def test_transcoded_data_node_metadata(self, example_transcoded_api):
                 "pandas.parquet_dataset.ParquetDataSet",
             ],
             "run_command": "kedro run --to-outputs=model_inputs@pandas2",
-            "stats": {},
         }
 
 
@@ -614,7 +626,6 @@ def test_data_node_metadata_for_free_input(self, client):
         assert response.json() == {
             "filepath": "raw_data.csv",
             "type": "pandas.csv_dataset.CSVDataSet",
-            "stats": {},
         }
 
     def test_parameters_node_metadata(self, client):
@@ -664,6 +675,7 @@ def test_get_pipeline(self, client):
                 "type": "data",
                 "layer": "model_inputs",
                 "dataset_type": "pandas.csv_dataset.CSVDataSet",
+                "stats": {"columns": 12, "rows": 29768},
             },
             {
                 "id": "7b140b3f",
@@ -686,6 +698,7 @@ def test_get_pipeline(self, client):
                 "type": "parameters",
                 "layer": None,
                 "dataset_type": None,
+                "stats": None,
             },
             {
                 "id": "d5a8b994",
@@ -696,6 +709,7 @@ def test_get_pipeline(self, client):
                 "type": "data",
                 "layer": None,
                 "dataset_type": "io.memory_dataset.MemoryDataset",
+                "stats": None,
             },
             {
                 "id": "uk",
@@ -706,6 +720,7 @@ def test_get_pipeline(self, client):
                 "modular_pipelines": None,
                 "layer": None,
                 "dataset_type": None,
+                "stats": None,
             },
             {
                 "id": "uk.data_science",
@@ -716,6 +731,7 @@ def test_get_pipeline(self, client):
                 "modular_pipelines": None,
                 "layer": None,
                 "dataset_type": None,
+                "stats": None,
             },
         ]
         assert_nodes_equal(response_data.pop("nodes"), expected_nodes)

package/tests/test_data_access/test_repositories/test_modular_pipelines.py

@@ -47,6 +47,7 @@ def test_add_input(self):
             layer="model",
             tags=set(),
             dataset=kedro_dataset,
+            stats=None,
         )
         modular_pipelines.add_input("data_science", data_node)
         assert data_node.id in data_science_pipeline.inputs
@@ -62,6 +63,7 @@ def test_add_output(self):
             layer="model",
             tags=set(),
             dataset=kedro_dataset,
+            stats=None,
         )
         modular_pipelines.add_output("data_science", data_node)
         assert data_node.id in data_science_pipeline.outputs