Support for Kedro 19

cypress.config.js

@@ -1,6 +1,7 @@
 const { defineConfig } = require('cypress');
 
 module.exports = defineConfig({
+  defaultCommandTimeout: 10000,
   env: {
     apiBaseUrl: 'http://localhost:4142',
     coverage: false,

demo-project/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.kedro]
 package_name = "demo_project"
 project_name = "modular-spaceflights"
-kedro_init_version = "0.18.14"
+kedro_init_version = "0.19.0"
 
 [tool.isort]
 multi_line_output = 3

demo-project/src/demo_project/cli.py

@@ -8,7 +8,6 @@
 from kedro.framework.cli.utils import (
     KedroCliError,
     _config_file_callback,
-    _reformat_load_versions,
     _split_params,
     env_option,
     split_string,
@@ -83,8 +82,7 @@ def cli():
     "-lv",
     type=str,
     multiple=True,
-    help=LOAD_VERSION_HELP,
-    callback=_reformat_load_versions,
+    help=LOAD_VERSION_HELP
 )
 @click.option("--pipeline", type=str, default=None, help=PIPELINE_ARG_HELP)
 @click.option(

demo-project/src/demo_project/extras/datasets/image_dataset.py

@@ -4,11 +4,11 @@
 import fsspec
 import numpy as np
 import PIL
-from kedro.io.core import AbstractDataSet, get_protocol_and_path
+from kedro.io.core import AbstractDataset, get_protocol_and_path
 from PIL import Image
 
 
-class ImageDataSet(AbstractDataSet):
+class ImageDataSet(AbstractDataset):
     """``ImageDataSet`` loads / save image data from a given filepath as `numpy` array
     using Pillow.
 

demo-project/src/docker_requirements.txt

@@ -1,4 +1,4 @@
-kedro~=0.18.0
+kedro>=0.18.0
 kedro-datasets[pandas.CSVDataSet,pandas.ExcelDataSet, pandas.ParquetDataSet, plotly.PlotlyDataSet, matplotlib.MatplotlibWriter]~=1.0
 scikit-learn~=1.0
 pillow~=9.0

package/features/steps/cli_steps.py

@@ -6,6 +6,7 @@
 import requests
 import yaml
 from behave import given, then, when
+from packaging.version import parse
 
 from features.steps.sh_run import ChildTerminatingPopen, run
 
@@ -76,8 +77,12 @@ def create_project_with_starter(context, starter):
 
 @given("I have installed the project's requirements")
 def install_project_requirements(context):
-    """Run ``pip install -r src/requirements.txt``."""
-    requirements_path = str(context.root_project_dir) + "/src/requirements.txt"
+    """Run ``pip install -r requirements.txt``."""
+    if context.kedro_version != "latest":
+        requirements_path = str(context.root_project_dir) + "/src/requirements.txt"
+    else:
+        requirements_path = str(context.root_project_dir) + "/requirements.txt"
+
     cmd = [context.pip, "install", "-r", requirements_path]
     res = run(cmd, env=context.env)
 
@@ -103,6 +108,9 @@ def install_lower_bound_requirements(context):
 @given('I have installed kedro version "{version}"')
 def install_kedro(context, version):
     """Install Kedro using pip."""
+    # add kedro_version to context
+    context.kedro_version = version
+
     if version == "latest":
         cmd = [context.pip, "install", "-U", "kedro"]
     else:

package/features/viz.feature

@@ -12,14 +12,14 @@ Feature: Viz plugin in new project
     Scenario: Execute viz with latest Kedro with lower-bound viz requirements
         Given I have installed kedro version "latest"
         And I have installed the lower-bound Kedro-viz requirements
-        And I have run a non-interactive kedro new with pandas-iris starter
+        And I have run a non-interactive kedro new with spaceflights-pandas starter
         And I have installed the project's requirements
         When I execute the kedro viz command
         Then kedro-viz should start successfully
 
     Scenario: Execute viz with latest Kedro
         Given I have installed kedro version "latest"
-        And I have run a non-interactive kedro new with pandas-iris starter
+        And I have run a non-interactive kedro new with spaceflights-pandas starter
         And I have installed the project's requirements
         When I execute the kedro viz command
         Then kedro-viz should start successfully

package/kedro_viz/data_access/managers.py

@@ -76,10 +76,11 @@ def resolve_dataset_factory_patterns(
         them against the datasets in the pipelines.
         """
         for pipeline in pipelines.values():
-            if hasattr(pipeline, "datasets"):
-                datasets = pipeline.datasets()  # kedro 0.19.0 onwards
-            else:
+            if hasattr(pipeline, "data_sets"):
+                # Support for Kedro 0.18.x
                 datasets = pipeline.data_sets()
+            else:
+                datasets = pipeline.datasets()
 
             for dataset_name in datasets:
                 try:

package/kedro_viz/data_access/repositories/catalog.py

@@ -15,16 +15,16 @@
     from kedro.io import DatasetNotFoundError, MemoryDataset
 except ImportError:  # pragma: no cover
     # older versions
-    from kedro.io import DataSetNotFoundError as DatasetNotFoundError
-    from kedro.io import MemoryDataSet as MemoryDataset
+    from kedro.io import DataSetNotFoundError as DatasetNotFoundError  # type: ignore
+    from kedro.io import MemoryDataSet as MemoryDataset  # type: ignore
 
 if TYPE_CHECKING:
     try:
         # kedro 0.18.12 onwards
         from kedro.io.core import AbstractDataset
     except ImportError:
         # older versions
-        from kedro.io.core import AbstractDataSet as AbstractDataset
+        from kedro.io.core import AbstractDataSet as AbstractDataset  # type: ignore
 
 logger = logging.getLogger(__name__)
 
@@ -86,8 +86,8 @@ def layers_mapping(self):
         except Exception:  # pragma: no cover
             datasets = self._catalog._datasets
 
-        # Maps layers according to the old format
-        if KEDRO_VERSION < parse("0.19.0"):
+        # Support for Kedro 0.18.x
+        if KEDRO_VERSION < parse("0.19.0"):  # pragma: no cover
             if self._catalog.layers is None:
                 self._layers_mapping = {
                     _strip_transcoding(dataset_name): None for dataset_name in datasets
@@ -100,7 +100,6 @@ def layers_mapping(self):
                             self._validate_layers_for_transcoding(dataset_name, layer)
                         self._layers_mapping[dataset_name] = layer
 
-        # Maps layers according to the new format
         for dataset_name in datasets:
             dataset = self._catalog._get_dataset(dataset_name)
             metadata = getattr(dataset, "metadata", None)

package/kedro_viz/data_access/repositories/tracking_datasets.py

@@ -17,7 +17,9 @@
         from kedro.io import AbstractVersionedDataset
     except ImportError:
         # older versions
-        from kedro.io import AbstractVersionedDataSet as AbstractVersionedDataset
+        from kedro.io import (  # type: ignore # isort:skip
+            AbstractVersionedDataSet as AbstractVersionedDataset,
+        )
 
 
 class TrackingDatasetsRepository:

package/kedro_viz/integrations/kedro/hooks.py

@@ -32,9 +32,10 @@ def after_catalog_created(self, catalog: DataCatalog):
         """
         # Temporary try/except block so the Kedro develop branch can work with Viz.
         try:
-            self.datasets = catalog._data_sets
+            self.datasets = catalog._datasets
         except Exception:  # pragma: no cover
-            self.datasets = catalog._datasets  # type: ignore[attr-defined]
+            # Support for Kedro 0.18.x
+            self.datasets = catalog._data_sets  # type: ignore[attr-defined]
 
     @hook_impl
     def after_dataset_loaded(self, dataset_name: str, data: Any):

package/kedro_viz/models/experiment_tracking.py

@@ -20,7 +20,9 @@
         from kedro.io import AbstractVersionedDataset
     except ImportError:
         # older versions
-        from kedro.io import AbstractVersionedDataSet as AbstractVersionedDataset
+        from kedro.io import (  # type: ignore # isort:skip
+            AbstractVersionedDataSet as AbstractVersionedDataset,
+        )
 
 logger = logging.getLogger(__name__)
 Base = declarative_base()

package/kedro_viz/models/flowchart.py

@@ -20,13 +20,13 @@
     from kedro.io.core import DatasetError
 except ImportError:  # pragma: no cover
     # older versions
-    from kedro.io.core import DataSetError as DatasetError
+    from kedro.io.core import DataSetError as DatasetError  # type: ignore
 try:
     # kedro 0.18.12 onwards
     from kedro.io.core import AbstractDataset
 except ImportError:  # pragma: no cover
     # older versions
-    from kedro.io.core import AbstractDataSet as AbstractDataset
+    from kedro.io.core import AbstractDataSet as AbstractDataset  # type: ignore
 
 logger = logging.getLogger(__name__)
 

package/kedro_viz/models/utils.py

@@ -11,7 +11,7 @@
         from kedro.io.core import AbstractDataset
     except ImportError:  # pragma: no cover
         # older versions
-        from kedro.io.core import AbstractDataSet as AbstractDataset
+        from kedro.io.core import AbstractDataSet as AbstractDataset  # type: ignore
 
 
 def get_dataset_type(dataset: "AbstractDataset") -> str:

package/tests/conftest.py

@@ -6,7 +6,7 @@
 import pytest
 from fastapi.testclient import TestClient
 from kedro.framework.session.store import BaseSessionStore
-from kedro.io import DataCatalog, Version
+from kedro.io import DataCatalog, MemoryDataset, Version
 from kedro.pipeline import Pipeline, node
 from kedro.pipeline.modular_pipeline import pipeline
 from kedro_datasets import pandas, tracking
@@ -20,13 +20,6 @@
 from kedro_viz.models.flowchart import GraphNode
 from kedro_viz.server import populate_data
 
-try:
-    # kedro 0.18.11 onwards
-    from kedro.io import MemoryDataset
-except ImportError:
-    # older versions
-    from kedro.io import MemoryDataSet as MemoryDataset
-
 
 @pytest.fixture
 def data_access_manager():
@@ -97,21 +90,20 @@ def train_model(model_inputs, parameters):
 @pytest.fixture
 def example_catalog():
     yield DataCatalog(
-        data_sets={
-            "uk.data_processing.raw_data": pandas.CSVDataset(filepath="raw_data.csv"),
-            "model_inputs": pandas.CSVDataset(filepath="model_inputs.csv"),
+        datasets={
+            "uk.data_processing.raw_data": pandas.CSVDataset(
+                filepath="raw_data.csv", metadata={"kedro-viz": {"layer": "raw"}}
+            ),
+            "model_inputs": pandas.CSVDataset(
+                filepath="model_inputs.csv",
+                metadata={"kedro-viz": {"layer": "model_inputs"}},
+            ),
             "uk.data_science.model": MemoryDataset(),
         },
         feed_dict={
             "parameters": {"train_test_split": 0.1, "num_epochs": 1000},
             "params:uk.data_processing.train_test_split": 0.1,
         },
-        layers={
-            "raw": {
-                "uk.data_processing.raw_data",
-            },
-            "model_inputs": {"model_inputs"},
-        },
         dataset_patterns={
             "{dataset_name}#csv": {
                 "type": "pandas.CSVDataset",
@@ -157,7 +149,7 @@ def train_model(model_inputs, parameters):
 @pytest.fixture
 def example_transcoded_catalog():
     yield DataCatalog(
-        data_sets={
+        datasets={
             "model_inputs@pandas": pandas.ParquetDataset(
                 filepath="model_inputs.parquet"
             ),
@@ -324,6 +316,7 @@ def pipeline_with_datasets_mock():
 
 
 # Create a mock for KedroPipeline with data_sets method
+# older versions
 @pytest.fixture
 def pipeline_with_data_sets_mock():
     pipeline = mock.MagicMock()

package/tests/test_api/main

@@ -1,7 +1,7 @@
 {
   "nodes": [
     {
-      "id": "f2e4bf0e",
+      "id": "782e4a43",
       "name": "process_data",
       "tags": ["split"],
       "pipelines": ["data_processing", "__default__"],
@@ -40,7 +40,7 @@
       "dataset_type": "pandas.csv_dataset.CSVDataset"
     },
     {
-      "id": "7b140b3f",
+      "id": "f2b25286",
       "name": "train_model",
       "tags": ["train"],
       "pipelines": ["__default__", "data_science"],
@@ -100,20 +100,20 @@
     }
   ],
   "edges": [
-    { "source": "f1f1425b", "target": "7b140b3f" },
+    { "source": "f1f1425b", "target": "f2b25286" },
     { "source": "0ecea0de", "target": "uk.data_science" },
     { "source": "f0ebef01", "target": "uk" },
-    { "source": "7b140b3f", "target": "d5a8b994" },
+    { "source": "f2b25286", "target": "d5a8b994" },
     { "source": "f0ebef01", "target": "uk.data_processing" },
-    { "source": "13399a82", "target": "f2e4bf0e" },
+    { "source": "13399a82", "target": "782e4a43" },
     { "source": "uk.data_science", "target": "d5a8b994" },
     { "source": "f1f1425b", "target": "uk" },
-    { "source": "0ecea0de", "target": "7b140b3f" },
+    { "source": "0ecea0de", "target": "f2b25286" },
     { "source": "uk", "target": "d5a8b994" },
     { "source": "f1f1425b", "target": "uk.data_science" },
-    { "source": "f2e4bf0e", "target": "0ecea0de" },
+    { "source": "782e4a43", "target": "0ecea0de" },
     { "source": "uk.data_processing", "target": "0ecea0de" },
-    { "source": "f0ebef01", "target": "f2e4bf0e" },
+    { "source": "f0ebef01", "target": "782e4a43" },
     { "source": "13399a82", "target": "uk" },
     { "source": "13399a82", "target": "uk.data_processing" }
   ],
@@ -146,7 +146,7 @@
       "outputs": ["0ecea0de"],
       "children": [
         { "id": "13399a82", "type": "data" },
-        { "id": "f2e4bf0e", "type": "task" }
+        { "id": "782e4a43", "type": "task" }
       ]
     },
     "uk": {
@@ -166,7 +166,7 @@
       "outputs": ["d5a8b994"],
       "children": [
         { "id": "d5a8b994", "type": "data" },
-        { "id": "7b140b3f", "type": "task" }
+        { "id": "f2b25286", "type": "task" }
       ]
     }
   },

package/tests/test_api/test_graphql/conftest.py

@@ -153,7 +153,7 @@ def savefig(cls, bytes_buffer, **kwargs):
     matplotlib_dataset.save(MockMatplotData)
 
     catalog = DataCatalog(
-        data_sets={
+        datasets={
             "metrics": metrics_dataset,
             "csv_dataset": csv_dataset,
             "more_metrics": more_metrics,
@@ -180,7 +180,7 @@ def example_multiple_run_tracking_catalog(example_run_ids, tmp_path):
     new_data = {"col1": 3, "col2": 3.23}
     new_metrics_dataset.save(new_data)
     catalog = DataCatalog(
-        data_sets={
+        datasets={
             "new_metrics": new_metrics_dataset,
         }
     )
@@ -202,7 +202,7 @@ def example_multiple_run_tracking_catalog_at_least_one_empty_run(
         version=Version(None, example_run_ids[0]),
     )
     catalog = DataCatalog(
-        data_sets={
+        datasets={
             "new_metrics": new_metrics_dataset,
         }
     )
@@ -221,7 +221,7 @@ def example_multiple_run_tracking_catalog_all_empty_runs(example_run_ids, tmp_pa
         version=Version(None, example_run_ids[0]),
     )
     catalog = DataCatalog(
-        data_sets={
+        datasets={
             "new_metrics": new_metrics_dataset,
         }
     )