Feature/remove session store

CONTRIBUTING.md

@@ -210,14 +210,6 @@ make run PROJECT_PATH=<path-to-your-test-project>/new-kedro-project
 
 > **Note**: Once the backend development server is launched at port 4142, the local app will always pull data from that server. To prevent this, you can comment out the proxy setting in `package.json` and restart the dev server at port 4141.
 
-#### Launch the development server with the `SQLiteSessionStore`
-
-Kedro-Viz provides a `SQLiteSessionStore` that users can use in their project to enable experiment tracking functionality. If you want to use this session store with the development server, make sure you don't use a relative path when specifying the store's location in `settings.py`. For example, `demo-project` specifies the local `data` directory within a project as the session store's location as follows:
-
-```python
-from kedro_viz.integrations.kedro.sqlite_store import SQLiteStore
-SESSION_STORE_ARGS = {"path": str(Path(__file__).parents[2] / "data")}
-```
 
 Owing to this coupling between the project settings and Kedro-Viz, if you wish to execute any Kedro commands on `demo-project` (including `kedro run`), you will need to install the Kedro-Viz Python package. To install your local development version of the package, run:
 

demo-project/src/demo_project/settings.py

@@ -2,25 +2,6 @@
 # List the installed plugins for which to disable auto-registry
 # DISABLE_HOOKS_FOR_PLUGINS = ("kedro-viz",)
 
-from pathlib import Path
-
-# Define where to store data from a KedroSession. Defaults to BaseSessionStore.
-# from kedro.framework.session.store import ShelveStore
-from kedro_viz.integrations.kedro.sqlite_store import SQLiteStore
-
-SESSION_STORE_CLASS = SQLiteStore
-SESSION_STORE_ARGS = {"path": str(Path(__file__).parents[2] / "data")}
-
-# Setup for collaborative experiment tracking.
-# SESSION_STORE_ARGS = {"path": str(Path(__file__).parents[2] / "data"),
-#                       "remote_path": "s3://{path-to-session_store}" }
-
-# Define custom context class. Defaults to `KedroContext`
-# CONTEXT_CLASS = KedroContext
-
-# Define the configuration folder. Defaults to `conf`
-# CONF_ROOT = "conf"
-
 from kedro.config import OmegaConfigLoader  # NOQA
 
 CONFIG_LOADER_CLASS = OmegaConfigLoader

docs/source/index.md

@@ -6,7 +6,7 @@
 
 </p>
 
-Kedro-Viz is an interactive development tool for visualising data science pipelines built with [Kedro](https://github.com/kedro-org/kedro). Kedro-Viz also enables users to view and compare different experiment runs within their Kedro project.
+Kedro-Viz is an interactive development tool for visualising data science pipelines built with [Kedro](https://github.com/kedro-org/kedro).
 
 Kedro-Viz features include:
 
@@ -18,7 +18,6 @@ Kedro-Viz features include:
 🎨 Rich metadata side panel to display parameters, plots, etc.     
 📊 Support for all types of [Plotly charts](https://plotly.com/javascript/).   
 ♻️ Autoreload on code change.   
-🧪 Support for experiment tracking and comparing runs in a Kedro project.
 
 Take a look at the <a href="https://demo.kedro.org/" target="_blank" rel="noopener noreferrer">live demo</a> for a preview of Kedro-Viz.
 
@@ -30,7 +29,6 @@ kedro-viz_visualisation
 share_kedro_viz
 preview_datasets
 slice_a_pipeline
-experiment_tracking
 ```
 
 ```{toctree}

docs/source/kedro-viz_visualisation.md

@@ -89,7 +89,6 @@ Some of the known limitations while using `--lite` flag:
 
 * If the datasets are not resolved, they will be defaulted to a custom dataset `UnavailableDataset`. 
 * The flowchart will not show the layers information for the datasets.
-* Experiment Tracking will not work if the pre-requisite of having kedro-datasets version 2.1.0 and above is not met.
 
 ## Automatic visualisation updates
 

package/README.md

@@ -205,33 +205,6 @@ Options:
   -h, --help          Show this message and exit.
 ```
 
-### Experiment Tracking usage
-
-To enable [experiment tracking](https://docs.kedro.org/en/stable/experiment_tracking/index.html) in Kedro-Viz, you need to add the Kedro-Viz `SQLiteStore` to your Kedro project.
-
-This can be done by adding the below code to `settings.py` in the `src` folder of your Kedro project.
-
-```python
-from kedro_viz.integrations.kedro.sqlite_store import SQLiteStore
-from pathlib import Path
-SESSION_STORE_CLASS = SQLiteStore
-SESSION_STORE_ARGS = {"path": str(Path(__file__).parents[2] / "data")}
-```
-
-Once the above set-up is complete, tracking datasets can be used to track relevant data for Kedro runs. More information on how to use tracking datasets can be found in the [experiment tracking documentation](https://docs.kedro.org/en/stable/experiment_tracking/index.html)
-
-**Notes:**
-
-- Experiment Tracking is only available for Kedro-Viz >= 4.0.2 and Kedro >= 0.17.5
-- Prior to Kedro 0.17.6, when using tracking datasets, you will have to explicitly mark the datasets as `versioned` for it to show up properly in Kedro-Viz experiment tracking tab. From Kedro >= 0.17.6, this is done automatically:
-
-```yaml
-train_evaluation.r2_score_linear_regression:
-  type: tracking.MetricsDataset
-  filepath: ${base_location}/09_tracking/linear_score.json
-  versioned: true
-```
-
 ### Standalone React component usage
 
 To use Kedro-Viz as a standalone React component, you can follow the example below. However, please note that Kedro-Viz does not support server-side rendering (SSR). If you're using Next.js or another SSR framework, you should be aware of this limitation.

package/kedro_viz/database.py

@@ -21,21 +21,3 @@ def configure_wal_for_azure(engine):
     if is_azure_ml:
         with engine.connect() as conn:
             conn.execute(text("PRAGMA journal_mode=WAL;"))
-
-
-def make_db_session_factory(session_store_location: str) -> sessionmaker:
-    """SQLAlchemy connection to a SQLite DB"""
-    database_url = f"sqlite:///{session_store_location}"
-    engine = create_engine(database_url, connect_args={"check_same_thread": False})
-    # TODO: making db session factory shouldn't depend on models.
-    # So want to move the table creation elsewhere ideally.
-    # But this means returning engine as well as session class.
-
-    # Check if we are running in an Azure ML environment if so enable WAL mode.
-    configure_wal_for_azure(engine)
-
-    # Create the database tables if they do not exist.
-    Base.metadata.create_all(bind=engine)
-
-    # Return a session factory bound to the engine.
-    return sessionmaker(bind=engine)

package/kedro_viz/integrations/kedro/data_loader.py

@@ -13,7 +13,6 @@
 from kedro import __version__
 from kedro.framework.project import configure_project, pipelines
 from kedro.framework.session import KedroSession
-from kedro.framework.session.store import BaseSessionStore
 from kedro.framework.startup import bootstrap_project
 from kedro.io import DataCatalog
 from kedro.pipeline import Pipeline
@@ -73,8 +72,7 @@ def _load_data_helper(
             configuration.
         is_lite: A flag to run Kedro-Viz in lite mode.
     Returns:
-        A tuple containing the data catalog, pipeline dictionary, session store
-        and dataset stats dictionary.
+        A tuple containing the data catalog, pipeline dictionary and dataset stats dictionary.
     """
 
     with KedroSession.create(
@@ -88,7 +86,6 @@ def _load_data_helper(
             session._hook_manager = _VizNullPluginManager()  # type: ignore
 
         context = session.load_context()
-        session_store = session._store
 
         # patch the AbstractDataset class for a custom
         # implementation to handle kedro.io.core.DatasetError
@@ -110,7 +107,7 @@ def _load_data_helper(
         # Useful for users who have `get_current_session` in their `register_pipelines()`.
         pipelines_dict = dict(pipelines)
         stats_dict = _get_dataset_stats(project_path)
-    return catalog, pipelines_dict, session_store, stats_dict
+    return catalog, pipelines_dict, stats_dict
 
 
 def load_data(
@@ -120,7 +117,7 @@ def load_data(
     package_name: Optional[str] = None,
     extra_params: Optional[Dict[str, Any]] = None,
     is_lite: bool = False,
-) -> Tuple[DataCatalog, Dict[str, Pipeline], BaseSessionStore, Dict]:
+) -> Tuple[DataCatalog, Dict[str, Pipeline], Dict]:
     """Load data from a Kedro project.
     Args:
         project_path: the path where the Kedro project is located.
@@ -134,8 +131,7 @@ def load_data(
             configuration.
         is_lite: A flag to run Kedro-Viz in lite mode.
     Returns:
-        A tuple containing the data catalog, pipeline dictionary, session store
-        and dataset stats dictionary.
+        A tuple containing the data catalog, pipeline dictionary,and dataset stats dictionary.
     """
     if package_name:
         configure_project(package_name)