docs(datasets): blacken code in rst literal blocks

Signed-off-by: Deepyaman Datta <deepyaman.datta@utexas.edu>

.pre-commit-config.yaml

@@ -23,6 +23,15 @@ repos:
           - "--ignore=E203,E266,E501,W503"
         exclude: "^kedro_airflow/dag_template.py|^template.py"
 
+  - repo: https://github.com/adamchainz/blacken-docs
+    rev: 1.16.0
+    hooks:
+    - id: blacken-docs
+      args:
+        - "--rst-literal-blocks"
+      additional_dependencies:
+        - black==22.12.0
+
   - repo: local
     hooks:
       # pylint quick checks

kedro-datasets/kedro_datasets/databricks/managed_table_dataset.py

@@ -175,12 +175,13 @@ class ManagedTableDataset(AbstractVersionedDataset):
     .. code-block:: python
 
         from pyspark.sql import SparkSession
-        from pyspark.sql.types import (StructField, StringType,
-                                       IntegerType, StructType)
+        from pyspark.sql.types import StructField, StringType, IntegerType, StructType
         from kedro_datasets.databricks import ManagedTableDataset
-        schema = StructType([StructField("name", StringType(), True),
-                             StructField("age", IntegerType(), True)])
-        data = [('Alex', 31), ('Bob', 12), ('Clarke', 65), ('Dave', 29)]
+
+        schema = StructType(
+            [StructField("name", StringType(), True), StructField("age", IntegerType(), True)]
+        )
+        data = [("Alex", 31), ("Bob", 12), ("Clarke", 65), ("Dave", 29)]
         spark_df = SparkSession.builder.getOrCreate().createDataFrame(data, schema)
         dataset = ManagedTableDataset(table="names_and_ages")
         dataset.save(spark_df)

kedro-datasets/kedro_datasets/pandas/hdf_dataset.py

@@ -35,15 +35,15 @@ class HDFDataset(AbstractVersionedDataset[pd.DataFrame, pd.DataFrame]):
     Example usage for the
     `Python API <https://kedro.readthedocs.io/en/stable/data/\
     advanced_data_catalog_usage.html>`_:
-    ::
+
+    .. code-block:: pycon
 
         >>> from kedro_datasets.pandas import HDFDataset
         >>> import pandas as pd
         >>>
-        >>> data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
-        ...                      'col3': [5, 6]})
+        >>> data = pd.DataFrame({"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]})
         >>>
-        >>> dataset = HDFDataset(filepath="test.h5", key='data')
+        >>> dataset = HDFDataset(filepath="test.h5", key="data")
         >>> dataset.save(data)
         >>> reloaded = dataset.load()
         >>> assert data.equals(reloaded)

kedro-datasets/kedro_datasets/spark/README.md

@@ -23,6 +23,7 @@ Supported file formats are:
 from kedro.framework.hooks import hook_impl
 from pyspark.sql import SparkSession
 
+
 class SparkStreamsHook:
     @hook_impl
     def after_pipeline_run(self) -> None: