Fix markdown linting test

Author: izmalk

releases/3.4/yaml/docs/.pymarkdown.yml

@@ -0,0 +1,3 @@
+plugins:
+  md022:
+    enabled: false

releases/3.4/yaml/docs/tutorial/1-environment-setup.md

@@ -190,7 +190,10 @@ kubectl get roles -n spark
 kubectl get rolebindings -n spark
 ```
 
-[details="Output example"]
+<details>
+
+<summary> Output example</summary>
+
 ```text
 kubectl get serviceaccounts -n spark
 NAME      SECRETS   AGE
@@ -206,7 +209,8 @@ kubectl get rolebindings -n spark
 NAME                 ROLE              AGE
 spark-role-binding   Role/spark-role   2m48s
 ```
-[/details]
+
+</details>
 
 Now, launch a PySpark shell using the service account you created earlier to verify that it works:
 
@@ -394,7 +398,10 @@ You can also see the configuration stored in a Kubernetes secret:
 kubectl get secret -n spark -o yaml
 ```
 
-[details="Output example"]
+<details>
+
+<summary> Output example</summary>
+
 ```text
 apiVersion: v1
 items:
@@ -418,7 +425,8 @@ kind: List
 metadata:
   resourceVersion: ""
 ```
-[/details]
+
+</details>
 
 With that, the tutorial’s environment setup is complete!
 

releases/3.4/yaml/docs/tutorial/2-distributed-data-processing.md

@@ -106,7 +106,6 @@ You can do that by manually setting the version of image used on the cluster sid
 ```bash
 spark-client.service-account-registry add-config --username spark --namespace spark --conf spark.kubernetes.container.image=ghcr.io/canonical/charmed-spark:3.4.2-22.04_edge
 ```
-```
 
 Here, we split the data into two parts, generating a distributed data structure, where each line is stored in one of the (possibly many) executors.
 The number of vowels in each line is computed, line by line, with the `count_vowels` function on each executor in parallel.