Enable Markdownlint rule MD046/code-block-style (#12429)

.markdownlint.yml

@@ -60,6 +60,3 @@ MD040: false
 
 # MD041/first-line-heading/first-line-h1
 MD041: false
-
-# MD046/code-block-style
-MD046: false

UPDATING.md

@@ -2234,14 +2234,18 @@ custom auth backends might need a small change: `is_active`,
 `is_authenticated`, and `is_anonymous` should now be properties. What this means is if
 previously you had this in your user class
 
-    def is_active(self):
-      return self.active
+```python
+def is_active(self):
+  return self.active
+```
 
 then you need to change it like this
 
-    @property
-    def is_active(self):
-      return self.active
+```python
+@property
+def is_active(self):
+  return self.active
+```
 
 ### Support autodetected schemas to GoogleCloudStorageToBigQueryOperator
 
@@ -2251,21 +2255,27 @@ If BigQuery tables are created outside of airflow and the schema is not defined
 
 define a schema_fields:
 
-    gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
-      ...
-      schema_fields={...})
+```python
+gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
+  ...
+  schema_fields={...})
+```
 
 or define a schema_object:
 
-    gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
-      ...
-      schema_object='path/to/schema/object)
+```python
+gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
+  ...
+  schema_object='path/to/schema/object')
+```
 
 or enabled autodetect of schema:
 
-    gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
-      ...
-      autodetect=True)
+```python
+gcs_to_bq.GoogleCloudStorageToBigQueryOperator(
+  ...
+  autodetect=True)
+```
 
 ## Airflow 1.10.1
 

UPGRADING_TO_2.0.md

@@ -817,7 +817,9 @@ The table below shows the differences:
 This endpoint ``/api/v1/dags/{dag_id}/dagRuns`` also allows you to filter dag_runs with parameters such as ``start_date``, ``end_date``, ``execution_date`` etc in the query string.
 Therefore the operation previously performed by this endpoint
 
-    /api/experimental/dags/<string:dag_id>/dag_runs/<string:execution_date>
+```
+/api/experimental/dags/<string:dag_id>/dag_runs/<string:execution_date>
+```
 
 can now be handled with filter parameters in the query string.
 Getting information about latest runs can be accomplished with the help of

chart/README.md

@@ -314,23 +314,31 @@ to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is w
 
 1. Start a project using [astro-cli](https://github.com/astronomer/astro-cli), which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`.
 
-        mkdir my-airflow-project && cd my-airflow-project
-        astro dev init
+    ```shell script
+    mkdir my-airflow-project && cd my-airflow-project
+    astro dev init
+    ```
 
 2. Then build the image:
 
-        docker build -t my-dags:0.0.1 .
+    ```shell script
+    docker build -t my-dags:0.0.1 .
+    ```
 
 3. Load the image into kind:
 
-        kind load docker-image my-dags:0.0.1
+    ```shell script
+    kind load docker-image my-dags:0.0.1
+    ```
 
 4. Upgrade Helm deployment:
 
-        helm upgrade airflow -n airflow \
-            --set images.airflow.repository=my-dags \
-            --set images.airflow.tag=0.0.1 \
-            astronomer/airflow
+    ```shell script
+    helm upgrade airflow -n airflow \
+        --set images.airflow.repository=my-dags \
+        --set images.airflow.tag=0.0.1 \
+        astronomer/airflow
+    ```
 
 ## Contributing