docs: enable Sphinx linter & fixing (#19515)

* docs: enable Sphinx linter
* fixes

Author: Borda

.pre-commit-config.yaml

@@ -71,6 +71,11 @@ repos:
         additional_dependencies: [tomli]
         args: ["--in-place"]
 
+  - repo: https://github.com/sphinx-contrib/sphinx-lint
+    rev: v0.9.1
+    hooks:
+      - id: sphinx-lint
+
   - repo: https://github.com/asottile/yesqa
     rev: v1.5.0
     hooks:
@@ -86,6 +91,8 @@ repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: "v0.1.15"
     hooks:
+      - id: ruff-format
+        args: ["--preview"]
       - id: ruff
         args: ["--fix", "--preview"]
 

docs/source-app/core_api/lightning_app/communication_content.rst

@@ -87,13 +87,13 @@ And here's the output you get when running the App using the **Lightning CLI**:
 
 .. code-block:: console
 
-	INFO: Your app has started. View it in your browser: http://127.0.0.1:7501/view
-	State: {'works': {'w': {'vars': {'counter': 1}}}}
-	State: {'works': {'w': {'vars': {'counter': 2}}}}
-	State: {'works': {'w': {'vars': {'counter': 3}}}}
-	State: {'works': {'w': {'vars': {'counter': 3}}}}
-	State: {'works': {'w': {'vars': {'counter': 4}}}}
-	...
+    INFO: Your app has started. View it in your browser: http://127.0.0.1:7501/view
+    State: {'works': {'w': {'vars': {'counter': 1}}}}
+    State: {'works': {'w': {'vars': {'counter': 2}}}}
+    State: {'works': {'w': {'vars': {'counter': 3}}}}
+    State: {'works': {'w': {'vars': {'counter': 3}}}}
+    State: {'works': {'w': {'vars': {'counter': 4}}}}
+    ...
 
 ----
 

docs/source-app/core_api/lightning_app/dynamic_work_content.rst

@@ -41,9 +41,9 @@ There are a couple of ways you can add a dynamic Work:
         def run(self):
 
             if not hasattr(self, "work"):
-		        # The `Work` component is created and attached here.
+                # The `Work` component is created and attached here.
                 setattr(self, "work", Work())
-	        # Run the `Work` component.
+            # Run the `Work` component.
             getattr(self,  "work").run()
 
 **OPTION 2:** Use the built-in Lightning classes :class:`~lightning.app.structures.Dict` or :class:`~lightning.app.structures.List`
@@ -60,7 +60,7 @@ There are a couple of ways you can add a dynamic Work:
 
         def run(self):
             if "work" not in self.dict:
-			    # The `Work` component is attached here.
+                # The `Work` component is attached here.
                 self.dict["work"] = Work()
             self.dict["work"].run()
 

docs/source-app/glossary/environment_variables.rst

@@ -24,4 +24,4 @@ Environment variables are available in all Flows and Works, and can be accessed
     print(os.environ["BAZ"])  # FAZ
 
 .. note::
-	Environment variables are not encrypted. For sensitive values, we recommend using :ref:`Encrypted Secrets <secrets>`.
+    Environment variables are not encrypted. For sensitive values, we recommend using :ref:`Encrypted Secrets <secrets>`.

docs/source-app/glossary/secrets.rst

@@ -8,7 +8,7 @@ Encrypted Secrets allow you to pass private data to your apps, like API keys, ac
 Secrets provide you with a secure way to store this data in a way that is accessible to Apps so that they can authenticate third-party services/solutions.
 
 .. tip::
-	For non-sensitive configuration values, we recommend using :ref:`plain-text Environment Variables <environment_variables>`.
+    For non-sensitive configuration values, we recommend using :ref:`plain-text Environment Variables <environment_variables>`.
 
 ************
 Add a secret

docs/source-app/glossary/sharing_components.rst

@@ -34,7 +34,7 @@ Now, imagine you have implemented a **KerasScriptRunner** component for training
 
 Here are the best practices steps before sharing the component:
 
-* **Testing**: Ensure your component is well tested by following the ref:`../testing` guide.
+* **Testing**: Ensure your component is well tested by following the :doc:`../testing` guide.
 * **Documented**: Ensure your component has a docstring and comes with some usage explications.
 
 .. Note:: As a Lightning user, it helps to implement your components thinking someone else is going to use them.

docs/source-app/workflows/access_app_state.rst

@@ -50,10 +50,10 @@ And here's the output you get when running the App using **Lightning CLI**:
 
 .. code-block:: console
 
-	INFO: Your app has started. View it in your browser: http://127.0.0.1:7501/view
-	State: {'works': {'w': {'vars': {'counter': 1}}}}
-	State: {'works': {'w': {'vars': {'counter': 2}}}}
-	State: {'works': {'w': {'vars': {'counter': 3}}}}
-	State: {'works': {'w': {'vars': {'counter': 3}}}}
-	State: {'works': {'w': {'vars': {'counter': 4}}}}
-	...
+    INFO: Your app has started. View it in your browser: http://127.0.0.1:7501/view
+    State: {'works': {'w': {'vars': {'counter': 1}}}}
+    State: {'works': {'w': {'vars': {'counter': 2}}}}
+    State: {'works': {'w': {'vars': {'counter': 3}}}}
+    State: {'works': {'w': {'vars': {'counter': 3}}}}
+    State: {'works': {'w': {'vars': {'counter': 4}}}}
+    ...

docs/source-app/workflows/add_web_ui/react/communicate_between_react_and_lightning.rst

@@ -47,7 +47,7 @@ Update React <-- Lightning app
 ******************************
 To change the React app from the Lightning app, use the values from the `lightningState`.
 
-In this example, when the `react_ui.counter`` increaes in the Lightning app:
+In this example, when the ``react_ui.counter`` increaes in the Lightning app:
 
 .. literalinclude:: ../../../../../src/lightning/app/cli/react-ui-template/example_app.py
     :emphasize-lines: 18, 24

docs/source-pytorch/advanced/post_training_quantization.rst

@@ -55,8 +55,8 @@ Usage
 
 Minor code changes are required for the user to get started with Intel® Neural Compressor quantization API. To construct the quantization process, users can specify the below settings via the Python code:
 
-1.	Calibration Dataloader (Needed for post-training static quantization)
-2.	Evaluation Dataloader and Metric
+1. Calibration Dataloader (Needed for post-training static quantization)
+2. Evaluation Dataloader and Metric
 
 The code changes that are required for Intel® Neural Compressor are highlighted with comments in the line above.
 

docs/source-pytorch/data/alternatives.rst

@@ -32,8 +32,8 @@ As datasets grow in size and the number of nodes scales, loading training data c
 The `StreamingDataset <https://github.com/mosaicml/streaming>`__ can make training on large datasets from cloud storage
 as fast, cheap, and scalable as possible.
 
-This library uses a custom built class:`~torch.utils.data.IterableDataset`. The library recommends iterating through it
-via a regular class:`~torch.utils.data.DataLoader`. This means that support in the ``Trainer`` is seamless:
+This library uses a custom built :class:`~torch.utils.data.IterableDataset`. The library recommends iterating through it
+via a regular :class:`~torch.utils.data.DataLoader`. This means that support in the ``Trainer`` is seamless:
 
 .. code-block:: python