[docs] Format md code blocks for new ruff 0.16

Author: Breakthrough

.github/ISSUE_TEMPLATE/scenedetect_package.md

@@ -14,8 +14,9 @@ Include code samples that demonstrate the issue:
 
 ```python
 from scenedetect import detect, ContentDetector, split_video_ffmpeg
-scene_list = detect('my_video.mp4', ContentDetector())
-split_video_ffmpeg('my_video.mp4', scene_list)
+
+scene_list = detect("my_video.mp4", ContentDetector())
+split_video_ffmpeg("my_video.mp4", scene_list)
 ```
 
 **Environment:**

README.md

@@ -61,7 +61,8 @@ To get started, there is a high level function in the library that performs cont
 
 ```python
 from scenedetect import detect, ContentDetector
-scene_list = detect('my_video.mp4', ContentDetector())
+
+scene_list = detect("my_video.mp4", ContentDetector())
 ```
 
 `scene_list` will now be a list containing the start/end times of all scenes found in the video.  There also exists a two-pass version `AdaptiveDetector` which handles fast camera movement better, and `ThresholdDetector` for handling fade out/fade in events.
@@ -70,20 +71,28 @@ Try calling `print(scene_list)`, or iterating over each scene:
 
 ```python
 from scenedetect import detect, ContentDetector
-scene_list = detect('my_video.mp4', ContentDetector())
+
+scene_list = detect("my_video.mp4", ContentDetector())
 for i, scene in enumerate(scene_list):
-    print('    Scene %2d: Start %s / Frame %d, End %s / Frame %d' % (
-        i+1,
-        scene[0].get_timecode(), scene[0].frame_num,
-        scene[1].get_timecode(), scene[1].frame_num,))
+    print(
+        "    Scene %2d: Start %s / Frame %d, End %s / Frame %d"
+        % (
+            i + 1,
+            scene[0].get_timecode(),
+            scene[0].frame_num,
+            scene[1].get_timecode(),
+            scene[1].frame_num,
+        )
+    )
 ```
 
 We can also split the video into each scene if `ffmpeg` is installed (`mkvmerge` is also supported):
 
 ```python
 from scenedetect import detect, ContentDetector, split_video_ffmpeg
-scene_list = detect('my_video.mp4', ContentDetector())
-split_video_ffmpeg('my_video.mp4', scene_list)
+
+scene_list = detect("my_video.mp4", ContentDetector())
+split_video_ffmpeg("my_video.mp4", scene_list)
 ```
 
 For more advanced usage, the API is highly configurable, and can easily integrate with any pipeline. This includes using different detection algorithms, splitting the input video, and much more. The following example shows how to implement a function similar to the above, but using [the `scenedetect` API](https://www.scenedetect.com/docs/latest/api.html):
@@ -93,12 +102,12 @@ from scenedetect import open_video, SceneManager, split_video_ffmpeg
 from scenedetect.detectors import ContentDetector
 from scenedetect.video_splitter import split_video_ffmpeg
 
+
 def split_video_into_scenes(video_path, threshold=27.0):
     # Open our video, create a scene manager, and add a detector.
     video = open_video(video_path)
     scene_manager = SceneManager()
-    scene_manager.add_detector(
-        ContentDetector(threshold=threshold))
+    scene_manager.add_detector(ContentDetector(threshold=threshold))
     scene_manager.detect_scenes(video, show_progress=True)
     scene_list = scene_manager.get_scene_list()
     split_video_ffmpeg(video_path, scene_list, show_progress=True)

website/pages/api.md

@@ -45,6 +45,7 @@ import typing as ty
 import numpy as np
 from scenedetect import FrameTimecode, SceneDetector
 
+
 class CustomDetector(SceneDetector):
     """CustomDetector class to implement a scene detection algorithm."""
 

website/pages/index.md

@@ -21,8 +21,9 @@ Split video on each fast cut using [Python API (docs)](docs.md):
 
 ```python
 from scenedetect import detect, AdaptiveDetector, split_video_ffmpeg
-scene_list = detect('my_video.mp4', AdaptiveDetector())
-split_video_ffmpeg('my_video.mp4', scene_list)
+
+scene_list = detect("my_video.mp4", AdaptiveDetector())
+split_video_ffmpeg("my_video.mp4", scene_list)
 ```