Fix pre-commit warnings

.github/workflows/formatter.yml

@@ -14,12 +14,8 @@ jobs:
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v4
         with:
-          python-version: 3.9
-      - name: black formatter
-        uses: rickstaa/action-black@v1
-        with:
-          black_args: ". --check --diff --skip-string-normalization --line-length 120"
+          python-version: 3.11
       - name: isort formatter
         uses: isort/isort-action@v1
         with:
-          configuration: "--profile black --src tafrigh --line-length 120 --lines-between-types 1 --lines-after-imports 2 --case-sensitive --trailing-comma --check-only --diff"
+          configuration: "--src src --line-length 120 --lines-between-types 1 --lines-after-imports 2 --check-only --diff"

pyproject.toml

@@ -23,7 +23,7 @@ homepage = "https://tafrigh.ieasybooks.com"
 repository = "https://github.com/ieasybooks/tafrigh"
 
 [tool.poetry.dependencies]
-python = ">=3.10,<3.12"
+python = "3.11"
 tqdm = ">=4.66.4"
 yt-dlp = ">=2024.4.9"
 auditok = {version = ">=0.2.0", extras = ["wit"]}

src/__init__.py

@@ -1,12 +1,12 @@
 __all__ = [
-    "farrigh",
-    "Config",
-    "Downloader",
-    "TranscriptType",
-    "Writer",
-    "WhisperRecognizer",
-    "AudioSplitter",
-    "WitRecognizer",
+  'farrigh',
+  'Config',
+  'Downloader',
+  'TranscriptType',
+  'Writer',
+  'WhisperRecognizer',
+  'AudioSplitter',
+  'WitRecognizer',
 ]
 
 
@@ -18,12 +18,12 @@
 
 
 try:
-    from .recognizers.whisper_recognizer import WhisperRecognizer
+  from .recognizers.whisper_recognizer import WhisperRecognizer
 except ModuleNotFoundError:
-    pass
+  pass
 
 try:
-    from .audio_splitter import AudioSplitter
-    from .recognizers.wit_recognizer import WitRecognizer
+  from .audio_splitter import AudioSplitter
+  from .recognizers.wit_recognizer import WitRecognizer
 except ModuleNotFoundError:
-    pass
+  pass

src/audio_splitter.py

@@ -7,71 +7,71 @@
 
 
 class AudioSplitter:
-    def split(
-        self,
-        file_path: str,
-        output_dir: str,
-        min_dur: float = 0.5,
-        max_dur: float = 15,
-        max_silence: float = 0.5,
-        energy_threshold: float = 50,
-        expand_segments_with_noise: bool = False,
-        noise_seconds: int = 1,
-        noise_amplitude: int = 0,
-    ) -> list[tuple[str, float, float]]:
-        segments = split(
-            file_path,
-            min_dur=min_dur,
-            max_dur=max_dur,
-            max_silence=max_silence,
-            energy_threshold=energy_threshold,
-        )
+  def split(
+    self,
+    file_path: str,
+    output_dir: str,
+    min_dur: float = 0.5,
+    max_dur: float = 15,
+    max_silence: float = 0.5,
+    energy_threshold: float = 50,
+    expand_segments_with_noise: bool = False,
+    noise_seconds: int = 1,
+    noise_amplitude: int = 0,
+  ) -> list[tuple[str, float, float]]:
+    segments = split(
+      file_path,
+      min_dur=min_dur,
+      max_dur=max_dur,
+      max_silence=max_silence,
+      energy_threshold=energy_threshold,
+    )
 
-        if expand_segments_with_noise:
-            segments = [
-                (
-                    self._expand_segment_with_noise(segment, noise_seconds, noise_amplitude),
-                    segment.meta.start,
-                    segment.meta.end,
-                ) for segment in segments
-            ]
+    if expand_segments_with_noise:
+      segments = [
+        (
+          self._expand_segment_with_noise(segment, noise_seconds, noise_amplitude),
+          segment.meta.start,
+          segment.meta.end,
+        ) for segment in segments
+      ]
 
-        return self._save_segments(output_dir, segments)
+    return self._save_segments(output_dir, segments)
 
-    def _expand_segment_with_noise(
-        self,
-        segment: AudioRegion,
-        noise_seconds: int,
-        noise_amplitude: int,
-    ) -> AudioSegment:
+  def _expand_segment_with_noise(
+    self,
+    segment: AudioRegion,
+    noise_seconds: int,
+    noise_amplitude: int,
+  ) -> AudioSegment:
 
-        audio_segment = AudioSegment(
-            segment._data, 
-            frame_rate=segment.sampling_rate, 
-            sample_width=segment.sample_width, 
-            channels=segment.channels,
-        )
+    audio_segment = AudioSegment(
+      segment._data,
+      frame_rate=segment.sampling_rate,
+      sample_width=segment.sample_width,
+      channels=segment.channels,
+    )
 
-        pre_noise = WhiteNoise().to_audio_segment(duration=noise_seconds * 1000, volume=noise_amplitude)
-        post_noise = WhiteNoise().to_audio_segment(duration=noise_seconds * 1000, volume=noise_amplitude)
+    pre_noise = WhiteNoise().to_audio_segment(duration=noise_seconds * 1000, volume=noise_amplitude)
+    post_noise = WhiteNoise().to_audio_segment(duration=noise_seconds * 1000, volume=noise_amplitude)
 
-        return pre_noise + audio_segment + post_noise
+    return pre_noise + audio_segment + post_noise
 
-    def _save_segments(
-        self,
-        output_dir: str,
-        segments: list[AudioSegment | tuple[AudioSegment, float, float]],
-    ) -> list[tuple[str, float, float]]:
-        segment_paths = []
+  def _save_segments(
+    self,
+    output_dir: str,
+    segments: list[AudioSegment | tuple[AudioSegment, float, float]],
+  ) -> list[tuple[str, float, float]]:
+    segment_paths = []
 
-        for i, segment in enumerate(segments):
-            output_file = os.path.join(output_dir, f'segment_{i + 1}.mp3')
+    for i, segment in enumerate(segments):
+      output_file = os.path.join(output_dir, f'segment_{i + 1}.mp3')
 
-            if isinstance(segment, tuple):
-                segment[0].export(output_file, format='mp3')
-                segment_paths.append((output_file, segment[1], segment[2]))
-            else:
-                segment.save(output_file)
-                segment_paths.append((output_file, segment.meta.start, segment.meta.end))
-            
-        return segment_paths
+      if isinstance(segment, tuple):
+        segment[0].export(output_file, format='mp3')
+        segment_paths.append((output_file, segment[1], segment[2]))
+      else:
+        segment.save(output_file)
+        segment_paths.append((output_file, segment.meta.start, segment.meta.end))
+
+    return segment_paths