Enable rules for excessive complexity, ignoring existing errors

bats_ai/core/management/commands/copy_recordings.py

@@ -151,7 +151,7 @@ def add_arguments(self, parser):
             ),
         )
 
-    def handle(self, *args, **options):
+    def handle(self, *args, **options):  # noqa: C901, PLR0912, PLR0915
         count = options["count"]
         tags_raw = options["tags"] or ",".join(DEFAULT_TAGS)
         tag_texts = [t.strip() for t in tags_raw.split(",") if t.strip()]

bats_ai/core/management/commands/importRecordings.py

@@ -55,7 +55,7 @@ def add_arguments(self, parser):
             ),
         )
 
-    def handle(self, *args, **options):
+    def handle(self, *args, **options):  # noqa: C901, PLR0912, PLR0915
         directory_path = Path(options["directory"])
         owner_username = options.get("owner")
         is_public = options.get("public", False)

bats_ai/core/management/commands/loadGRTS.py

@@ -65,7 +65,7 @@ def _download_file(self, url: str, zip_path: Path) -> None:
         with zip_path.open("wb") as f:
             f.write(response.content)
 
-    def handle(self, *args, **options):
+    def handle(self, *args, **options):  # noqa: C901, PLR0912, PLR0915
         batch_size = options["batch_size"]
 
         # Track existing IDs to avoid duplicates

bats_ai/core/management/commands/load_public_dataset.py

@@ -108,7 +108,7 @@ def _try_start_spectrogram_generation(recording_id: int):
         recording_compute_spectrogram.delay(recording_id)
 
 
-def _ingest_files_from_manifest(
+def _ingest_files_from_manifest(  # noqa: C901, PLR0912, PLR0913, PLR0915
     *,
     s3_client,
     bucket: str,

bats_ai/core/management/commands/load_species_geojson.py

@@ -32,7 +32,7 @@ def add_arguments(self, parser):
             help="Delete all SpeciesRange rows before loading.",
         )
 
-    def handle(self, *args, **options):
+    def handle(self, *args, **options):  # noqa: C901
         path = Path(options["geojson_path"] or DEFAULT_GEOJSON).resolve()
         if not path.is_file():
             raise CommandError(f"GeoJSON file not found: {path}")

bats_ai/core/tasks/export_task.py

@@ -75,7 +75,7 @@ def annotation_to_dict(
     return data
 
 
-def write_csv_and_json(
+def write_csv_and_json(  # noqa: PLR0913
     zipf,
     name_prefix,
     queryset,

bats_ai/core/tasks/nabat/tasks.py

@@ -22,7 +22,7 @@
 logger = logging.getLogger("NABatDataRetrieval")
 
 
-def generate_spectrograms(
+def generate_spectrograms(  # noqa: C901, PLR0915
     self, nabat_recording: NABatRecording, presigned_url: str, processing_task: ProcessingTask
 ):
     from bats_ai.core.utils.batbot_metadata import generate_spectrogram_assets

bats_ai/core/tasks/tasks.py

@@ -27,7 +27,7 @@
 
 
 @app.task(bind=True)
-def recording_compute_spectrogram(self, recording_id: int):
+def recording_compute_spectrogram(self, recording_id: int):  # noqa: C901, PLR0912, PLR0915
     from bats_ai.core.utils.batbot_metadata import generate_spectrogram_assets
 
     celery_id = getattr(self.request, "id", None)

bats_ai/core/utils/contour_utils.py

@@ -86,7 +86,7 @@ def auto_histogram_levels(
     return groups
 
 
-def compute_auto_levels(
+def compute_auto_levels(  # noqa: PLR0913
     data: npt.NDArray,
     mode: str,
     percentile_values,
@@ -227,7 +227,7 @@ def apply_transparency_mask(mat, threshold_percent):
 # -----------------------------------------------------------------------------
 
 
-def extract_contours(
+def extract_contours(  # noqa: PLR0913
     image_path: Path,
     *,
     levels_mode: str,
@@ -277,7 +277,7 @@ def extract_contours(
     return sorted(contours, key=lambda x: x[1]), img.shape
 
 
-def process_spectrogram_assets_for_contours(
+def process_spectrogram_assets_for_contours(  # noqa: C901, PLR0913
     assets: dict[str, Any],
     *,
     levels_mode: str = "percentile",

bats_ai/core/utils/guano_utils.py

@@ -86,7 +86,7 @@ def extract_metadata_from_filename(filename: str) -> dict:
     return metadata
 
 
-def extract_guano_metadata(file_path: str | Path, *, check_filename: bool = False) -> dict:
+def extract_guano_metadata(file_path: str | Path, *, check_filename: bool = False) -> dict:  # noqa: C901
     """Extract GUANO metadata from a WAV file.
 
     Args:

bats_ai/core/views/nabat/nabat_recording.py

@@ -82,7 +82,7 @@ def decode_jwt(token):
     return json.loads(decoded_str)
 
 
-def get_email_if_authorized(
+def get_email_if_authorized(  # noqa: PLR0911
     request: HttpRequest,
     api_token: str,
     recording_id: int | None = None,
@@ -196,7 +196,7 @@ def update_nabat_species(species_id: int, api_token: str, recording_id: int, sur
 
 
 @router.post("/", auth=None)
-def generate_nabat_recording(
+def generate_nabat_recording(  # noqa: PLR0911
     request: HttpRequest,
     payload: Form[NABatRecordingGenerateSchema],
 ):

bats_ai/core/views/recording.py

@@ -351,7 +351,7 @@ def create_recording(
 
 
 @router.patch("/{pk}")
-def update_recording(request: HttpRequest, pk: int, recording_data: RecordingUploadSchema):
+def update_recording(request: HttpRequest, pk: int, recording_data: RecordingUploadSchema):  # noqa: C901, PLR0912
     try:
         recording = Recording.objects.get(pk=pk, owner=request.user)
     except Recording.DoesNotExist:
@@ -484,7 +484,7 @@ def delete_recording(
 
 
 @router.get("/", response=RecordingPaginatedResponse)
-def get_recordings(
+def get_recordings(  # noqa: C901
     request: HttpRequest,
     q: Query[RecordingListQuerySchema],
 ):
@@ -1085,7 +1085,7 @@ def put_annotation(
 
 
 @router.patch("/{recording_pk}/annotations/{annotation_pk}")
-def patch_annotation(
+def patch_annotation(  # noqa: C901, PLR0912
     request,
     recording_pk: int,
     annotation_pk: int,
@@ -1168,10 +1168,7 @@ def patch_sequence_annotation(
                 annotation_instance.end_time = annotation.end_time
             if annotation.comments:
                 annotation_instance.comments = annotation.comments
-            if annotation.type:
-                annotation_instance.type = annotation.type
-            else:
-                annotation_instance.type = None
+            annotation_instance.type = annotation.type or None
             annotation_instance.save()
 
             # Clear existing species associations

bats_ai/core/views/recording_location.py

@@ -62,7 +62,7 @@ def _split_tags(tags: str | None) -> list[str]:
     return [t.strip() for t in tags.split(",") if t.strip()]
 
 
-def _apply_recording_filters_and_sort(
+def _apply_recording_filters_and_sort(  # noqa: PLR0913
     *,
     qs: QuerySet[Recording],
     exclude_submitted: bool,

pyproject.toml

@@ -157,15 +157,10 @@ ignore = [
 
   # Project-specific
   "BLE001", # blind-except
-  "C901", # complex-structure
   "DJ001", # django-nullable-model-string-field
   "N815", # mixed-case-variable-in-class-scope
   "N999", # invalid-module-name
   "PLC0415", # import-outside-top-level
-  "PLR0911", # too-many-return-statements
-  "PLR0912", # too-many-branches
-  "PLR0913", # too-many-arguments
-  "PLR0915", # too-many-statements
   "PLW2901", # redefined-loop-name
   "PTH", # flake8-use-pathlib
   "S110", # try-except-pass

scripts/contours/extract_contours.py

@@ -98,7 +98,7 @@ def auto_histogram_levels(
     return groups
 
 
-def compute_auto_levels(
+def compute_auto_levels(  # noqa: PLR0913
     data: np.ndarray,
     mode: str,
     percentile_values,
@@ -315,7 +315,7 @@ def apply_transparency_mask(mat, threshold_percent):
 # -----------------------------------------------------------------------------
 
 
-def extract_contours(
+def extract_contours(  # noqa: PLR0913
     image_path: Path,
     *,
     output_path: Path | None = None,
@@ -410,7 +410,7 @@ def extract_contours(
     is_flag=True,
     help="Save debug images (filtered and unfiltered) to the output directory",
 )
-def main(input_path: str, out_dir, verbose, debug_images, **kwargs):
+def main(input_path: str, out_dir, verbose, debug_images, **kwargs):  # noqa: C901, PLR0912, PLR0915
     logging.basicConfig(level=logging.INFO if verbose else logging.WARNING)
 
     out_dir = Path(out_dir)

scripts/generateSpectrograms.py

@@ -21,7 +21,7 @@
 COLORMAP_ALLOWED = [None, "gist_yarg", "turbo"]
 
 
-def generate_spectrogram(wav_path, output_folder, colormap=None):
+def generate_spectrogram(wav_path, output_folder, colormap=None):  # noqa: C901, PLR0915
     try:
         sig, sr = librosa.load(wav_path, sr=None)
         duration = len(sig) / sr

scripts/synthetic/waveGenerator.py

@@ -155,7 +155,7 @@ def generate_spectrogram(wav_path, output_path, colormap="turbo"):
         return None, None
 
 
-def generate_compressed(img_path, duration, annotation_path, output_path):
+def generate_compressed(img_path, duration, annotation_path, output_path):  # noqa: C901
     try:
         img = np.array(Image.open(img_path))
         canvas = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY).astype(np.float32)