[refactor] apply suggestion from sonarlint

src/app.py

@@ -29,9 +29,9 @@ def lambda_handler(event: dict, context: LambdaContext):
         app_logger.info(f"event version: {event['version']}.")
 
     try:
-        app_logger.info(f"try get_parsed_event...")
+        app_logger.info("try get_parsed_event...")
         request_input = get_parsed_request_body(event)
-        app_logger.info(f"event parsed: ok")
+        app_logger.info("event parsed: ok")
         body_request = get_parsed_bbox_points(request_input)
 
         try:

src/io/geo_helpers.py

@@ -61,7 +61,7 @@ def get_vectorized_raster_as_geojson(mask: np.ndarray, matrix: Tuple[float]) ->
         transform = get_affine_transform_from_gdal(matrix)
         app_logger.info(f"transform to consume with rasterio.shapes: {type(transform)}, {transform}.")
 
-        # mask = band != 0
+        # old value for mask => band != 0
         shapes_generator = ({
             'properties': {'raster_val': v}, 'geometry': s}
             for i, (s, v)
@@ -69,13 +69,13 @@ def get_vectorized_raster_as_geojson(mask: np.ndarray, matrix: Tuple[float]) ->
             # use mask=None to avoid using source
             in enumerate(shapes(mask, mask=None, transform=transform))
         )
-        app_logger.info(f"created shapes_generator, transform it to a polygon list...")
+        app_logger.info("created shapes_generator, transform it to a polygon list...")
         shapes_list = list(shapes_generator)
         app_logger.info(f"created {len(shapes_list)} polygons.")
         gpd_polygonized_raster = GeoDataFrame.from_features(shapes_list, crs="EPSG:3857")
-        app_logger.info(f"created a GeoDataFrame, export to geojson...")
+        app_logger.info("created a GeoDataFrame, export to geojson...")
         geojson = gpd_polygonized_raster.to_json(to_wgs84=True)
-        app_logger.info(f"created geojson, preparing API response...")
+        app_logger.info("created geojson, preparing API response...")
         return {
             "geojson": geojson,
             "n_shapes_geojson": len(shapes_list)

src/io/lambda_helpers.py

@@ -80,7 +80,7 @@ def get_parsed_bbox_points(request_input: RawRequestInput) -> Dict:
     app_logger.debug(f"bbox => {bbox}.")
     app_logger.debug(f'request_input-prompt updated => {new_prompt_list}.')
 
-    app_logger.info(f"unpacking elaborated request...")
+    app_logger.info("unpacking elaborated request...")
     return {
         "bbox": [ne_latlng, sw_latlng],
         "prompt": new_prompt_list,

src/prediction_api/sam_onnx.py

@@ -175,7 +175,6 @@ class SegmentAnythingONNX:
                         app_logger.debug(f"mask_shape transform_masks:{mask.shape}, dtype:{mask.dtype}.")
                     except Exception as e_mask_shape_transform_masks:
                         app_logger.error(f"e_mask_shape_transform_masks:{e_mask_shape_transform_masks}.")
-                        # raise e_mask_shape_transform_masks
                     mask = cv2.warpAffine(
                         mask,
                         transform_matrix[:2],

tests/io/test_tms2geotiff.py

@@ -1,3 +1,4 @@
+import logging
 import unittest
 
 import numpy as np
@@ -28,7 +29,7 @@ class TestTms2geotiff(unittest.TestCase):
         )
         server_thread = Thread(target=server.serve_forever, name="http_server")
         server_thread.start()
-        print(f"listen:: host {host}, port {port}.")
+        logging.info(f"listen:: host {host}, port {port}.")
 
         try:
             yield
@@ -49,6 +50,7 @@ class TestTms2geotiff(unittest.TestCase):
             np_img = np.array(img)
             output_hash = hash_calculate(np_img)
             assert output_hash == b'LJNhEuMMp2nRclFJfF6oM3iMVbnZnWDmZqWzrs3T4Hs='
+            assert matrix == (1628916.673269823, 76.42413122132838, 0, 4584983.258896411, 0, -76.45836079647981)
 
     def test_download_extent_io_error1(self):
 
@@ -91,9 +93,7 @@ if __name__ == '__main__':
     from tests import TEST_ROOT_FOLDER
 
     main_listen_port = 8000
-    print("http_basedir_serve:", TEST_ROOT_FOLDER, "#")
+    logging.info(f"http_basedir_serve: {TEST_ROOT_FOLDER}.")
     with TestTms2geotiff.http_server("127.0.0.1", main_listen_port, directory=TEST_ROOT_FOLDER):
-        pass
-        # import time
-        # time.sleep(10)
-    print("Http server stopped.")
+        logging.info("""import time; time.sleep(10)""")
+    logging.info("Http server stopped.")

tests/prediction_api/test_sam_onnx.py

@@ -1,11 +1,9 @@
 import logging
 import unittest
-from unittest.mock import patch
 
 import numpy as np
 
 from src import MODEL_FOLDER
-from src.prediction_api import sam_onnx
 from src.prediction_api.sam_onnx import SegmentAnythingONNX
 from src.utilities.constants import MODEL_ENCODER_NAME, MODEL_DECODER_NAME
 from src.utilities.utilities import hash_calculate
@@ -58,15 +56,12 @@ class TestSegmentAnythingONNX(unittest.TestCase):
         try:
             assert 1 not in perc
         except AssertionError:
-            logging.error(f"found {perc[1]} % different pixels between expected masks and output mask.")
+            n_pixels = perc[1]
+            logging.error(f"found {n_pixels:.2%} different pixels between expected masks and output mask.")
             # try to assert that the % of different pixels are minor than 5%
             assert perc[1] < 5
 
     def test_encode_predict_masks_ex1(self):
-        instance_sam_onnx = SegmentAnythingONNX(
-            encoder_model_path=MODEL_FOLDER / MODEL_ENCODER_NAME,
-            decoder_model_path=MODEL_FOLDER / MODEL_DECODER_NAME
-        )
         with self.assertRaises(Exception):
             try:
                 np_input = np.zeros((10, 10))