Import cleanup

AGENTS.md

@@ -56,14 +56,16 @@ deleting that directory is how you test a first-run experience.
 
 ## Conventions that are easy to get wrong
 
-- **The GUI test environment has no pywebview and no plotly** — `gui-tests` installs
-  gradio, both others are `gui`-only. So no GUI module may import `webview` or
-  `plotly` at module import time: `gui/utils.py` imports `webview` inside the dialog
-  functions and `open_window` only, and its `_WINDOW` annotation is a string under
-  `TYPE_CHECKING`. The tests import `gui.utils` unstubbed on purpose. A test that
-  builds species-list controls must stub `gu.plot_map_scatter_mapbox` (it draws a
-  plotly map). A local venv with the `gui` extra hides both problems, so run GUI
-  tests once with `webview`/`plotly` made unimportable before pushing.
+- **The GUI test environment has no pywebview, no plotly and no pywin32** —
+  `gui-tests` installs gradio only, the others are `gui`-only, and pywin32 is
+  imported in one place, inside `_get_network_shortcuts`. So no GUI module may
+  import `webview` or `plotly` at module import time: `gui/utils.py` imports
+  `webview` inside the dialog functions and `open_window` only, and its `_WINDOW`
+  annotation is a string under `TYPE_CHECKING`. The tests import `gui.utils`
+  unstubbed on purpose. A test that builds species-list controls must stub
+  `gu.plot_map_scatter_mapbox` (it draws a plotly map). A local venv with the `gui`
+  extra hides these problems, so run GUI tests once with `webview`, `plotly`,
+  `pythoncom` and `win32com` made unimportable before pushing.
 - **Localization is all-or-nothing.** `lang/*.json` holds one file per language. A
   new UI string has to be added to *every* file with a real translation — not the
   English text copied over. Write them with a json load/dump round-trip

birdnet_analyzer/__init__.py

@@ -1,6 +1,4 @@
 import logging
-import os
-import warnings
 
 from birdnet_analyzer.settings import apply_model_directory
 
@@ -21,7 +19,3 @@
 
 __version__ = "2.4.0"
 __all__ = ["analyze", "embeddings", "search", "segments", "species", "train"]
-os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
-os.environ["WRAPT_DISABLE_EXTENSIONS"] = "true"
-
-warnings.filterwarnings("ignore")

birdnet_analyzer/gui/__init__.py

@@ -1,4 +1,5 @@
 def main():
+    import birdnet_analyzer.gui.localization as loc
     import birdnet_analyzer.gui.multi_file as mfa
     import birdnet_analyzer.gui.segments as gs
     import birdnet_analyzer.gui.single_file as sfa
@@ -12,8 +13,11 @@ def main():
         train,
     )
     from birdnet_analyzer.logs import setup_logging
+    from birdnet_analyzer.utils import configure_runtime
 
     setup_logging()
+    configure_runtime()
+    loc.load_local_state()
     gu.open_window(
         [
             sfa.build_single_analysis_tab,

birdnet_analyzer/gui/localization.py

@@ -5,11 +5,26 @@
 
 from birdnet_analyzer import settings
 
-LANGUAGE_LOOKUP = {}
-TARGET_LANGUAGE = settings.FALLBACK_LANGUAGE
 logger = logging.getLogger(__name__)
 
 
+def available_languages() -> list[str]:
+    """The ids of the languages the GUI has a language file for, sorted."""
+    return sorted(file.stem for file in Path(settings.LANG_DIR).glob("*.json"))
+
+
+def _read_language_file(language: str) -> dict:
+    if language not in available_languages():
+        raise ValueError(f"Unknown language {language!r}")
+
+    with open(f"{settings.LANG_DIR}/{language}.json", encoding="utf-8") as f:
+        return json.load(f)
+
+
+TARGET_LANGUAGE = settings.FALLBACK_LANGUAGE
+LANGUAGE_LOOKUP = _read_language_file(TARGET_LANGUAGE)
+
+
 def load_local_state():
     """
     Loads the local language settings and populates the LANGUAGE_LOOKUP dictionary with
@@ -35,19 +50,6 @@ def load_local_state():
         LANGUAGE_LOOKUP = fallback | LANGUAGE_LOOKUP
 
 
-def available_languages() -> list[str]:
-    """The ids of the languages the GUI has a language file for, sorted."""
-    return sorted(file.stem for file in Path(settings.LANG_DIR).glob("*.json"))
-
-
-def _read_language_file(language: str) -> dict:
-    if language not in available_languages():
-        raise ValueError(f"Unknown language {language!r}")
-
-    with open(f"{settings.LANG_DIR}/{language}.json", encoding="utf-8") as f:
-        return json.load(f)
-
-
 def localize(key: str) -> str:
     """
     Translates a given key into its corresponding localized string.

birdnet_analyzer/gui/single_file.py

@@ -17,11 +17,24 @@
 
 MATPLOTLIB_FIGURE_NUM = "single-file-tab-spectrogram-plot"
 MAX_TABLE_ROWS = 50
-HEADER_START_LBL = loc.localize("single-tab-output-header-start")
-HEADER_END_LBL = loc.localize("single-tab-output-header-end")
-HEADER_SCI_NAME_LBL = loc.localize("single-tab-output-header-sci-name")
-HEADER_COMMON_NAME_LBL = loc.localize("single-tab-output-header-common-name")
-HEADER_CONFIDENCE_LBL = loc.localize("single-tab-output-header-confidence")
+_HEADER_LABELS = {
+    "HEADER_START_LBL": "single-tab-output-header-start",
+    "HEADER_END_LBL": "single-tab-output-header-end",
+    "HEADER_SCI_NAME_LBL": "single-tab-output-header-sci-name",
+    "HEADER_COMMON_NAME_LBL": "single-tab-output-header-common-name",
+    "HEADER_CONFIDENCE_LBL": "single-tab-output-header-confidence",
+}
+
+
+def _header_labels() -> list[str]:
+    return [loc.localize(key) for key in _HEADER_LABELS.values()]
+
+
+def __getattr__(name: str) -> str:
+    if name in _HEADER_LABELS:
+        return loc.localize(_HEADER_LABELS[name])
+
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
 
 
 @gu.gui_runtime_error_handler
@@ -109,41 +122,40 @@ def convert_to_time_str(seconds: float) -> str:
         )
 
     n_rows = table.shape[0]
+    start_lbl, end_lbl, sci_name_lbl, common_name_lbl, confidence_lbl = _header_labels()
 
     if n_rows > 0:
         split_species = table["species_name"].str.split("_", n=1, expand=True)
-        table[HEADER_SCI_NAME_LBL] = split_species[0]
-        table[HEADER_COMMON_NAME_LBL] = (
+        table[sci_name_lbl] = split_species[0]
+        table[common_name_lbl] = (
             split_species[1] if len(split_species.columns) > 1 else ""
         )
     else:
-        table[HEADER_SCI_NAME_LBL] = []
-        table[HEADER_COMMON_NAME_LBL] = []
+        table[sci_name_lbl] = []
+        table[common_name_lbl] = []
 
     table[" "] = ["▶"] * n_rows
     table.rename(
         columns={
-            "start_time": HEADER_START_LBL,
-            "end_time": HEADER_END_LBL,
-            "confidence": HEADER_CONFIDENCE_LBL,
+            "start_time": start_lbl,
+            "end_time": end_lbl,
+            "confidence": confidence_lbl,
         },
         inplace=True,
     )
-    table[HEADER_START_LBL] = table[HEADER_START_LBL].apply(convert_to_time_str)
-    table[HEADER_END_LBL] = table[HEADER_END_LBL].apply(convert_to_time_str)
+    table[start_lbl] = table[start_lbl].apply(convert_to_time_str)
+    table[end_lbl] = table[end_lbl].apply(convert_to_time_str)
     table = table[
         [
             " ",
-            HEADER_START_LBL,
-            HEADER_END_LBL,
-            HEADER_SCI_NAME_LBL,
-            HEADER_COMMON_NAME_LBL,
-            HEADER_CONFIDENCE_LBL,
+            start_lbl,
+            end_lbl,
+            sci_name_lbl,
+            common_name_lbl,
+            confidence_lbl,
         ]
     ]
-    table[HEADER_CONFIDENCE_LBL] = table[HEADER_CONFIDENCE_LBL].apply(
-        lambda x: f"{x:0.3f}"
-    )
+    table[confidence_lbl] = table[confidence_lbl].apply(lambda x: f"{x:0.3f}")
 
     return (
         table,
@@ -241,14 +253,7 @@ def build_single_analysis_tab() -> gu.TAB_BUILDER_RESULT:
 
         output_dataframe = gr.Dataframe(
             type="pandas",
-            headers=[
-                " ",
-                HEADER_START_LBL,
-                HEADER_END_LBL,
-                HEADER_SCI_NAME_LBL,
-                HEADER_COMMON_NAME_LBL,
-                HEADER_CONFIDENCE_LBL,
-            ],
+            headers=[" ", *_header_labels()],
             elem_id="single-file-output",
             interactive=False,
             buttons=[],

birdnet_analyzer/gui/utils.py

@@ -8,7 +8,6 @@
 import platform
 import sys
 import threading
-import warnings
 from collections.abc import Callable
 from contextlib import contextmanager, suppress
 from html import escape
@@ -26,16 +25,16 @@
 if TYPE_CHECKING:
     import webview
 
-warnings.filterwarnings("ignore")
-loc.load_local_state()
-
 logger = logging.getLogger(__name__)
 SCRIPT_DIR = os.path.abspath(os.path.dirname(__file__))
-CUSTOM_SPECIES = loc.localize("species-list-radio-option-custom-list")
-PREDICT_SPECIES = loc.localize("species-list-radio-option-predict-list")
-CUSTOM_CLASSIFIER = loc.localize("species-list-radio-option-custom-classifier")
-ALL_SPECIES = loc.localize("species-list-radio-option-all")
-USE_PERCH = loc.localize("species-list-radio-option-use-perch")
+# Localized on access, so they follow the language gui.main loads.
+_LOCALIZED_LABELS = {
+    "CUSTOM_SPECIES": "species-list-radio-option-custom-list",
+    "PREDICT_SPECIES": "species-list-radio-option-predict-list",
+    "CUSTOM_CLASSIFIER": "species-list-radio-option-custom-classifier",
+    "ALL_SPECIES": "species-list-radio-option-all",
+    "USE_PERCH": "species-list-radio-option-use-perch",
+}
 # BirdNET acoustic model choices. Not localized: the version number is the label.
 USE_BIRDNET_2_4 = "BirdNET 2.4"
 USE_BIRDNET_3_0 = "BirdNET 3.0"
@@ -84,6 +83,17 @@
 }
 
 
+def _label(name: str) -> str:
+    return loc.localize(_LOCALIZED_LABELS[name])
+
+
+def __getattr__(name: str) -> str:
+    if name in _LOCALIZED_LABELS:
+        return _label(name)
+
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+
+
 def is_birdnet_model(model_choice: str) -> bool:
     """Whether the selected model is an official BirdNET acoustic model."""
     return model_choice in _BIRDNET_MODEL_VERSIONS
@@ -98,14 +108,16 @@ def model_supports_sensitivity(model_choice: str) -> bool:
     """Whether the sensitivity slider applies to the selected model choice."""
     from birdnet_analyzer.model_utils import supports_sensitivity
 
-    return supports_sensitivity("perch" if model_choice == USE_PERCH else "birdnet")
+    return supports_sensitivity(
+        "perch" if model_choice == _label("USE_PERCH") else "birdnet"
+    )
 
 
 def _species_choices(is_perch: bool) -> list[str]:
     if is_perch:
-        return [ALL_SPECIES, CUSTOM_SPECIES]
+        return [_label("ALL_SPECIES"), _label("CUSTOM_SPECIES")]
 
-    return [ALL_SPECIES, CUSTOM_SPECIES, PREDICT_SPECIES]
+    return [_label("ALL_SPECIES"), _label("CUSTOM_SPECIES"), _label("PREDICT_SPECIES")]
 
 
 def _max_overlap(is_perch: bool) -> float:
@@ -782,10 +794,11 @@ def model_choices():
     """Returns the models that can be selected on the current platform."""
     birdnet_models = [label for label, _ in birdnet_model_choices()]
 
-    values = [*birdnet_models, CUSTOM_CLASSIFIER, USE_PERCH]
+    values = [*birdnet_models, _label("CUSTOM_CLASSIFIER"), _label("USE_PERCH")]
 
     if platform.system() == "Darwin":
-        values.remove(USE_PERCH)  # TODO: Remove when tf 2.21+ is available on macOS
+        # TODO: Remove when tf 2.21+ is available on macOS
+        values.remove(_label("USE_PERCH"))
 
     return values
 
@@ -803,7 +816,7 @@ def sample_species_model_settings(state: TabState, opened=True):
     model_choice = state.get(
         "model_selection_radio", default_model(), choices=model_choices()
     )
-    is_perch = model_choice == USE_PERCH
+    is_perch = model_choice == _label("USE_PERCH")
 
     sample_settings = sample_sliders(
         state,
@@ -815,7 +828,7 @@ def sample_species_model_settings(state: TabState, opened=True):
     model_settings = model_selection(state, opened=opened)
 
     def on_model_change(value, species_choice, overlap, current_locale):
-        is_perch = value == USE_PERCH
+        is_perch = value == _label("USE_PERCH")
         choices = _species_choices(is_perch)
         max_overlap = _max_overlap(is_perch)
         shown = {
@@ -828,7 +841,7 @@ def on_model_change(value, species_choice, overlap, current_locale):
         # Keep the current species selection (e.g. the one a preset was just
         # applied with) as long as the new model offers it.
         if species_choice not in choices:
-            fitted["species_list_radio"] = ALL_SPECIES
+            fitted["species_list_radio"] = _label("ALL_SPECIES")
 
         if model_supports_sensitivity(value):
             sensitivity_update = gr.update(
@@ -1285,13 +1298,13 @@ def show_species_choice(choice: str, file_input):
             Column update,
         ]
     """
-    if choice == CUSTOM_SPECIES:
+    if choice == _label("CUSTOM_SPECIES"):
         return [
             gr.update(visible=False),
             gr.update(visible=True),
             gr.update(visible=bool(file_input)),
         ]
-    if choice == PREDICT_SPECIES:
+    if choice == _label("PREDICT_SPECIES"):
         return [
             gr.update(visible=True),
             gr.update(visible=False),
@@ -1322,7 +1335,7 @@ def model_selection(state: TabState, opened=True):
             selected_model = model_selection_radio.value
 
             with gr.Column(
-                visible=selected_model == CUSTOM_CLASSIFIER
+                visible=selected_model == _label("CUSTOM_CLASSIFIER")
             ) as custom_classifier_selector:
                 classifier_selection_button = gr.Button(
                     loc.localize(
@@ -1406,7 +1419,7 @@ def on_custom_classifier_selection_click():
     )
 
     def on_model_selection_change(choice: str, cc_state):
-        if choice == CUSTOM_CLASSIFIER:
+        if choice == _label("CUSTOM_CLASSIFIER"):
             return gr.update(visible=True), gr.update(visible=cc_state is not None)
 
         return gr.update(visible=False), gr.update(visible=False)
@@ -1448,15 +1461,15 @@ def species_lists(
                 gr.Radio,
                 accepts={"choices": _species_choices(is_perch=False)},
                 choices=_species_choices(is_perch),
-                value=ALL_SPECIES,
+                value=_label("ALL_SPECIES"),
                 label=loc.localize("species-list-radio-label"),
                 info=loc.localize("species-list-radio-info"),
                 elem_classes="d-block",
             )
             selected_species_list = species_list_radio.value
 
             with gr.Column(
-                visible=selected_species_list == PREDICT_SPECIES
+                visible=selected_species_list == _label("PREDICT_SPECIES")
             ) as position_row:
                 (
                     lat_number,
@@ -1469,7 +1482,7 @@ def species_lists(
 
             species_file_input = gr.File(
                 file_types=[".txt"],
-                visible=selected_species_list == CUSTOM_SPECIES,
+                visible=selected_species_list == _label("CUSTOM_SPECIES"),
                 show_label=False,
             )
 
@@ -1731,10 +1744,7 @@ def open_window(
     multiprocessing.freeze_support()
 
     with (
-        gr.Blocks(
-            theme=gr.themes.Default(),
-            analytics_enabled=False,
-        ) as demo,
+        gr.Blocks(analytics_enabled=False) as demo,
     ):
         build_header()