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Compatibility with Python <3.9, remove CMD window pop-ups on Windows, add missing gaia dll

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This commit is contained in:
Ahmed Al-Taiar
2025-08-07 20:43:30 -04:00
parent 6bda2d471f
commit a31f2ad341
3 changed files with 35 additions and 27 deletions
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55
__init__.py
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@@ -5,6 +5,7 @@ import hashlib
import threading
import concurrent.futures
import tempfile
from typing import List, Tuple, Dict, Optional
from picard import config, log
from picard.ui.itemviews import (
@@ -15,7 +16,6 @@ from picard.ui.itemviews import (
from picard.track import Track
from picard.album import Album
from picard.ui.options import OptionsPage, register_options_page
from picard.formats import OggOpusFile
from PyQt5 import QtWidgets
from .constants import *
@@ -31,7 +31,7 @@ class AcousticBrainzNG:
binary_path += '.exe'
return binary_path
def _get_binary_paths(self) -> tuple[str, str]:
def _get_binary_paths(self) -> Tuple[str, str]:
binaries_path = config.setting["acousticbrainz_ng_binaries_path"]
if not binaries_path:
raise ValueError("Binaries path not configured")
@@ -46,7 +46,7 @@ class AcousticBrainzNG:
return musicnn_binary_path, gaia_binary_path
def _run_musicnn_models(self, models: list[tuple[str, str]], musicnn_binary_path: str, file: str, output_path: str) -> None:
def _run_musicnn_models(self, models: List[Tuple[str, str]], musicnn_binary_path: str, file: str, output_path: str) -> None:
models_path = config.setting["acousticbrainz_ng_models_path"]
if not models_path:
raise ValueError("Models path not configured")
@@ -68,7 +68,8 @@ class AcousticBrainzNG:
[musicnn_binary_path, model_path, file, output_file_path],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
except FileNotFoundError as e:
log.error(f"Model {model_name} not found: {e}")
@@ -80,7 +81,7 @@ class AcousticBrainzNG:
futures = [executor.submit(run_musicnn_model, model) for model in models]
concurrent.futures.wait(futures)
def analyze_required(self, metadata: dict, file: str) -> None:
def analyze_required(self, metadata: Dict, file: str) -> None:
if not self._check_binaries():
log.error("Essentia binaries not found")
return
@@ -107,7 +108,8 @@ class AcousticBrainzNG:
[gaia_binary_path, file, os.path.join(output_path, "gaia.json")],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
gaia_thread = threading.Thread(target=run_gaia)
@@ -116,7 +118,7 @@ class AcousticBrainzNG:
self._run_musicnn_models(REQUIRED_MODELS, musicnn_binary_path, file, output_path)
gaia_thread.join()
def analyze_optional(self, metadata: dict, file: str) -> None:
def analyze_optional(self, metadata: Dict, file: str) -> None:
if not self._check_binaries():
log.error("Essentia binaries not found")
return
@@ -137,7 +139,7 @@ class AcousticBrainzNG:
self._run_musicnn_models(OPTIONAL_MODELS, musicnn_binary_path, file, output_path)
def parse_required(self, metadata: dict, file: str) -> None:
def parse_required(self, metadata: Dict, file: str) -> None:
if not self._check_required_models():
raise ValueError("Required models not found")
@@ -251,7 +253,7 @@ class AcousticBrainzNG:
metadata["ab:lo:tonal:key_scale"] = selected_key_data["scale"]
metadata["ab:lo:tonal:key_key"] = selected_key_data["key"]
def parse_optional(self, metadata: dict, file: str) -> None:
def parse_optional(self, metadata: Dict, file: str) -> None:
if not self._check_optional_models():
raise ValueError("Optional models not found")
@@ -303,7 +305,7 @@ class AcousticBrainzNG:
def _format_class(class_name: str) -> str:
return class_name.replace("non", "not").replace("_", " ").capitalize()
def _generate_cache_folder(self, metadata: dict, file_path: str) -> str:
def _generate_cache_folder(self, metadata: Dict, file_path: str) -> str:
cache_base = config.setting["acousticbrainz_ng_cache_path"]
if not cache_base:
raise ValueError("Cache path not configured")
@@ -340,7 +342,8 @@ class AcousticBrainzNG:
[binary_path, file_path],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
if result.returncode == 0:
@@ -368,7 +371,7 @@ class AcousticBrainzNG:
return True
def _check_models(self, models: list[tuple[str, str]]) -> bool:
def _check_models(self, models: List[Tuple[str, str]]) -> bool:
path = config.setting["acousticbrainz_ng_models_path"]
if not path or not os.path.exists(path):
@@ -390,7 +393,7 @@ class AcousticBrainzNG:
def _is_opus_file(self, file_path: str) -> bool:
return file_path.lower().endswith('.opus')
def calculate_track_loudness(self, file_path: str) -> dict:
def calculate_track_loudness(self, file_path: str) -> Dict:
try:
ffmpeg_path = config.setting["acousticbrainz_ng_ffmpeg_path"]
if not ffmpeg_path:
@@ -400,7 +403,8 @@ class AcousticBrainzNG:
[ffmpeg_path, "-hide_banner", "-i", file_path, "-af", f"loudnorm=I={config.setting['acousticbrainz_ng_replaygain_reference_loudness']}:print_format=json", "-f", "null", "-"],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
replaygain_gain = None
@@ -430,7 +434,7 @@ class AcousticBrainzNG:
except (json.JSONDecodeError, ValueError, TypeError):
pass
result: dict = {
result: Dict = {
"replaygain_track_gain": replaygain_gain,
"replaygain_track_peak": replaygain_peak,
"replaygain_track_range": replaygain_range,
@@ -441,7 +445,8 @@ class AcousticBrainzNG:
[ffmpeg_path, "-hide_banner", "-i", file_path, "-af", "loudnorm=I=-23:print_format=json", "-f", "null", "-"],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
r128_track_gain = None
@@ -475,7 +480,7 @@ class AcousticBrainzNG:
log.error(f"Error calculating track loudness: {e}")
return {}
def calculate_album_loudness(self, album_track_files: list[str]) -> dict:
def calculate_album_loudness(self, album_track_files: List[str]) -> Dict:
try:
if len(album_track_files) == 0:
return {}
@@ -499,7 +504,8 @@ class AcousticBrainzNG:
"-vn", "-af", f"loudnorm=I={config.setting['acousticbrainz_ng_replaygain_reference_loudness']}:print_format=json", "-f", "null", "-"],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
album_gain = None
@@ -529,7 +535,7 @@ class AcousticBrainzNG:
except (json.JSONDecodeError, ValueError, TypeError):
pass
result: dict = {
result: Dict = {
"replaygain_album_gain": album_gain,
"replaygain_album_peak": album_peak,
"replaygain_album_range": album_range
@@ -540,7 +546,8 @@ class AcousticBrainzNG:
"-vn", "-af", "loudnorm=I=-23:print_format=json", "-f", "null", "-"],
capture_output=True,
text=True,
env=ENV
env=ENV,
creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0
)
r128_album_gain = None
@@ -577,7 +584,7 @@ class AcousticBrainzNG:
log.error(f"Error calculating album loudness: {e}")
return {}
def calculate_loudness(self, metadata: dict, file_path: str, album: Album | None = None) -> None:
def calculate_loudness(self, metadata: Dict, file_path: str, album: Optional[Album] = None) -> None:
try:
cache_folder = self._generate_cache_folder(metadata, file_path)
loudness_file = os.path.join(cache_folder, f"loudness_{config.setting['acousticbrainz_ng_replaygain_reference_loudness'] or -18}.json")
@@ -642,7 +649,7 @@ class AcousticBrainzNG:
except Exception as e:
log.error(f"Error calculating loudness: {e}")
def parse_loudness(self, metadata: dict, file: str) -> None:
def parse_loudness(self, metadata: Dict, file: str) -> None:
output_path = self._generate_cache_folder(metadata, file)
if not output_path:
raise ValueError("Failed to generate cache folder path")
@@ -705,7 +712,7 @@ acousticbrainz_ng = AcousticBrainzNG()
class AcousticBrainzNGAction(BaseAction):
NAME = f"Analyze with {PLUGIN_NAME}"
def _process_track(self, track: Track, album: Album | None = None) -> None:
def _process_track(self, track: Track, album: Optional[Album] = None) -> None:
for file in track.files:
acousticbrainz_ng.analyze_required(file.metadata, file.filename)
acousticbrainz_ng.parse_required(file.metadata, file.filename)
@@ -875,7 +882,7 @@ class AcousticBrainzNGOptionsPage(OptionsPage):
missing_binaries.append(binary)
try:
result = subprocess.run([ffmpeg_path, "-version"], capture_output=True, text=True)
result = subprocess.run([ffmpeg_path, "-version"], capture_output=True, text=True, creationflags=subprocess.CREATE_NO_WINDOW if os.name == 'nt' else 0)
if result.returncode != 0 or "ffmpeg version" not in result.stdout:
missing_binaries.append("FFmpeg (invalid executable)")
except Exception:

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7
constants.py
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@@ -1,5 +1,6 @@
import os
import sys
from typing import List, Tuple
from picard.config import BoolOption, TextOption, IntOption
PLUGIN_NAME = "AcousticBrainz-ng"
@@ -23,7 +24,7 @@ PLUGIN_LICENSE = "GPL-2.0-or-later"
PLUGIN_LICENSE_URL = "https://www.gnu.org/licenses/gpl-2.0.html"
PLUGIN_USER_GUIDE_URL = "https://example.com" # TODO: Update with actual user guide URL
REQUIRED_MODELS: list[tuple[str, str]] = [
REQUIRED_MODELS: List[Tuple[str, str]] = [
("msd-musicnn-1", "msd"),
("mood_acoustic-musicnn-mtt-2", "mood_acoustic"),
("mood_aggressive-musicnn-mtt-2", "mood_aggressive"),
@@ -38,13 +39,13 @@ REQUIRED_MODELS: list[tuple[str, str]] = [
("voice_instrumental-musicnn-msd-2", "voice_instrumental")
]
OPTIONAL_MODELS: list[tuple[str, str]] = [
OPTIONAL_MODELS: List[Tuple[str, str]] = [
("genre_electronic-musicnn-msd-2", "genre_electronic"),
("genre_rosamerica-musicnn-msd-2", "genre_rosamerica"),
("genre_tzanetakis-musicnn-msd-2", "genre_tzanetakis")
]
REQUIRED_BINARIES: list[str] = [
REQUIRED_BINARIES: List[str] = [
"streaming_extractor_music",
"streaming_musicnn_predict",
"streaming_md5",