pyproject.toml

[build-system]
requires = ["setuptools>=80.10.2", "wheel", "setuptools-scm"]
build-backend = "setuptools.build_meta"

[project]
# NOTE: この root project は uv workspace の管理用 meta package。
# PyPI へは publish せず (`[tool.uv] package = false` 参照)、
# canonical な `piper-plus` パッケージは `src/python_run/` から build される。
# Issue #418: src/python_run を workspace member 化する際の name 衝突を回避するため
# root を `piper-plus-workspace` に rename した。
name = "piper-plus-workspace"
dynamic = ["version"]
description = "Development workspace for piper-plus (not published; canonical piper-plus is built from src/python_run)"
license = {text = "MIT"}
requires-python = ">=3.11"
dependencies = [
    "huggingface-hub>=0.36.2,<1.0",
    "numpy<2.5",
    "tensorboard>=2.21.0",
    "inflect>=0.3.1",
    "nltk>=3.10.0",
    "joblib>=1.5.0",
    "torch==2.11.0",
    "torchaudio==2.11.0",
    "pytorch-lightning>=2.6.5",
    "librosa>=0.11.0",
    "cython>=3.2.9",
    "pyopenjtalk-plus>=0.4",
    "wandb>=0.28.1",
    # transformers 5 は hidden_states を層の hook で集めるため、学習時の layerdrop で
    # 飛んだ層が抜け、WavLMDiscriminator の use_layers がずれる (4.x は飛んだ層も
    # 前の層の値で埋める)。学習で使っている 4.x に揃える。
    "transformers>=4.50.0,<5",
    # workspace member refs: `uv sync` でこれらが自動 install される (root は
    # `package = false` なのでこの dependencies は実 install でなく resolver
    # の入力として機能)。Issue #418 で `piper-plus` を新規 member 化したため
    # 明示。 piper-plus-g2p は piper-train の依存として間接的に install される。
    "piper-train",
    "piper-plus",
    "onnxscript>=0.7.1",
    # Issue #527 / DR-002: C++ canonical (cmake/OnnxRuntime.cmake) と統一

    "ghapi>=1.1.1",
    "onnx>=1.22.0",
]

[project.optional-dependencies]
# piper-phonemize 1.1.0 only publishes macOS x86_64 wheels for CPython
# 3.11 / 3.12 (no sdist, no Linux/Windows wheel, no Apple Silicon wheel,
# no cp313 wheel), so every other interpreter/platform fails hard. The
# marker restricts the dependency to exactly that matrix — sys_platform
# AND platform_machine AND python_version — so it is never even attempted
# elsewhere and `uv sync --all-extras` succeeds by skipping it (QA finding
# F5). Dataset preprocessing via piper-phonemize is therefore macOS-x86_64
# + Python 3.11/3.12 only; piper-plus' own G2P does not need it.
preprocess = [
    "piper-phonemize>=1.1.0; sys_platform == 'darwin' and platform_machine == 'x86_64' and python_version < '3.13'",
]

inference = [
    "piper-plus[cpu]",
    "onnxruntime>=1.28.0",
    "soundfile>=0.14.0",
    "pyopenjtalk-plus",
    "inflect>=0.3.1",
    "nltk>=3.10.0",
    "joblib>=1.5.0",
    "fastapi>=0.141.1",
    "uvicorn>=0.49.0",
]

inference-gpu = [
    "piper-plus[gpu]",
    # Issue #527 follow-up: onnxruntime-gpu 1.26+ requires libcudart.so.13 (CUDA 13)
    # but DR-001 base image is CUDA 12.8.1. Cap to <1.26 until the CUDA 13 base
    # bump lands in a dedicated follow-up PR.
    "onnxruntime-gpu>=1.20.1,<1.26",
    "soundfile>=0.14.0",
    "pyopenjtalk-plus",
    "inflect>=0.3.1",
    "nltk>=3.10.0",
    "joblib>=1.5.0",
    "fastapi>=0.141.1",
    "uvicorn>=0.49.0",
]

multilingual = [
    "pypinyin>=0.55.0",
    "g2pk2>=0.0.3",
]

train = [
    "scipy>=1.17.1",
    "librosa>=0.11.0",
    # PR #222 (Zero-Shot TTS): extract_speaker_embedding.py / norm_audio /
    # tools/cache_audio.py が `import soxr` を行う。 librosa>=0.11 経由で
    # 推移的に提供されるが、 supply-chain hygiene として explicit floor を宣言。
    "soxr>=1.1.0",
    "soundfile>=0.14.0",
    "pytorch-lightning>=2.6.5",
    "torchmetrics>=1.9.0",
    # transformers 5 は hidden_states を層の hook で集めるため、学習時の layerdrop で
    # 飛んだ層が抜け、WavLMDiscriminator の use_layers がずれる (4.x は飛んだ層も
    # 前の層の値で埋める)。学習で使っている 4.x に揃える。
    "transformers>=4.50.0,<5",
    "onnx>=1.22.0",
    "onnxruntime>=1.28.0",
    "pyopenjtalk-plus",
    "mecab-python3>=1.0",
    "unidic-lite>=1.0",
    "inflect>=0.3.1",
    "nltk>=3.10.0",
    "joblib>=1.5.0",
    "tensorboard>=2.21.0",
    "wandb>=0.28.1",
    "tqdm>=4.70.0",
    "einops>=0.7",
    "numba>=0.66.0",
    "matplotlib>=3.11.1",
    "seaborn>=0.13",
    "pyyaml>=6.0.3",
    "onnxsim-prebuilt",
]

dev = [
    "black==26.5.1",
    "flake8==6.1.0",
    "mypy>=1.20.2",
    "pylint==3.3.9",
    "ruff==0.15.15",
    "pytest>=9.1.1,<10",
    "pytest-cov==4.1.0",
    "pytest-xdist==3.8.0",
    "pytest-timeout==2.4.0",
    "pytest-mock==3.16.0",
    "pytest-asyncio>=1.4.0",  # NEW: async FastAPI tests
    "coverage[toml]>=7.15.2",
    "types-requests==2.33.0.20260906",
    "types-PyYAML==6.0.12",
    "sphinx>=4.0.0",
    "sphinx-rtd-theme>=3.1.0",
    "pre-commit>=4.6.1",
    # Mutation testing (manual / weekly CI 専用、push 毎には走らせない)。
    # 設定: .mutmut.toml / docs/reference/mutation-testing.md。
    # 通常は `uvx mutmut run` で十分だが、dev 環境の declarative source として pin。
    "mutmut>=2.4,<3",
]

test = [
    "pytest>=9.1.1,<10",
    "pytest-cov==4.1.0",
    "pytest-xdist==3.8.0",
    "pytest-timeout==2.4.0",
    "pytest-mock==3.16.0",
    "pytest-asyncio>=1.4.0",  # NEW: async FastAPI tests
    "coverage[toml]>=7.15.2",
    "ruff==0.15.15",
    "mypy>=1.20.2",
    "types-requests==2.33.0.20260906",
    "types-PyYAML==6.0.12",
]

[[tool.uv.index]]
name = "pytorch-cu128"
url = "https://download.pytorch.org/whl/cu128"
explicit = true

[tool.uv.sources]
torch = [
    { index = "pytorch-cu128", marker = "sys_platform != 'darwin'" },
]
torchaudio = [
    { index = "pytorch-cu128", marker = "sys_platform != 'darwin'" },
]
piper-train = { workspace = true, editable = true }
piper-plus-g2p = { workspace = true, editable = true }
piper-plus = { workspace = true, editable = true }

[tool.uv.workspace]
members = [
    "src/python",
    "src/python/g2p",
    "src/python_run",
]

[dependency-groups]
dev = [
    "ruff==0.15.15",
    "pytest>=9.1.1,<10",
    "pytest-timeout>=2.2.0",
    "black==26.5.1",
    # Issue #527 / DR-002: inference extras の統一 floor (>=0.136.1) と揃える。
    "fastapi>=0.136.1",
    "httpx>=0.28.1",
    # starlette 1.x の TestClient は httpx ではなく httpx2 を要求する
    # (starlette/testclient.py が httpx2 未導入時に RuntimeError を投げる)。
    # 現状は wandb 0.30 の transitive として解決されるが、
    # test_http_server_root.py / test_http_timing.py / test_openai_api.py が
    # TestClient を使うため、 無関係な経路への暗黙依存を避けて明示宣言する。
    "httpx2>=2.13.0",
    # OpenAI SDK for end-to-end tests against /v1/audio/speech via
    # docker/python-inference/test_openai_api.py::TestOpenAISDKEndToEnd. Tests
    # auto-skip when the SDK is not installed; this entry just ensures uv-managed
    # dev environments and CI runners pick it up.
    "openai>=1.50.0",
    "uvicorn>=0.49.0",
]

cpu = ["onnxruntime>=1.28.0", "piper-train[train]"]

[tool.uv]
default-groups = ["dev", "cpu"]
conflicts = [
    [{extra = "inference-gpu"}, {group = "cpu"}],
    [{extra = "inference-gpu"}, {extra = "inference"}],
    [{extra = "inference-gpu"}, {extra = "train"}],
    [{package = "piper-plus", extra = "cpu"}, {package = "piper-plus", extra = "gpu"}],
]
# root は workspace 管理用 meta package。`package = false` で root 自体を
# install/build 対象から外す (Issue #418、 src/python_run と name が衝突しない
# よう root を `piper-plus-workspace` にした上で非 install 化)。
package = false

[tool.ruff]
extend-exclude = ["**/_vendor"]
# Ruffの基本設定
line-length = 88  # blackと同じ行長
target-version = "py311"  # Python 3.11以降をターゲット

# 除外するファイルとディレクトリ
exclude = [
    ".git",
    "__pycache__",
    "build",
    "dist",
    "*.egg-info",
    "src/python/piper_train/vits/monotonic_align",  # Cython generated
    # Temporary debug/test scripts in root directory
    "check_*.py",
    "debug_*.py",
    "test_*.py",
    "analyze_*.py",
    "verify_*.py",
    "export_*.sh",
]

[tool.ruff.lint]
# 有効にするルール
select = [
    "E",    # pycodestyle errors
    "W",    # pycodestyle warnings
    "F",    # pyflakes
    "I",    # isort
    "B",    # flake8-bugbear
    "C4",   # flake8-comprehensions
    "UP",   # pyupgrade
    "ARG",  # flake8-unused-arguments
    "PL",   # pylint
    "S",    # flake8-bandit (security)
    "PERF", # perflint (performance anti-patterns)
    "SIM",  # flake8-simplify
    "RUF",  # ruff-specific rules
]

# 除外するルール
ignore = [
    "E501",  # line too long (blackが処理)
    "PLR0913",  # Too many arguments to function call
    "PLR2004",  # Magic value used in comparison
    "PLR0912",  # Too many branches
    "PLR0915",  # Too many statements
    "PLR0911",  # Too many return statements
    "ARG001",  # Unused function argument
    "ARG002",  # Unused method argument
    "PLW2901",  # Redefined loop name
    # bandit: ノイジーすぎるルールの段階的緩和 (将来的に解消予定)
    "S101",  # use of assert (テストで多用される)
    "S104",  # hardcoded bind all interfaces (HTTP server で 0.0.0.0 を意図的に使用)
    "S105",  # hardcoded password (false positive: token / phoneme symbol 等)
    "S107",  # hardcoded password default (同上)
    "S110",  # try-except-pass (graceful degradation で意図的)
    "S301",  # pickle (内部信頼チェックポイントで使用)
    "S310",  # suspicious URL open (HF Hub / model download で必要)
    "S311",  # pseudo-random generators (TTS noise/sampling 用途は cryptographic でない)
    "S324",  # insecure hashlib (md5/sha1 を cache key 用途で使用、暗号用途ではない)
    "S603",  # subprocess call: 内部スクリプト実行で必要
    "S607",  # subprocess with partial path: 内部スクリプト実行で必要
    # SIM: 段階的緩和 (一部はリーダビリティで残したい)
    "SIM102",  # collapsible if (可読性で残すケースあり)
    "SIM105",  # contextlib.suppress (try-except-pass で十分)
    "SIM108",  # use ternary instead of if-else (可読性で残すケースあり)
    "SIM114",  # if-elif-else with same arms (TTS の分岐構造で意図的)
    "SIM115",  # open file with context handler (一部 lazy load で必要)
    "SIM117",  # nested with statements (可読性で残すケースあり)
    "SIM118",  # in dict.keys() (明示性のため許容)
    # PERF: 段階的緩和
    "PERF102",  # incorrect dict iterator (パフォーマンス影響軽微)
    "PERF203",  # try-except in loop (致命的でない/置き換え難しいケースあり)
    "PERF401",  # use list comprehension (リーダビリティで残すケースあり)
    "PERF402",  # manual list copy (`list.copy()` ではなく `[:]` を意図的に使う場面あり)
    "PERF403",  # manual dict comprehension (リーダビリティ優先)
    # RUF: 日本語コメント/文字列を多用するため一部緩和
    "RUF001",  # ambiguous unicode characters in string (日本語/CJK で誤検出)
    "RUF002",  # ambiguous unicode characters in docstring
    "RUF003",  # ambiguous unicode characters in comment
    "RUF005",  # collection literal concatenation (`[*a, *b]` より `a + b` を残す場面あり)
    "RUF012",  # mutable class default (dataclasses.field で個別対応中)
    "RUF013",  # implicit optional (M2 で個別対応)
    "RUF100",  # unused noqa (ruff version drift で一時的に発生)
]

# isort互換設定
[tool.ruff.lint.isort]
known-first-party = ["piper_plus", "piper_plus_g2p", "piper_train"]
combine-as-imports = true
lines-after-imports = 2

# flake8-quotes互換設定
[tool.ruff.lint.flake8-quotes]
inline-quotes = "double"

# Per-file ignores
[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F401", "F403"]
# テストファイル全般: bandit の assert 系 / pylint magic value / 条件付き import などを緩和
"src/python/tests/*" = [
    "ARG",      # unused arguments (fixtures)
    "PLC0415",  # conditional imports allowed in tests
    "S",        # bandit rules (assert/hardcoded passwords/etc は test では多用)
    "PLR2004",  # magic value comparison (test では普通)
    "SIM117",   # nested with statements
    "PERF",     # performance anti-patterns (test では readability 優先)
]
"src/python_run/tests/*" = [
    "ARG",
    "PLC0415",
    "S",
    "PLR2004",
    "SIM117",
    "PERF",
]
"src/python/g2p/tests/*" = [
    "ARG",
    "PLC0415",
    "S",
    "PLR2004",
    "SIM117",
    "PERF",
]
"test/**/*" = [
    "ARG",
    "PLC0415",
    "S",
    "PLR2004",
    "SIM117",
    "PERF",
]
"tests/**/*" = [
    "ARG",
    "PLC0415",
    "S",
    "PLR2004",
    "SIM117",
    "PERF",
]
"scripts/*" = ["ARG", "PLC0415", "S", "RUF059"]  # Allow conditional imports + subprocess + unused unpack
"tools/**/*" = ["ARG", "PLC0415", "S"]  # benchmark/dev tools
# 同梱ビルドスクリプト: 自前 build した tar/zip を展開するので extractall は許容
"src/piper_phonemize_bundled/*.py" = ["S202"]
# G2P ベンチマーク: 条件付き import + subprocess 許容
"src/python/g2p/benchmarks/*.py" = ["PLC0415", "S"]
# WASM テスト util: localhost への curl shell=True (ローカル開発用)
"src/wasm/openjtalk-web/test/*.py" = ["S602", "S605", "S607"]
# preprocess.py / prepare_bilingual_dataset.py: 既存ループ構造の SIM113 (enumerate refactor) は別 PR で
"src/python/piper_train/tools/prepare_bilingual_dataset.py" = ["SIM113"]
# token_mapper.py: グローバル変数を使用した音素マッピングシステム
"src/python/piper_train/phonemize/token_mapper.py" = ["PLW0603"]
# korean.py: G2p()インスタンスのモジュールレベルキャッシュ
"src/python/piper_train/phonemize/korean.py" = ["PLW0603"]
# bilingual.py: 条件付きインポート（後方互換のため動的切り替え）
"src/python/piper_train/phonemize/bilingual.py" = ["PLC0415"]
# mel_processing.py: パフォーマンス最適化のためのグローバルキャッシュ
"src/python/piper_train/vits/mel_processing.py" = ["PLW0602"]
# test_phonemize.py: オプショナルな依存関係の条件付きインポート
"src/python/tests/test_phonemize.py" = ["E402"]
# preprocess.py: 条件付きインポートで警告を抑制 + 既存ループ構造の SIM113 (enumerate refactor は別 PR で)
"src/python/piper_train/preprocess.py" = ["PLC0415", "SIM113"]
"src/python/piper_train/phonemize/english.py" = ["PLC0415", "PLW0603"]
# prepare scripts: 条件付きインポートを許可
"src/python/prepare_*.py" = ["PLC0415"]
# runtime files: 条件付きインポートを許可
"src/python_run/*" = ["PLC0415"]
# Docker test scripts: テスト関数内での条件付きインポートを許可
"docker/**/test.py" = ["PLC0415"]
# HuggingFace Spaces app: オプショナルな多言語依存の条件付きインポート
"huggingface-space/*.py" = ["PLC0415"]
# __main__.py: torch.serialization.add_safe_globals() がimport前に必要
"src/python/piper_train/__main__.py" = ["E402"]
# export_onnx.py: 同上
"src/python/piper_train/export_onnx.py" = ["E402"]
# lightning.py: メソッド内の遅延import（循環import回避、オプショナル依存）
"src/python/piper_train/vits/lightning.py" = ["PLC0415"]

[tool.setuptools.packages.find]
where = ["src/python"]

[tool.setuptools.dynamic]
version = {file = "VERSION"}

# -----------------------------------------------------------------------------
# Coverage configuration
# -----------------------------------------------------------------------------
# `pyproject.toml` is the single source of truth for coverage settings.
# pytest.ini の addopts で `--cov-fail-under` を上書きするため、CI と local で
# 同じ閾値を担保。閾値の段階的引き上げ計画:
#   - root (piper_train + piper runtime): 70 -> 80 (M2-M3)
#   - g2p: 80 -> 85 (M3)
#
# `omit` の方針 (Wave 2 で根本対応):
#   unit-test 不可能なモジュールを `omit` に列挙し、計測対象を「ライブラリ
#   コード (model 構造 / G2P / config parser / timing 計算 etc)」に絞る。
#   omit 根拠は以下 4 カテゴリのいずれか:
#     (a) CLI エントリ — argparse + `if __name__ == "__main__"` のみで lib 利用は薄い
#     (b) Lightning Trainer / DDP 起動を要するもの — マルチ GPU + datasets が必要
#     (c) Data preprocessing — 大量のオーディオ/テキスト ファイルシステム I/O が必要
#     (d) Network / model file 必須 (HuggingFace download, 巨大 .onnx ロード)
#   E2E は別途 docker / integration job で cover (本 unit coverage の対象外)。
[tool.coverage.run]
branch = true
source = [
    "src/python/piper_train",
    "src/python_run/piper_plus",
    "src/python/g2p/piper_plus_g2p",
]
omit = [
    "*/_vendor/*",
    # ----- 既存 -----
    "*/tests/*",
    "*/test_*.py",
    "*/__main__.py",                                       # (a) CLI エントリ
    "*/vits/monotonic_align/*",                            # Cython generated
    "*/.venv/*",
    "*/build/*",
    "*/dist/*",
    # ----- (a) CLI エントリ (argparse + main()、lib 関数として呼ばれない) -----
    "*/piper_train/clean_cached_audio.py",
    "*/piper_train/select_speaker.py",
    "*/piper_train/filter_utterances.py",
    "*/piper_train/voice_conversion.py",
    "*/piper_train/f0_extraction.py",
    "*/piper_train/infer.py",
    "*/piper_train/infer_generator.py",
    "*/piper_train/infer_torchscript.py",
    "*/piper_train/infer_onnx.py",                         # (a) ONNX 推論 CLI (model file 必須)
    "*/piper_train/infer_onnx_streaming.py",
    "*/piper_train/export_torchscript.py",
    "*/piper_train/export_generator.py",
    "*/piper_train/export_onnx.py",                        # (a)+(d) model file 必須 + Lightning ckpt load
    "*/piper_train/export_onnx_streaming.py",
    "*/piper_train/update_model_config.py",
    # ----- (b) Lightning Trainer 起動が必要 -----
    "*/piper_train/vits/lightning.py",                     # Lightning Module / Trainer
    "*/piper_train/vits/onnx_attention.py",                # ONNX export 専用 (推論時のみ)
    "*/piper_train/vits/losses.py",                        # 学習用 loss 関数のみ (lightning.py が唯一の caller)
    "*/piper_train/vits/config.py",                        # dataclass + 学習時 factory のみ (lightning.py が caller)
    # ----- (a) vendored scipy.io.wavfile (read/write のみ使用、形式判定の大部分は dead branch) -----
    "*/piper_train/vits/wavfile.py",
    # ----- (a) SSML fallback shim (canonical は piper_plus_g2p.ssml 側、ランタイム側は import re-export のみ) -----
    "*/piper_plus/phonemize/ssml.py",
    # ----- (c) Data preprocessing scripts -----
    "*/piper_train/preprocess.py",
    "*/piper_train/tools/prepare_bilingual_dataset.py",
    "*/piper_train/tools/prepare_multilingual_dataset.py",
    "*/piper_train/tools/convert_fp16.py",                 # (a) ONNX 変換 CLI
    "*/piper_train/tools/convert_nst_dictionary.py",       # (a) 辞書変換 CLI
    "*/piper_train/tools/add_prosody_features.py",         # (a) prosody 抽出 CLI
    # PR #222 (Zero-Shot TTS) preprocess + extract scripts: actual model file
    # + GPU/CPU + librosa/soxr resampling 必須で unit-test 不可能。 整合性は
    # E2E test で別途担保 (test_zero_shot_e2e.py / Rust / Go / C# / C++ parallel)。
    "*/piper_train/extract_speaker_embedding.py",
    "*/piper_train/tools/batch_spectrograms.py",
    "*/piper_train/tools/cache_audio.py",
    # ----- (d) Speaker encoder train/export scripts (model file + dataset 必須) -----
    "*/piper_train/speaker_encoder/__init__.py",
    "*/piper_train/speaker_encoder/encoder.py",            # ONNX/ckpt model file 必須
    "*/piper_train/speaker_encoder/audio_utils.py",        # 音声ファイル I/O (test fixtures 不在)
    "*/piper_train/speaker_encoder/ecapa_tdnn.py",         # 学習用モデル (Lightning Module)
    "*/piper_train/speaker_encoder/evaluate.py",
    "*/piper_train/speaker_encoder/export_encoder.py",
    # ----- (b) norm_audio: VAD/trim はファイルシステム + audio I/O が必要 -----
    "*/piper_train/norm_audio/__init__.py",
    "*/piper_train/norm_audio/trim.py",
    "*/piper_train/norm_audio/vad.py",
    # ----- (a) Runtime CLI entries -----
    "*/piper_plus/__main__.py",
    "*/piper_plus/webui.py",                               # Gradio UI
    "*/piper_plus/http_server.py",                         # FastAPI server (E2E test で cover)
    "*/piper_plus/training_manager.py",                    # subprocess train 起動
    "*/piper_plus/download.py",                            # (d) HuggingFace network 必須
    "*/piper_plus/sample_texts.py",                        # WebUI 用 constant データ (制御フローなし)
    # ----- (a) Resource finder (importlib.resources、env 依存) -----
    "*/piper_train/_resources.py",
    "*/piper_train/model_manager.py",                      # (d) HuggingFace catalog network 必須
]
parallel = true
# Cython / 動的に書き換えられるファイルでの coverage 計測のずれを回避
relative_files = true

[tool.coverage.report]
# CI/local 両方で coverage 70% を下回ると fail
fail_under = 70
show_missing = true
skip_covered = false
precision = 2
exclude_lines = [
    "pragma: no cover",
    "raise NotImplementedError",
    "if __name__ == .__main__.:",
    "if TYPE_CHECKING:",
    "@overload",
    "\\.\\.\\.",  # Ellipsis (Protocol/abstract method)
    "raise AssertionError",
]

[tool.coverage.html]
directory = "htmlcov"

[tool.coverage.xml]
output = "coverage.xml"