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import hashlib
import io
from typing import Any
import numpy as np
import soundfile as sf
from fastapi.encoders import jsonable_encoder
def round_floats(value: Any, round_value: int) -> Any:
"""floatの小数点以下を再帰的に丸める"""
if isinstance(value, float):
return round(value, round_value)
elif isinstance(value, np.ndarray) and np.issubdtype(value.dtype, np.floating):
return np.round(value, round_value)
elif isinstance(value, list):
return [round_floats(v, round_value) for v in value]
elif isinstance(value, dict):
return {k: round_floats(v, round_value) for k, v in value.items()}
else:
return value
def pydantic_to_native_type(value: Any) -> Any:
"""pydanticの型をnativeな型に変換する"""
return jsonable_encoder(value)
def hash_long_string(value: Any) -> Any:
"""文字数が1000文字を超えるものはハッシュ化する"""
def to_hash(value: str) -> str:
return "MD5:" + hashlib.md5(value.encode()).hexdigest()
if isinstance(value, str):
return value if len(value) <= 1000 else to_hash(value)
elif isinstance(value, list):
return [hash_long_string(v) for v in value]
elif isinstance(value, dict):
return {k: hash_long_string(v) for k, v in value.items()}
else:
return value
def summarize_big_ndarray(value: Any) -> Any:
"""要素数が100を超える NDArray を、ハッシュ値と shape からなる文字列へ要約する"""
def to_hash(value: np.ndarray) -> str:
return "MD5:" + hashlib.md5(value.tobytes()).hexdigest()
if isinstance(value, np.ndarray):
if value.size <= 100:
return value
else:
return {"hash": to_hash(value), "shape": value.shape}
elif isinstance(value, list):
return [summarize_big_ndarray(v) for v in value]
elif isinstance(value, dict):
return {k: summarize_big_ndarray(v) for k, v in value.items()}
else:
return value
def hash_wave_floats_from_wav_bytes(wav_bytes: bytes) -> str:
""".wavファイルバイト列から音声波形を抽出しハッシュ化する"""
wave = sf.read(io.BytesIO(wav_bytes))[0].tolist()
# NOTE: Linux-Windows 数値精度問題に対するワークアラウンド
wave = round_floats(wave, 2)
return "MD5:" + hashlib.md5(np.array(wave).tobytes()).hexdigest()
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