- pyproject.toml with FastAPI, uvicorn, Pydantic v2, aiofiles, structlog deps - DeviceConfig Pydantic model with StripType, UUID, validation constraints - ShowModel with AudioRef, TrackModel, CueModel, AnalysisBlock, schema_version=1 - BaseDevice ABC with encode_frame, encode_animation_cmd, bytes_per_pixel - SK6812Device (4 bytes/pixel) and WS2801Device (3 bytes/pixel) implementations
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from uuid import UUID, uuid4
|
|
from datetime import datetime, timezone
|
|
from typing import Any, Literal
|
|
from pydantic import BaseModel, Field
|
|
|
|
from lightsync.models.device import DeviceConfig
|
|
|
|
|
|
class AudioRef(BaseModel):
|
|
source_type: Literal["file", "youtube"] = "file"
|
|
path: str | None = None
|
|
yt_url: str | None = None
|
|
duration_seconds: float | None = None
|
|
|
|
|
|
class CueModel(BaseModel):
|
|
id: UUID = Field(default_factory=uuid4)
|
|
timestamp: float
|
|
mode: Literal["animation", "frame_sequence"] = "animation"
|
|
animation: str | None = None
|
|
params: dict[str, Any] = Field(default_factory=dict)
|
|
|
|
|
|
class TrackModel(BaseModel):
|
|
device_id: UUID
|
|
cues: list[CueModel] = Field(default_factory=list)
|
|
|
|
|
|
class AnalysisBlock(BaseModel):
|
|
analysed_at: datetime | None = None
|
|
tempo_bpm: float | None = None
|
|
beat_times: list[float] = Field(default_factory=list)
|
|
onset_times: list[float] = Field(default_factory=list)
|
|
|
|
|
|
class ShowModel(BaseModel):
|
|
schema_version: int = 1
|
|
id: UUID = Field(default_factory=uuid4)
|
|
name: str
|
|
created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
|
|
updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
|
|
audio: AudioRef = Field(default_factory=AudioRef)
|
|
devices: list[DeviceConfig] = Field(default_factory=list)
|
|
analysis: AnalysisBlock = Field(default_factory=AnalysisBlock)
|
|
tracks: list[TrackModel] = Field(default_factory=list)
|
|
ai_sequences: list[Any] = Field(default_factory=list)
|