- Replace asyncio sleep loop with APScheduler AsyncIOScheduler + CronTrigger
- Add schedule_time (HH:MM), schedule_days (days of week), auto_download_after_rescan fields to SchedulerConfig
- Add _auto_download_missing() to queue missing episodes after rescan
- Reload config live via reload_config(SchedulerConfig) without restart
- Update GET/POST /api/scheduler/config to return {success, config, status} envelope
- Add day-of-week pill toggles to Settings -> Scheduler section in UI
- Update JS loadSchedulerConfig / saveSchedulerConfig for new API shape
- Add 29 unit tests for SchedulerConfig model, 18 unit tests for SchedulerService
- Rewrite 23 endpoint tests and 36 integration tests for APScheduler behaviour
- Coverage: 96% api/scheduler, 95% scheduler_service, 90% total (>= 80% threshold)
- Update docs: API.md, CONFIGURATION.md, features.md, CHANGELOG.md
228 lines
7.9 KiB
Python
228 lines
7.9 KiB
Python
from typing import Dict, List, Optional
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from pydantic import BaseModel, Field, ValidationError, field_validator
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_VALID_DAYS = frozenset(["mon", "tue", "wed", "thu", "fri", "sat", "sun"])
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_ALL_DAYS = ["mon", "tue", "wed", "thu", "fri", "sat", "sun"]
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class SchedulerConfig(BaseModel):
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"""Scheduler related configuration.
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Cron-based scheduling is configured via ``schedule_time`` and
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``schedule_days``. The legacy ``interval_minutes`` field is kept for
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backward compatibility but is **deprecated** and ignored when
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``schedule_time`` is set.
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"""
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enabled: bool = Field(
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default=True, description="Whether the scheduler is enabled"
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)
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interval_minutes: int = Field(
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default=60,
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ge=1,
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description="[Deprecated] Scheduler interval in minutes. "
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"Use schedule_time + schedule_days instead.",
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)
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schedule_time: str = Field(
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default="03:00",
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description="Daily run time in 24-hour HH:MM format (e.g. '03:00')",
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)
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schedule_days: List[str] = Field(
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default_factory=lambda: list(_ALL_DAYS),
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description="Days of week to run the scheduler (3-letter lowercase "
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"abbreviations: mon, tue, wed, thu, fri, sat, sun). "
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"Empty list means disabled.",
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)
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auto_download_after_rescan: bool = Field(
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default=False,
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description="Automatically queue and start downloads for all missing "
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"episodes after a scheduled rescan completes.",
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)
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@field_validator("schedule_time")
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@classmethod
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def validate_schedule_time(cls, v: str) -> str:
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"""Validate HH:MM format within 00:00–23:59."""
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import re
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if not re.fullmatch(r"([01]\d|2[0-3]):[0-5]\d", v or ""):
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raise ValueError(
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f"Invalid schedule_time '{v}'. "
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"Expected HH:MM in 24-hour format (00:00–23:59)."
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)
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return v
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@field_validator("schedule_days")
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@classmethod
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def validate_schedule_days(cls, v: List[str]) -> List[str]:
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"""Validate each entry is a valid 3-letter lowercase day abbreviation."""
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invalid = [d for d in v if d not in _VALID_DAYS]
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if invalid:
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raise ValueError(
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f"Invalid day(s) in schedule_days: {invalid}. "
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f"Allowed values: {sorted(_VALID_DAYS)}"
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)
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return v
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class BackupConfig(BaseModel):
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"""Configuration for automatic backups of application data."""
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enabled: bool = Field(
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default=False, description="Whether backups are enabled"
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)
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path: Optional[str] = Field(
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default="data/backups", description="Path to store backups"
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)
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keep_days: int = Field(
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default=30, ge=0, description="How many days to keep backups"
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)
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class LoggingConfig(BaseModel):
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"""Logging configuration with basic validation for level."""
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level: str = Field(
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default="INFO", description="Logging level"
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)
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file: Optional[str] = Field(
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default=None, description="Optional file path for log output"
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)
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max_bytes: Optional[int] = Field(
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default=None, ge=0, description="Max bytes per log file for rotation"
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)
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backup_count: Optional[int] = Field(
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default=3, ge=0, description="Number of rotated log files to keep"
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)
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@field_validator("level")
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@classmethod
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def validate_level(cls, v: str) -> str:
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allowed = {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"}
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lvl = (v or "").upper()
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if lvl not in allowed:
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raise ValueError(f"invalid logging level: {v}")
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return lvl
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class NFOConfig(BaseModel):
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"""NFO metadata configuration."""
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tmdb_api_key: Optional[str] = Field(
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default=None, description="TMDB API key for metadata scraping"
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)
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auto_create: bool = Field(
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default=False, description="Auto-create NFO files for new series"
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)
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update_on_scan: bool = Field(
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default=False, description="Update existing NFO files on rescan"
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)
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download_poster: bool = Field(
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default=True, description="Download poster.jpg"
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)
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download_logo: bool = Field(
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default=True, description="Download logo.png"
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)
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download_fanart: bool = Field(
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default=True, description="Download fanart.jpg"
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)
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image_size: str = Field(
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default="original", description="Image size (original or w500)"
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)
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@field_validator("image_size")
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@classmethod
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def validate_image_size(cls, v: str) -> str:
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allowed = {"original", "w500"}
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size = (v or "").lower()
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if size not in allowed:
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raise ValueError(
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f"invalid image size: {v}. Must be 'original' or 'w500'"
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)
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return size
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class ValidationResult(BaseModel):
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"""Result of a configuration validation attempt."""
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valid: bool = Field(..., description="Whether the configuration is valid")
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errors: List[str] = Field(
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default_factory=lambda: [],
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description="List of validation error messages"
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)
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class AppConfig(BaseModel):
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"""Top-level application configuration model used by the web layer.
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This model intentionally keeps things small and serializable to JSON.
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"""
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name: str = Field(default="Aniworld", description="Application name")
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data_dir: str = Field(default="data", description="Base data directory")
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scheduler: SchedulerConfig = Field(
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default_factory=SchedulerConfig
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)
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logging: LoggingConfig = Field(default_factory=LoggingConfig)
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backup: BackupConfig = Field(default_factory=BackupConfig)
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nfo: NFOConfig = Field(default_factory=NFOConfig)
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other: Dict[str, object] = Field(
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default_factory=dict, description="Arbitrary other settings"
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)
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def validate_config(self) -> ValidationResult:
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"""Perform light-weight validation and return a ValidationResult.
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This method intentionally avoids performing IO (no filesystem checks)
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so it remains fast and side-effect free for unit tests and API use.
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"""
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errors: List[str] = []
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# Pydantic field validators already run on construction; re-run a
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# quick check for common constraints and collect messages.
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try:
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# Reconstruct to ensure nested validators are executed
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AppConfig(**self.model_dump())
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except ValidationError as exc:
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for e in exc.errors():
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loc = ".".join(str(x) for x in e.get("loc", []))
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msg = f"{loc}: {e.get('msg')}"
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errors.append(msg)
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# backup.path must be set when backups are enabled
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backup_data = self.model_dump().get("backup", {})
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if backup_data.get("enabled") and not backup_data.get("path"):
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errors.append(
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"backup.path must be set when backups.enabled is true"
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)
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return ValidationResult(valid=(len(errors) == 0), errors=errors)
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class ConfigUpdate(BaseModel):
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scheduler: Optional[SchedulerConfig] = None
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logging: Optional[LoggingConfig] = None
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backup: Optional[BackupConfig] = None
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nfo: Optional[NFOConfig] = None
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other: Optional[Dict[str, object]] = None
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def apply_to(self, current: AppConfig) -> AppConfig:
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"""Return a new AppConfig with updates applied to the current config.
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Performs a shallow merge for `other`.
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"""
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data = current.model_dump()
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if self.scheduler is not None:
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data["scheduler"] = self.scheduler.model_dump()
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if self.logging is not None:
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data["logging"] = self.logging.model_dump()
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if self.backup is not None:
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data["backup"] = self.backup.model_dump()
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if self.nfo is not None:
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data["nfo"] = self.nfo.model_dump()
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if self.other is not None:
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merged = dict(current.other or {})
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merged.update(self.other)
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data["other"] = merged
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return AppConfig(**data)
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