bambuddy/backend/app/schemas/print_queue.py

from datetime import datetime
from typing import Annotated, Literal

from pydantic import BaseModel, BeforeValidator, Field, PlainSerializer, model_validator

from backend.app.utils.printer_models import MAX_CHAMBER_TEMP_C


# Custom serializer to ensure UTC datetimes have Z suffix
def serialize_utc_datetime(dt: datetime | None) -> str | None:
    if dt is None:
        return None
    # Add Z suffix to indicate UTC
    return dt.isoformat() + "Z"


UTCDatetime = Annotated[datetime | None, PlainSerializer(serialize_utc_datetime)]


def _coerce_tristate(v: object) -> object:
    """Map legacy on/off booleans onto the tri-state calibration options.

    bed_levelling / flow_cali / nozzle_offset_cali were plain booleans before we
    added BambuStudio's third "auto" state (skip if recently done). Rows and API
    payloads created under the old scheme carry bool / 0-1 int / "true"/"false";
    coerce them so old clients and un-migrated rows still validate. getValueInt
    parity: off=0, on=1, auto=2.
    """
    if isinstance(v, bool):
        return "on" if v else "off"
    if isinstance(v, int):
        return {0: "off", 1: "on", 2: "auto"}.get(v, "auto")
    if isinstance(v, str):
        low = v.strip().lower()
        if low in ("true", "1"):
            return "on"
        if low in ("false", "0"):
            return "off"
    return v


# Tri-state calibration option: "auto" (printer decides / skip if recent),
# "on" (force every print), "off" (never). Mirrors BambuStudio's ops_auto.
TriState = Annotated[Literal["off", "on", "auto"], BeforeValidator(_coerce_tristate)]


class QueueVariantCreate(BaseModel):
    """One candidate file for a cross-model queue item (#671).

    Per-file rather than per-item because the settings genuinely differ between
    candidates: an H2C slice is dual-nozzle and will not share slot count, AMS
    mapping or nozzle mapping with the H2S slice of the same model.

    ``target_model`` is normally omitted and read from the file's own
    ``sliced_for_model``; supply it only for a legacy 3MF that declares none.
    """

    library_file_id: int
    target_model: str | None = None
    plate_id: int | None = None
    ams_mapping: list[int] | None = None
    nozzle_mapping: list[int] | None = None
    # Which rack position each filament group prints from (#1784), as
    # {group_id: 1-based position}. The operator's pick, re-checked against the
    # live rack at dispatch; null means "assign them for me".
    nozzle_rack_choice: dict[int, int] | None = None
    filament_overrides: list[dict] | None = None


class PrintQueueItemCreate(BaseModel):
    printer_id: int | None = None  # None = unassigned, user assigns later
    target_model: str | None = None  # Target printer model (mutually exclusive with printer_id)
    target_location: str | None = None  # Target location filter (only used with target_model)
    required_filament_types: list[str] | None = None  # Required filament types for model-based assignment
    filament_overrides: list[dict] | None = None  # Filament overrides for model-based assignment
    # Either archive_id OR library_file_id must be provided
    archive_id: int | None = None
    library_file_id: int | None = None
    scheduled_time: datetime | None = None  # None = ASAP (next when idle)
    require_previous_success: bool = False
    auto_off_after: bool = False  # Power off printer after print completes
    manual_start: bool = False  # Requires manual trigger to start (staged)
    insert_at_top: bool = False  # Insert ahead of other pending items in the same queue scope
    insert_position: int | None = None  # 1-indexed insertion position for priority queueing
    # Persistent "Print Anyway" acknowledgement (#1698-followup). When set,
    # PrintModal already showed the deficit warning and the user confirmed,
    # so the scheduler does not re-flag this item on the next tick.
    skip_filament_check: bool = False
    # AMS mapping: list of global tray IDs for each filament slot
    # Format: [5, -1, 2, -1] where position = slot_id-1, value = global tray ID (-1 = unused)
    ams_mapping: list[int] | None = None
    # Plate ID for multi-plate 3MF files (1-indexed, None = auto-detect/plate 1)
    plate_id: int | None = None
    # Print options. bed_levelling / flow_cali / nozzle_offset_cali are tri-state
    # (off/on/auto), defaulting to "auto" to match BambuStudio. vibration_cali /
    # layer_inspect / timelapse stay on/off (BambuStudio exposes no auto for them).
    bed_levelling: TriState = "auto"
    flow_cali: TriState = "auto"
    vibration_cali: bool = True
    layer_inspect: bool = False
    timelapse: bool = False
    use_ams: bool = True
    # Nozzle offset calibration — dual-nozzle printers only (#1682). The MQTT
    # layer ignores the value on single-nozzle printers so the wire stays "skip".
    nozzle_offset_cali: TriState = "auto"
    # Ask for a post-print outcome verdict when this job completes (#1898)
    confirm_outcome: bool = False
    # Preheat / heat-soak per-item override (#1468). 'inherit' uses the global
    # preheat_enabled setting; 'on' / 'off' force the decision. The chamber
    # target falls through: this override → max(filament-map[loaded tray]) → 0.
    preheat_override: Literal["inherit", "on", "off"] = "inherit"
    preheat_chamber_target_override: int | None = Field(default=None, ge=0, le=MAX_CHAMBER_TEMP_C)
    # Auto-print G-code injection
    gcode_injection: bool = False
    # Batch: create multiple copies (creates a batch if > 1)
    quantity: int = 1
    # Existing batch to add this item into. When set, the item's batch_id is
    # populated on insert so the queue UI groups it with its siblings. Used by
    # the multi-plate auto-batch flow and by the "Group as batch" action.
    batch_id: int | None = None
    # Project to associate the resulting archive with
    project_id: int | None = None
    cost_center_id: int | None = None
    estimated_cost: float | None = None
    # Which rack position each filament group prints from (#1784), as
    # {group_id: 1-based position}. The operator's pick, re-checked against the
    # live rack at dispatch; null means "assign them for me".
    nozzle_rack_choice: dict[int, int] | None = None
    # Direct printer-card uploads are temporary library files. The scheduler
    # deletes them after creating the durable archive copy.
    cleanup_library_after_dispatch: bool = False
    # Cross-model alternatives (#671): several sliced files, one job, whichever
    # printer frees up first. Mutually exclusive with printer_id (a specific
    # printer defeats the purpose) and with archive_id/library_file_id (the
    # candidates ARE the files). The scheduler resolves one onto the row at
    # dispatch, after which the item is an ordinary single-file job.
    variants: list[QueueVariantCreate] | None = None


class PrintQueueItemUpdate(BaseModel):
    printer_id: int | None = None
    target_model: str | None = None  # Target printer model (mutually exclusive with printer_id)
    target_location: str | None = None  # Target location filter (only used with target_model)
    filament_overrides: list[dict] | None = None  # Filament overrides for model-based assignment
    position: int | None = None
    scheduled_time: datetime | None = None
    require_previous_success: bool | None = None
    auto_off_after: bool | None = None
    manual_start: bool | None = None
    ams_mapping: list[int] | None = None
    plate_id: int | None = None
    # Print options
    bed_levelling: TriState | None = None
    flow_cali: TriState | None = None
    vibration_cali: bool | None = None
    layer_inspect: bool | None = None
    timelapse: bool | None = None
    use_ams: bool | None = None
    nozzle_offset_cali: TriState | None = None
    confirm_outcome: bool | None = None
    preheat_override: Literal["inherit", "on", "off"] | None = None
    preheat_chamber_target_override: int | None = Field(default=None, ge=0, le=MAX_CHAMBER_TEMP_C)
    # Auto-print G-code injection
    gcode_injection: bool | None = None
    cost_center_id: int | None = None
    estimated_cost: float | None = None
    # H2C dual-nozzle-rack slicer pick (#1780). list[int] per-filament
    # physical nozzle position IDs from BambuStudio's project_file MQTT
    # body; sent back to the printer verbatim on dispatch.
    nozzle_mapping: list[int] | None = None
    # Which rack position each filament group prints from (#1784), as
    # {group_id: 1-based position}. The operator's pick, re-checked against the
    # live rack at dispatch; null means "assign them for me".
    nozzle_rack_choice: dict[int, int] | None = None


class QueueVariantSummary(BaseModel):
    """One candidate on a cross-model queue item, for display (#671)."""

    library_file_id: int
    filename: str
    target_model: str
    position: int


class PrintQueueItemResponse(BaseModel):
    id: int
    printer_id: int | None  # None = unassigned
    target_model: str | None = None  # Target printer model for model-based assignment
    target_location: str | None = None  # Target location filter for model-based assignment
    required_filament_types: list[str] | None = None  # Required filament types for model-based assignment
    filament_overrides: list[dict] | None = None  # Filament overrides for model-based assignment
    waiting_reason: str | None = None  # Why this job hasn't started yet (empty once it can)
    archive_id: int | None  # None if library_file_id is set (archive created at print start)
    library_file_id: int | None  # For queue items from library files
    cost_center_id: int | None = None
    estimated_cost: float | None = None
    position: int
    scheduled_time: UTCDatetime
    require_previous_success: bool
    auto_off_after: bool
    manual_start: bool
    # True when the dispatch scheduler last evaluated this item and the
    # assigned spool could not satisfy at least one slot's required grams
    # (#1496). Display-only — the ▶ click recomputes deficit against live
    # spool state.
    filament_short: bool = False
    # User has acknowledged "Print Anyway" — scheduler skips the deficit check
    # for this item (#1698-followup).
    skip_filament_check: bool = False
    ams_mapping: list[int] | None = None
    plate_id: int | None = None  # Plate ID for multi-plate 3MF files
    # Print options
    bed_levelling: TriState = "auto"
    flow_cali: TriState = "auto"
    vibration_cali: bool = True
    layer_inspect: bool = False
    timelapse: bool = False
    use_ams: bool = True
    nozzle_offset_cali: TriState = "auto"
    confirm_outcome: bool = False
    preheat_override: Literal["inherit", "on", "off"] = "inherit"
    preheat_chamber_target_override: int | None = None
    status: Literal["pending", "printing", "completed", "failed", "skipped", "cancelled"]
    started_at: UTCDatetime
    completed_at: UTCDatetime
    error_message: str | None
    created_at: UTCDatetime

    # Nested info for UI (populated in route)
    archive_name: str | None = None
    archive_thumbnail: str | None = None
    # True when the linked archive has been soft-deleted (its files are gone
    # from disk). In that case the *archive_name* / *archive_thumbnail* /
    # downstream metadata fields are intentionally left None so the frontend
    # doesn't 404-storm the now-missing thumbnail / plates / plate-thumbnail
    # endpoints (#1348 follow-up). Frontends can render a "source deleted"
    # badge based on this flag.
    archive_deleted: bool = False
    library_file_name: str | None = None  # Name of library file (if library_file_id is set)
    library_file_thumbnail: str | None = None  # Thumbnail of library file
    printer_name: str | None = None
    print_time_seconds: int | None = None  # Estimated print time from archive or library file
    filament_used_grams: float | None = None  # Estimated print weight from archive or library file
    filament_type: str | None = None  # e.g. "PLA", "PETG" (from archive/library file)
    filament_color: str | None = None  # e.g. "#FFFFFF" (from archive/library file)
    layer_height: float | None = None  # e.g. 0.2 (from archive/library file)
    nozzle_diameter: float | None = None  # e.g. 0.4 (from archive/library file)
    sliced_for_model: str | None = None  # e.g. "P1S" (from archive/library file)
    # Build plate type (e.g. "Textured PEI Plate") so the user knows which
    # plate to mount on the printer (#1281). Per-plate accurate on multi-plate
    # 3MFs: when `plate_id` is set, the value is the matching plate's
    # `curr_bed_type` rather than the archive-level first-plate default.
    bed_type: str | None = None
    # True when the source archive carries the slicer's own live-resolved
    # AMS-slot pick (extra_data.slicer_ams_mapping) *and* it was resolved
    # against this row's own printer — the only case where dispatch actually
    # reuses that exact physical spool instead of the scheduler re-deriving one
    # from the file's static type/color.
    archive_has_slicer_ams_mapping: bool = False

    # User tracking (Issue #206)
    created_by_id: int | None = None
    created_by_username: str | None = None

    # Batch grouping
    batch_id: int | None = None
    batch_name: str | None = None

    # Cross-model alternatives (#671), in priority order. Empty for every
    # ordinary item. Present until dispatch resolves one onto the row, after
    # which library_file_id / target_model name the candidate that actually ran.
    variants: list[QueueVariantSummary] = []

    # Shortest-job-first scheduling
    been_jumped: bool = False

    # Auto-print G-code injection
    gcode_injection: bool = False
    cleanup_library_after_dispatch: bool = False

    # H2C dual-nozzle-rack slicer pick (#1780). Surface for any future
    # "edit print → choose nozzle" UI; null on every model except O1C2
    # uploads from BambuStudio.
    nozzle_mapping: list[int] | None = None
    # Which rack position each filament group prints from (#1784), as
    # {group_id: 1-based position}. The operator's pick, re-checked against the
    # live rack at dispatch; null means "assign them for me".
    nozzle_rack_choice: dict[int, int] | None = None

    class Config:
        from_attributes = True


class PrintQueueReorderItem(BaseModel):
    id: int
    position: int


class PrintQueueReorder(BaseModel):
    items: list[PrintQueueReorderItem]

    @model_validator(mode="after")
    def _validate_positions_unique(self) -> "PrintQueueReorder":
        """Reject reorder requests with duplicate positions in the payload
        (#1625-followup).

        The /reorder route is the drag-drop renumber path on the queue UI;
        a well-behaved client sends a contiguous renumbering of a single
        printer's pending queue. A buggy client that sends two items at
        the same position would leave the queue in an inconsistent state
        (scheduler's ORDER BY (printer_id, position) ties get broken by
        physical row order). Fail closed at the schema boundary so the
        bug is caught before any DB mutation.

        Uniqueness is enforced WITHIN THE PAYLOAD only — cross-printer
        reorders that intentionally share positions across different
        printer queues are a non-goal of the drag-drop UI, so this is the
        right scope.
        """
        positions = [it.position for it in self.items]
        if len(positions) != len(set(positions)):
            duplicates = sorted({p for p in positions if positions.count(p) > 1})
            raise ValueError(f"Duplicate positions in reorder request: {duplicates}")
        return self


class PrintQueueBulkUpdate(BaseModel):
    """Bulk update multiple queue items with the same values."""

    item_ids: list[int]
    # Fields to update (all optional - only set fields are applied)
    printer_id: int | None = None
    scheduled_time: datetime | None = None
    require_previous_success: bool | None = None
    auto_off_after: bool | None = None
    manual_start: bool | None = None
    # Print options
    bed_levelling: TriState | None = None
    flow_cali: TriState | None = None
    vibration_cali: bool | None = None
    layer_inspect: bool | None = None
    timelapse: bool | None = None
    use_ams: bool | None = None
    nozzle_offset_cali: TriState | None = None
    confirm_outcome: bool | None = None
    preheat_override: Literal["inherit", "on", "off"] | None = None
    preheat_chamber_target_override: int | None = Field(default=None, ge=0, le=MAX_CHAMBER_TEMP_C)
    # Auto-print G-code injection
    gcode_injection: bool | None = None
    cost_center_id: int | None = None
    estimated_cost: float | None = None


class PrintQueueBulkUpdateResponse(BaseModel):
    """Response for bulk update operation."""

    updated_count: int
    skipped_count: int  # Items that were not pending
    message: str


class PrintBatchPlateTarget(BaseModel):
    """How many runs of one plate an order wants (#342).

    ``plate_id`` is the plate index inside the source 3MF, or null for a
    single-plate file — matching ``PrintQueueItem.plate_id``. A target of 0 is
    legal and means "this plate is not required (yet)".
    """

    plate_id: int | None = None
    plate_name: str | None = None
    quantity_target: int = Field(default=1, ge=0, le=999)
    sort_order: int = 0


class PrintBatchCreate(BaseModel):
    """Create a batch, either empty (multi-plate pre-batch flow) or by
    assigning existing pending queue items into it (manual "Group as batch")."""

    name: str
    archive_id: int | None = None
    library_file_id: int | None = None
    # Existing pending queue items to assign to this batch. None / empty for
    # the empty-batch flow (client passes the returned id on subsequent
    # addToQueue calls).
    item_ids: list[int] | None = None
    # Per-plate targets. Omitted entirely by the pre-#342 flows, which produce
    # a batch that reports progress but owes nothing.
    plates: list[PrintBatchPlateTarget] | None = None
    # Planning metadata. Projects own the heavier fields (BOM, attachments,
    # tags); these two are the ones that are useless without a Project to
    # hang them on, so the order carries them directly.
    project_id: int | None = None
    due_date: datetime | None = None
    notes: str | None = None
    # The external record this batch fulfils, for integrations. ``external_ref``
    # is unique within ``external_source``: creating a second batch with the
    # same pair is a 409, which makes a retried create safe.
    external_source: str | None = Field(default=None, min_length=1, max_length=32, pattern=r"^[a-z0-9_-]+$")
    external_ref: str | None = Field(default=None, min_length=1, max_length=255)

    @model_validator(mode="after")
    def _external_link_is_complete(self) -> "PrintBatchCreate":
        # A ref without its source can't be looked up, and a source without a
        # ref would escape the uniqueness guarantee (NULLs never collide).
        if (self.external_source is None) != (self.external_ref is None):
            raise ValueError("external_source and external_ref must be given together")
        return self


class PrintBatchUpdate(BaseModel):
    """Edit an order's header or its per-plate targets while it runs.

    Every field is optional; ``plates`` replaces the full target set when
    given, so a plate omitted from the list has its target row removed.
    """

    name: str | None = None
    status: Literal["active", "cancelled"] | None = None
    plates: list[PrintBatchPlateTarget] | None = None
    project_id: int | None = None
    due_date: datetime | None = None
    notes: str | None = None


class PrintBatchDispatchRequest(BaseModel):
    """Create queue items for the runs an order still owes."""

    # Restrict to one plate. Null is a legitimate plate_id (single-plate file),
    # so the caller opts in explicitly rather than us inferring from null.
    plate_id: int | None = None
    only_plate: bool = False
    # Cap on how many items to create across all plates. None = everything owed.
    limit: int | None = Field(default=None, ge=1, le=999)


class PrintBatchUngroupResponse(BaseModel):
    """Response after ungrouping a batch."""

    ungrouped_count: int
    message: str


class PrintBatchPlateProgress(BaseModel):
    """Per-plate progress within a batch."""

    plate_id: int | None = None
    plate_name: str | None = None
    quantity_target: int = 0
    dispatched: int = 0
    remaining: int = 0
    pending_count: int = 0
    printing_count: int = 0
    completed_count: int = 0
    failed_count: int = 0
    cancelled_count: int = 0
    skipped_count: int = 0
    # Measured from finished runs, never estimated from the file. Null until
    # at least one run of this plate has produced a cost.
    actual_cost: float | None = None
    estimated_remaining_cost: float | None = None
    filament_used_grams: float | None = None
    print_time_seconds: int = 0
    # False when this plate owes runs but has no queue item left to clone
    # their configuration from, so offering to queue it would only fail.
    can_dispatch: bool = False


class PrintBatchResponse(BaseModel):
    """Response for a print batch with progress stats."""

    id: int
    name: str
    archive_id: int | None = None
    library_file_id: int | None = None
    quantity: int
    status: str
    created_at: UTCDatetime
    completed_at: UTCDatetime | None = None
    created_by_id: int | None = None
    created_by_username: str | None = None
    project_id: int | None = None
    due_date: UTCDatetime | None = None
    notes: str | None = None
    external_source: str | None = None
    external_ref: str | None = None
    # Derived counts
    pending_count: int = 0
    printing_count: int = 0
    completed_count: int = 0
    failed_count: int = 0
    cancelled_count: int = 0
    skipped_count: int = 0
    # Planning roll-up. has_targets is false for batches created before
    # per-plate targets existed: they report progress but owe nothing, and the
    # dispatch endpoint is a no-op for them.
    has_targets: bool = False
    target_count: int = 0
    remaining_count: int = 0
    # Of ``remaining_count``, how many runs can actually be queued. Lower when
    # a plate's last queue item was deleted (#2960).
    dispatchable_count: int = 0
    actual_cost: float | None = None
    estimated_remaining_cost: float | None = None
    filament_used_grams: float | None = None
    print_time_seconds: int = 0
    plates: list[PrintBatchPlateProgress] = []

    class Config:
        from_attributes = True