"""Background processing for staged uploads.

Each staged upload runs through three phases, in batches of 75 (the same
lookup size the original app used for its e621 MD5 cache command):

1. e621 MD5 lookup — one ``posts.json`` query per round; byte-identical
   matches are imported straight into the library (``auto_md5``).
2. Local visual similarity — perceptual hashes are compared against the
   whole library once per round.
3. e621 IQDB — reverse-image search for whatever is still unresolved.

The pipeline runs in a daemon thread started on demand (like the download and
match scans), so the browser can navigate away and the work keeps going.
Progress and pause/error state live in the ``UploadRun`` row; per-file state
lives on ``TempUpload``. Rows are claimed with ``SELECT ... FOR UPDATE SKIP
LOCKED`` so several gunicorn workers cannot process the same file, and stale
claims left by a recycled worker are reaped and picked up again.
"""

import logging
import threading
import time
from datetime import timedelta

from django.conf import settings
from django.contrib.auth import get_user_model
from django.db import connection, transaction
from django.db.models import F, Q
from django.utils import timezone

from . import e621, services
from .models import TempUpload, UploadRun

logger = logging.getLogger(__name__)

# Same batch size as the original app's e621 cache command.
MD5_BATCH_SIZE = 75
# Rows one worker round claims; also the MD5 query size.
CLAIM_SIZE = MD5_BATCH_SIZE
# A claimed row is assumed dead after this long and is queued again.
STALE_CLAIM_AFTER = timedelta(minutes=15)
# A run whose heartbeat stopped this long ago can be taken over.
STALE_RUN_AFTER = timedelta(minutes=15)
# Per-row failures before the pipeline stops retrying automatically.
MAX_ATTEMPTS = 3
# Round-level e621 retries before the run is paused.
ROUND_ATTEMPTS = 3
ROUND_RETRY_SECONDS = 20

WORK_STATUSES = (TempUpload.STATUS_PENDING, TempUpload.STATUS_VISUAL_MATCH)
VIDEO_RE = r"\.(mp4|webm)$"

# A staged upload still needs work when any phase has not run yet. IQDB is
# skipped for videos, which never get iqdb_data, so they must not stay
# "outstanding" forever.
OUTSTANDING_Q = (
    Q(e621_checked_at__isnull=True)
    | Q(visual_checked_at__isnull=True)
    | (Q(iqdb_data__isnull=True) & ~Q(original_filename__iregex=VIDEO_RE))
)

_running_lock = threading.Lock()
_running_users: set[int] = set()


class PipelinePaused(Exception):
    """A round-level failure that should pause the run instead of failing rows."""


def is_video(filename):
    return bool(filename) and filename.lower().endswith((".mp4", ".webm"))


def is_finished(temp):
    """True when every phase this file needs has run."""
    if temp.status == TempUpload.STATUS_COMPLETED:
        return True
    if temp.e621_checked_at is None or temp.visual_checked_at is None:
        return False
    return is_video(temp.original_filename) or temp.iqdb_data is not None


def outstanding_queryset(user):
    return (
        TempUpload.objects.filter(user=user, status__in=WORK_STATUSES)
        .filter(OUTSTANDING_Q)
        .filter(attempts__lt=MAX_ATTEMPTS)
    )


def count_outstanding(user):
    return outstanding_queryset(user).count()


def count_failed(user):
    return (
        TempUpload.objects.filter(user=user, status__in=WORK_STATUSES)
        .filter(attempts__gte=MAX_ATTEMPTS)
        .count()
    )


def waiting_counts(user):
    """How many files are left per phase (phases overlap by design)."""
    base = TempUpload.objects.filter(
        user=user, status__in=WORK_STATUSES, attempts__lt=MAX_ATTEMPTS
    )
    return {
        "md5": base.filter(e621_checked_at__isnull=True).count(),
        "visual": base.filter(visual_checked_at__isnull=True).count(),
        "iqdb": (
            base.filter(iqdb_data__isnull=True)
            .exclude(original_filename__iregex=VIDEO_RE)
            .count()
        ),
    }


def status_payload(user):
    """Cheap state for the shell/upload page to poll."""
    run = UploadRun.objects.filter(user=user).first()
    outstanding = count_outstanding(user)
    failed = count_failed(user)
    status = run.status if run is not None else UploadRun.STATUS_IDLE
    total = run.total if run is not None else 0
    processed = run.processed if run is not None else 0
    # A paused run with nothing left to do is not "active" (the user may have
    # resolved or discarded the failed rows); failed rows stay visible until
    # they are retried or dismissed.
    active = (
        outstanding > 0 or failed > 0 or status == UploadRun.STATUS_RUNNING
    )
    return {
        "status": status,
        "active": active,
        "phase": run.phase if run is not None else "",
        "total": max(total, processed + failed),
        "processed": processed,
        "matched": run.matched if run is not None else 0,
        "failed": max(failed, run.failed if run is not None else 0),
        "error": run.error if run is not None else "",
        "outstanding": outstanding,
        "waiting": waiting_counts(user),
        "updated_at": run.updated_at.isoformat() if run is not None else None,
    }


def reap_stale_claims():
    """Queue rows left claimed by a recycled worker and pause dead runs."""
    cutoff = timezone.now() - STALE_CLAIM_AFTER
    released = TempUpload.objects.filter(claimed_at__lt=cutoff).update(
        claimed_at=None
    )
    paused = UploadRun.objects.filter(
        status=UploadRun.STATUS_RUNNING, updated_at__lt=cutoff
    ).update(
        status=UploadRun.STATUS_PAUSED,
        phase="",
        error="The worker stopped before finishing. Retry to resume.",
        updated_at=timezone.now(),
    )
    if released or paused:
        logger.info(
            "Reaped %s stale upload claims and %s dead upload runs", released, paused
        )
    return released, paused


def start_pipeline(user):
    """Start the pipeline for one user in a daemon thread (idempotent)."""
    if not getattr(settings, "UPLOAD_PIPELINE_AUTOSTART", True):
        return False
    if user is None or not getattr(user, "can_upload", False):
        return False
    user_id = int(user.pk)
    with _running_lock:
        if user_id in _running_users:
            return False
        _running_users.add(user_id)
    reap_stale_claims()
    thread = threading.Thread(target=_thread_entry, args=(user_id,), daemon=True)
    thread.start()
    return True


def _thread_entry(user_id):
    try:
        run_pipeline(user_id)
    except Exception:  # noqa: BLE001 - a thread must never crash the worker
        logger.exception("Upload pipeline for user %s crashed", user_id)
    finally:
        with _running_lock:
            _running_users.discard(user_id)
        connection.close()


def run_pipeline(user_id):
    user = get_user_model().objects.filter(pk=user_id).first()
    if user is None or not user.can_upload:
        return
    now = timezone.now()
    # Claim the run row so two gunicorn workers cannot own the same queue.
    with transaction.atomic():
        run, _ = UploadRun.objects.select_for_update().get_or_create(user=user)
        if (
            run.status == UploadRun.STATUS_RUNNING
            and run.updated_at is not None
            and run.updated_at > now - STALE_RUN_AFTER
        ):
            # Another worker owns this run.
            return

        # Reset the counters when a new queue starts cleanly; otherwise keep
        # accumulating so failed rows from an earlier pass stay visible.
        live_failed = count_failed(user)
        outstanding = count_outstanding(user)
        if run.status == UploadRun.STATUS_IDLE and live_failed == 0:
            run.total = outstanding
            run.processed = 0
            run.matched = 0
            run.failed = 0
        else:
            run.total = max(
                run.total or 0, run.processed + run.failed + outstanding
            )
            run.failed = max(run.failed, live_failed)
        run.status = UploadRun.STATUS_RUNNING
        run.phase = ""
        run.error = ""
        run.started_at = now
        run.save()

    try:
        while True:
            rows = claim_round(user)
            if not rows:
                break
            process_round(run, user, rows)
    except PipelinePaused as exc:
        run.status = UploadRun.STATUS_PAUSED
        run.phase = ""
        run.error = str(exc)
        run.save()
    except Exception as exc:  # noqa: BLE001 - surface crashes as a run error
        logger.exception("Upload pipeline for user %s failed", user_id)
        run.status = UploadRun.STATUS_ERROR
        run.phase = ""
        run.error = f"The upload pipeline stopped: {exc}"
        run.save()
    else:
        run.status = UploadRun.STATUS_IDLE
        run.phase = ""
        run.save()


def claim_round(user, size=CLAIM_SIZE):
    """Claim up to ``size`` outstanding rows for this worker."""
    now = timezone.now()
    with transaction.atomic():
        rows = list(
            TempUpload.objects.select_for_update(skip_locked=True)
            .filter(user=user, status__in=WORK_STATUSES)
            .filter(OUTSTANDING_Q)
            .filter(claimed_at__isnull=True, attempts__lt=MAX_ATTEMPTS)
            .order_by("created_at")[:size]
        )
        if rows:
            TempUpload.objects.filter(pk__in=[row.pk for row in rows]).update(
                claimed_at=now
            )
            for row in rows:
                row.claimed_at = now
    return rows


def process_round(run, user, rows):
    """Run every phase for one claimed round, then release/account the rows."""
    ids = [row.pk for row in rows]
    matched = 0
    try:
        matched += md5_phase(run, user, rows)
        rows = refresh(ids)
        visual_phase(run, user, rows)
        rows = refresh(ids)
        iqdb_phase(run, user, rows)
    finally:
        finalize_round(run, ids, matched)


def refresh(ids):
    return list(TempUpload.objects.filter(pk__in=ids))


def _save_run(run, **fields):
    for key, value in fields.items():
        setattr(run, key, value)
    run.save(
        update_fields=[*fields.keys(), "updated_at"]
    )


def md5_phase(run, user, rows):
    """One e621 MD5 batch query; matches are imported into the library."""
    targets = [row for row in rows if row.e621_checked_at is None]
    if not targets:
        return 0
    _save_run(
        run,
        phase=UploadRun.PHASE_MD5,
        total=run.processed + run.failed + count_outstanding(user),
    )
    posts = _e621_round(
        lambda: e621.check_md5_batch(user, [row.md5 for row in targets])
    )
    by_md5 = {}
    for post in posts.values():
        file_data = post.get("file") or {}
        md5 = str(file_data.get("md5") or "").strip().lower()
        if md5:
            by_md5[md5] = post

    matched = 0
    now = timezone.now()
    for row in targets:
        post = by_md5.get(str(row.md5).strip().lower())
        if post is None:
            TempUpload.objects.filter(pk=row.pk).update(
                e621_checked_at=now, pipeline_error="", updated_at=now
            )
            continue
        try:
            trimmed = services.trim_e621_post(post)
            if trimmed is None or not trimmed.get("id"):
                raise e621.E621Error("e621 returned an unexpected post payload.")
            TempUpload.objects.filter(pk=row.pk).update(
                e621_post_id=int(trimmed["id"]),
                e621_data=trimmed,
                resolution=TempUpload.RESOLUTION_AUTO_MD5,
                e621_checked_at=now,
                pipeline_error="",
                updated_at=now,
            )
            row.refresh_from_db()
            from .uploads import complete_temp_upload

            complete_temp_upload(row)
            matched += 1
        except Exception as exc:  # noqa: BLE001 - keep going for other files
            logger.exception("Could not auto-import staged upload %s", row.pk)
            record_failure(row, f"Could not finish the upload: {exc}")
    return matched


def visual_phase(run, user, rows):
    """Compare each row's perceptual hashes against the library once."""
    from .uploads import build_hash_index, match_hashes

    targets = [
        row
        for row in rows
        if row.visual_checked_at is None
        and row.status in WORK_STATUSES
        and row.file
    ]
    if not targets:
        return
    _save_run(run, phase=UploadRun.PHASE_VISUAL)
    index = build_hash_index()
    now = timezone.now()
    for row in targets:
        try:
            hashes = services.compute_visual_hashes(row.file.path)
            if not hashes:
                TempUpload.objects.filter(pk=row.pk).update(
                    visual_checked_at=now, pipeline_error="", updated_at=now
                )
                continue
            matches = match_hashes(hashes, index, user=user)
            update = {
                "visual_matches": matches,
                "visual_checked_at": now,
                "pipeline_error": "",
                "updated_at": now,
            }
            if matches and row.status == TempUpload.STATUS_PENDING:
                update["status"] = TempUpload.STATUS_VISUAL_MATCH
            TempUpload.objects.filter(pk=row.pk).update(**update)
        except Exception as exc:  # noqa: BLE001 - keep going for other files
            logger.exception("Visual similarity failed for %s", row.pk)
            record_failure(row, f"Visual similarity failed: {exc}")


def iqdb_phase(run, user, rows):
    """Reverse-image search every unresolved image, one e621 query each."""
    targets = [
        row
        for row in rows
        if row.iqdb_data is None
        and row.status in WORK_STATUSES
        and row.file
        and not is_video(row.original_filename)
    ]
    if not targets:
        return
    _save_run(run, phase=UploadRun.PHASE_IQDB)
    heartbeat_at = time.monotonic()
    for row in targets:
        # Keep the run row fresh: a 75-file IQDB round takes minutes and must
        # not look like a dead worker to another request.
        if time.monotonic() - heartbeat_at > 30:
            UploadRun.objects.filter(pk=run.pk).update(updated_at=timezone.now())
            heartbeat_at = time.monotonic()
        try:
            raw = e621.iqdb_search(user, row.file.path)
            results = normalize_iqdb_results(user, raw)
        except e621.E621AuthError as exc:
            record_failure(row, str(exc))
            raise PipelinePaused(
                "e621 rejected the credentials — fix them in Account and retry."
            ) from exc
        except e621.E621RateLimited as exc:
            record_failure(row, str(exc))
            raise PipelinePaused(
                "e621 is throttling IQDB right now; the queue will resume."
            ) from exc
        except Exception as exc:  # noqa: BLE001 - keep going for other files
            logger.exception("IQDB search failed for %s", row.pk)
            record_failure(row, f"IQDB search failed: {exc}")
            continue
        now = timezone.now()
        update = {
            "iqdb_data": results,
            "pipeline_error": "",
            "updated_at": now,
        }
        if results and row.status == TempUpload.STATUS_PENDING:
            update["status"] = TempUpload.STATUS_VISUAL_MATCH
        TempUpload.objects.filter(pk=row.pk).update(**update)


def record_failure(row, message):
    """Count one failed attempt against a row and queue it for a retry."""
    TempUpload.objects.filter(pk=row.pk).update(
        attempts=F("attempts") + 1,
        pipeline_error=str(message)[:2000],
        claimed_at=None,
        updated_at=timezone.now(),
    )


def finalize_round(run, ids, matched):
    """Account finished/failed rows and release the rest of the claims."""
    rows = refresh(ids)
    finished = {row.pk for row in rows if is_finished(row)}
    failed = {row.pk for row in rows if row.attempts >= MAX_ATTEMPTS}
    # Release every claim: finished rows must not keep looking "processing"
    # to the board, and unfinished rows are re-queued for the next run.
    release = [row.pk for row in rows if row.claimed_at is not None]
    if release:
        TempUpload.objects.filter(pk__in=release).update(claimed_at=None)
    _save_run(
        run,
        processed=run.processed + len(finished),
        failed=run.failed + len(failed - finished),
        matched=run.matched + matched,
    )


def _e621_round(task):
    """Run a round-level e621 call, retrying through rate limits."""
    last_error = None
    for attempt in range(ROUND_ATTEMPTS):
        try:
            return task()
        except e621.E621AuthError:
            raise
        except (e621.E621RateLimited, e621.E621Error) as exc:
            last_error = exc
            if attempt + 1 >= ROUND_ATTEMPTS:
                break
            delay = ROUND_RETRY_SECONDS * (attempt + 1)
            logger.info("e621 round failed (%s); retrying in %ss", exc, delay)
            time.sleep(delay)
    raise PipelinePaused(
        f"e621 is not answering right now ({last_error}); the queue will resume."
    ) from last_error


def flatten_tag_preview(tags, limit=8):
    """First few tag names from a modern post payload, like the SPA shows."""
    if not isinstance(tags, dict):
        return []
    out = []
    for values in tags.values():
        if not isinstance(values, list):
            continue
        for tag in values:
            if isinstance(tag, str) and tag not in out:
                out.append(tag)
                if len(out) >= limit:
                    return out
    return out


def _legacy_iqdb_post(entry):
    """Unwrap the post payload embedded in a legacy IQDB match."""
    post = entry.get("post")
    if not isinstance(post, dict):
        return {}
    inner = post.get("posts")
    return inner if isinstance(inner, dict) else post


def normalize_iqdb_results(user, raw_results):
    """Shape legacy IQDB matches like the SPA's E621IqdbCandidate entries.

    The IQDB payload carries little post data, so candidates are enriched
    with one batched ``id:`` lookup before they are stored.
    """
    candidates = []
    for entry in (raw_results or [])[:10]:
        if not isinstance(entry, dict):
            continue
        post = _legacy_iqdb_post(entry)
        post_id = entry.get("post_id")
        if not isinstance(post_id, int):
            post_id = post.get("id")
        score = entry.get("score")
        candidates.append(
            {
                "post_id": post_id if isinstance(post_id, int) else None,
                "score": float(score) if isinstance(score, (int, float)) else None,
                "preview_url": None,
                "rating": (
                    post.get("rating") if isinstance(post.get("rating"), str) else None
                ),
                "md5": post.get("md5") if isinstance(post.get("md5"), str) else None,
                "score_total": (
                    post.get("score") if isinstance(post.get("score"), int) else None
                ),
                "fav_count": (
                    post.get("fav_count")
                    if isinstance(post.get("fav_count"), int)
                    else None
                ),
                "width": (
                    post.get("image_width")
                    if isinstance(post.get("image_width"), int)
                    else None
                ),
                "height": (
                    post.get("image_height")
                    if isinstance(post.get("image_height"), int)
                    else None
                ),
                "tags_preview": [],
            }
        )

    ids = [entry["post_id"] for entry in candidates if entry["post_id"]]
    if not ids:
        return services.sanitize_iqdb_results(candidates)

    try:
        posts = e621.fetch_posts_by_ids(user, ids)
    except e621.E621Error as exc:
        # Candidates without enrichment still show up; keep them.
        logger.info("Could not enrich IQDB candidates: %s", exc)
        posts = []
    by_id = {post.get("id"): post for post in posts}

    for entry in candidates:
        post = by_id.get(entry["post_id"])
        if not isinstance(post, dict):
            continue
        file_data = post.get("file") or {}
        preview = post.get("preview") or {}
        score = post.get("score") or {}
        entry["preview_url"] = preview.get("url") or entry["preview_url"]
        entry["rating"] = post.get("rating") or entry["rating"]
        entry["md5"] = file_data.get("md5") or entry["md5"]
        if isinstance(score, dict):
            entry["score_total"] = score.get("total")
        entry["fav_count"] = post.get("fav_count")
        entry["width"] = file_data.get("width")
        entry["height"] = file_data.get("height")
        entry["tags_preview"] = flatten_tag_preview(post.get("tags"))

    return services.sanitize_iqdb_results(candidates)