"""Shared frame extraction for Stage D (caption + AuroraCap runners).

Contract (unified across all stages):
  - indices = round(linspace(0, n_frames-1, 32)) over meta.json n_frames
  - decode via decord -> cv2 -> ffmpeg-select fallback
  - JPEG q=85, long side capped at 768px
  - single_frame condition = THE MIDDLE FRAME = round((n_frames-1)/2)
    (= sample_indices(n_frames, 1); the data contract and stage_e1_api's
    remote extractor use this rule — an earlier version of this module took
    position 16 of the 32-index list, round(16*(n-1)/31), which drifts off
    the true middle)

frames_for_hash() deduplicates repeated indices (videos with n_frames < 32
produce duplicate indices); callers can report len(result) as n_frames_used.
Dependency-light on purpose: json/PIL only; decord/cv2 optional.
"""
import io
import json
import os
import subprocess
import tempfile

from PIL import Image

N_FRAMES_DEFAULT = 32
LONG_SIDE = 768
JPEG_QUALITY = 85


def sample_indices(n_frames, n=N_FRAMES_DEFAULT):
    """round(linspace(0, n_frames-1, n)) without numpy. May contain duplicates."""
    if n_frames <= 0:
        raise ValueError("n_frames must be positive")
    if n == 1:
        return [round((n_frames - 1) / 2)]
    return [round(i * (n_frames - 1) / (n - 1)) for i in range(n)]


def _resize(img):
    w, h = img.size
    m = max(w, h)
    if m > LONG_SIDE:
        img = img.resize((max(1, round(w * LONG_SIDE / m)),
                          max(1, round(h * LONG_SIDE / m))), Image.LANCZOS)
    return img.convert("RGB")


def _decode_decord(path, idxs):
    import decord
    vr = decord.VideoReader(path, num_threads=2)
    avail = len(vr)
    uniq = sorted({min(i, avail - 1) for i in idxs})
    out = {}
    for c0 in range(0, len(uniq), 64):        # chunked: 600 frames of 720p as one batch = ~1.7 GB
        chunk = uniq[c0:c0 + 64]
        batch = vr.get_batch(chunk).asnumpy()
        for j, u in enumerate(chunk):
            out[u] = Image.fromarray(batch[j])
    return out


def _decode_cv2(path, idxs):
    import cv2
    cap = cv2.VideoCapture(path)
    if not cap.isOpened():
        raise RuntimeError(f"cv2 cannot open {path}")
    want = sorted(set(idxs))
    out, pos = {}, 0
    hi = want[-1]
    wi = 0
    while wi < len(want):
        ok = cap.grab()
        if not ok:
            break
        if pos == want[wi]:
            ok, fr = cap.retrieve()
            if not ok:
                break
            out[pos] = Image.fromarray(cv2.cvtColor(fr, cv2.COLOR_BGR2RGB))
            wi += 1
        pos += 1
        if pos > hi:
            break
    cap.release()
    if not out:
        raise RuntimeError(f"cv2 decoded 0/{len(want)} frames from {path}")
    last = max(out)
    for w in want:          # clamp missing tail indices to last decoded frame
        if w not in out:
            out[w] = out[last]
    return out


def _decode_ffmpeg(path, idxs):
    uniq = sorted(set(idxs))
    sel = "+".join(f"eq(n\\,{i})" for i in uniq)
    with tempfile.TemporaryDirectory() as td:
        cmd = [os.environ.get("FFMPEG_BIN", "ffmpeg"), "-y", "-v", "error",
               "-i", path, "-vf", f"select='{sel}'", "-vsync", "0",
               f"{td}/f_%05d.jpg"]
        subprocess.run(cmd, check=True, capture_output=True, timeout=1800)
        files = sorted(os.listdir(td))
        if not files:
            raise RuntimeError(f"ffmpeg extracted 0 frames from {path}")
        imgs = [Image.open(os.path.join(td, f)) for f in files]
        for im in imgs:
            im.load()
    out = {}
    for j, u in enumerate(uniq):    # ffmpeg may drop trailing frames; clamp
        out[u] = imgs[min(j, len(imgs) - 1)]
    return out


def _decode(path, idxs):
    errs = []
    for fn in (_decode_decord, _decode_cv2, _decode_ffmpeg):
        try:
            return fn(path, idxs)
        except ImportError:
            continue
        except Exception as e:
            errs.append(f"{fn.__name__}: {e}")
    raise RuntimeError("all decoders failed: " + " | ".join(errs))


def frames_for_hash(store, content_hash, n=N_FRAMES_DEFAULT, single=False):
    """Return list[PIL.Image] (RGB, long side <=768) for a normalized video.

    single=True -> [middle frame] = round((n_frames-1)/2), the contract rule
    shared with stage_e1_api's remote extractor.
    Otherwise the n sampled frames with duplicate indices removed
    (order preserved); len(result) == n unless n_frames < n.
    """
    d = os.path.join(store, "normalized", content_hash)
    meta = json.load(open(os.path.join(d, "meta.json")))
    if single:
        idxs = sample_indices(meta["n_frames"], 1)
    else:
        idxs = sample_indices(meta["n_frames"], n)
    keep = list(dict.fromkeys(idxs))            # dedupe, keep order
    decoded = _decode(os.path.join(d, "video.mp4"), keep)
    avail_max = max(decoded)
    return [_resize(decoded[min(i, avail_max)]) for i in keep]


def to_jpeg_bytes(img):
    buf = io.BytesIO()
    img.save(buf, format="JPEG", quality=JPEG_QUALITY)
    return buf.getvalue()


def to_data_url(img):
    import base64
    return "data:image/jpeg;base64," + base64.b64encode(to_jpeg_bytes(img)).decode()