"""Stage runner with an input-hash cache."""
from __future__ import annotations

import hashlib
import importlib
import os
import time
from dataclasses import dataclass, field
from pathlib import Path

import numpy as np

from . import config as C
from .grid import Grid

STAGES = ["grid", "sketch", "plates", "crust", "elevation", "erosion", "climate",
          "hydrology", "seabed", "environment", "ice", "fields", "render"]


class StageError(RuntimeError):
    pass


@dataclass
class Ctx:
    root: Path
    cfg: dict
    tect: dict
    res: int
    data: dict = field(default_factory=dict)
    grid: Grid | None = None
    out_dir: Path | None = None        # render: out/r<res> unless set (an era writes out/r<res>/eras/<era>)
    preview_dir: Path | None = None
    low_memory: bool = False           # trade speed for a lower memory peak; never changes the results

    @property
    def seed(self) -> int:
        return int(self.cfg["build"]["seed"])

    def need(self, *keys):
        missing = [k for k in keys if k not in self.data]
        if missing:
            raise StageError(f"missing inputs {missing}: run the stage that produces them first")
        return [self.data[k] for k in keys]


def inputs_key(root: Path, res: int) -> str:
    h = hashlib.sha256(str(res).encode())
    files = []
    for sub, pat in (("config", "*.toml"), ("masks", "*.png"), ("sketch", "*.png")):
        files += sorted(p for p in (root / sub).glob(pat) if p.name != C.ERAS_FILE)   # eras: their own key
    files += sorted(Path(__file__).resolve().parent.glob("*.py"))
    for p in files:
        h.update(p.name.encode())
        h.update(p.read_bytes())
    return h.hexdigest()[:16]


ALIGN = 64


def save_npz_aligned(path, /, **arrays) -> None:
    """np.savez(path, **arrays), but each array's data starts at a multiple of ALIGN bytes in the file (the local zip
    header gets a padding extra field, as zipalign does): an ordinary .npz for np.load, whose arrays npz_maps can
    map in place. Alignment matters for more than speed: numpy sums 8-byte-misaligned data in buffered chunks,
    i.e. in another order — mapped misaligned inputs would change the last bits of results."""
    import io
    import struct
    import zipfile
    from numpy.lib import format as F
    with zipfile.ZipFile(path, "w", compression=zipfile.ZIP_STORED, allowZip64=True) as zf:
        for name, v in arrays.items():
            v = np.asarray(v)
            if v.dtype.hasobject:
                raise ValueError(f"save_npz_aligned: {name} has object dtype")
            head = io.BytesIO()
            d = F.header_data_from_array_1_0(v)
            try:
                F.write_array_header_1_0(head, d)
            except ValueError:
                head = io.BytesIO()
                F.write_array_header_2_0(head, d)
            info = zipfile.ZipInfo(f"{name}.npy", date_time=(1980, 1, 1, 0, 0, 0))
            info.compress_type = zipfile.ZIP_STORED
            start = zf.fp.tell() + 30 + len(info.filename.encode()) + 20 + len(head.getvalue())   # 20: zip64 field
            pad = -start % ALIGN
            if 0 < pad < 4:                                          # an extra field is at least its 4-byte header
                pad += ALIGN
            if pad:
                info.extra = struct.pack("<HH", 0xA1A1, pad - 4) + bytes(pad - 4)
            with zf.open(info, "w", force_zip64=True) as m:
                m.write(head.getvalue())
                _write_data(m, v)


def _write_data(m, v) -> None:
    """The array's bytes (C order, or Fortran order for an F-contiguous array, as np.save) in 16 MB pieces."""
    flat = v.T.reshape(-1) if (v.flags.f_contiguous and not v.flags.c_contiguous) else np.ascontiguousarray(v).reshape(-1)
    step = max(1, (16 << 20) // max(v.itemsize, 1))
    for i in range(0, flat.size, step):
        m.write(flat[i:i + step].tobytes())


def npz_maps(f: Path) -> dict:
    """The arrays of an uncompressed .npz (np.savez) mapped from the file, copy-on-write: plain writable arrays with
    the same values, whose pages the OS reads on use and can drop again (writes stay private, the file never
    changes). Members that can't be mapped (compressed, object dtype) are read into memory as np.load would."""
    import mmap
    import struct
    import zipfile
    out = {}
    with open(f, "rb") as fh, zipfile.ZipFile(fh) as zf:
        mm = mmap.mmap(fh.fileno(), 0, access=mmap.ACCESS_COPY)
        for info in zf.infolist():
            name = info.filename[:-4] if info.filename.endswith(".npy") else info.filename
            ok = info.compress_type == zipfile.ZIP_STORED
            if ok:
                fh.seek(info.header_offset)
                local = fh.read(30)
                n_name, n_extra = struct.unpack("<HH", local[26:30])
                fh.seek(info.header_offset + 30 + n_name + n_extra)
                version = np.lib.format.read_magic(fh)
                read_header = {(1, 0): np.lib.format.read_array_header_1_0,
                               (2, 0): np.lib.format.read_array_header_2_0}.get(version)
                ok = read_header is not None
            if ok:
                shape, fortran, dtype = read_header(fh, max_header_size=1 << 20)
                ok = not dtype.hasobject
                ok = fh.tell() % ALIGN == 0                         # misaligned: read (see save_npz_aligned)
            if ok:
                count = int(np.prod(shape, dtype=np.int64))
                a = np.frombuffer(mm, dtype=dtype, count=count, offset=fh.tell()) if count else np.empty(0, dtype)
                out[name] = a.reshape(shape, order="F" if fortran else "C")
            else:
                with zf.open(info) as m:
                    out[name] = np.lib.format.read_array(m, allow_pickle=False)
    return out


def _after(ctx: Ctx, name: str) -> None:
    if name == "grid":
        ctx.grid = Grid.from_arrays(ctx.data, ctx.res, float(ctx.cfg["planet"]["radius_km"]))


def build(root: Path, res: int, start: str | None = None, stop: str | None = None, log=print,
          low_memory: bool = False) -> Ctx:
    cfg, tect = C.load(root)
    ctx = Ctx(root, cfg, tect, res, low_memory=low_memory)
    cache = root / "out" / "cache" / f"r{res}"
    cache.mkdir(parents=True, exist_ok=True)
    key = inputs_key(root, res)
    stages = STAGES[: STAGES.index(stop) + 1] if stop else STAGES
    forced = False
    for name in stages:
        forced = forced or name == start
        f = cache / f"{name}.npz"
        t0 = time.time()
        if not forced and f.exists():
            with np.load(f, allow_pickle=False) as z:
                hit = str(z["_key"]) == key
                if hit and not ctx.low_memory:
                    ctx.data.update({k: z[k] for k in z.files if k != "_key"})
            if hit:
                if ctx.low_memory:
                    ctx.data.update({k: v for k, v in npz_maps(f).items() if k != "_key"})
                _after(ctx, name)
                log(f"{name}: cached")
                continue
        forced = True
        out = importlib.import_module(f"mapgen.{name}").run(ctx)
        tmp = f.with_name(f"{f.stem}.tmp-{os.getpid()}.npz")
        save_npz_aligned(tmp, _key=np.array(key), **out)
        os.replace(tmp, f)                  # never truncated in place: maps of the old file stay valid
        if ctx.low_memory:                  # fields kept on disk from here on (the cache file just written)
            maps = npz_maps(f)
            out = {k: maps.get(k, v) if isinstance(v, np.ndarray) else v for k, v in out.items()}
        ctx.data.update(out)
        _after(ctx, name)
        log(f"{name}: {time.time() - t0:.1f}s")
    return ctx