blog/_posts/2026-10-01-quine.md

---
layout: post
title: 如何制作一个“完整”的博客压缩包？
tags: [压缩包, Quine, LZMA2, 7-Zip]
---

  让AI做出真正的“完整”将不再是难事……<!--more-->   

# 起因
  在上次[用AI制作了各种东西](/2026/09/01/vibe-coding2.html)之后，我已经完全理解了AI确实是无所不能的。既然如此，那就让它帮我解决曾经未能解决的事情吧？   
  去年，我为了让下载全站压缩包的按钮不断链，让这个压缩包也包含它本身而研究了[ZIP Quine](/2025/09/01/quine.html)，但限于DEFLATE的回溯窗口大小没能做到……但那是人做的东西，人还是太弱小了，现在换AI来试试，也许一切将变得不一样？   

# 制作基于LZMA2的博客压缩包
  首先，我把[Ruben Van Mello](https://github.com/ruvmello)写的那篇论文《[A Generator for Recursive Zip Files](https://www.mdpi.com/2076-3417/14/21/9797)》以及生成器[zip-quine-generator](https://github.com/ruvmello/zip-quine-generator)发给了AI，问它这个限制是不是真的，是不是真的无法创造出超过32KiB的ZIP Quine？没过多久它分析完了，告诉我确实存在这样的问题，但并不是无法解决的，最简单的办法就是换个回溯窗口更大的压缩算法。我看了一下它给我列出的几个算法，看起来LZMA2和zstd比较符合要求。不过zstd感觉不是很知名，一般的解压软件应该处理不了，所以我就选择让它基于LZMA2来制作了。   
  不过LZMA2只是算法，还得选个容器，考虑到7z算是最出名，而且LZMA2本来就是7-Zip的作者开发的，所以就直接让它做7z版本的了。另外因为[Nate Choe](https://github.com/NateChoe1)做了通过扩展欧几里得求逆元来计算CRC32的[PR](https://github.com/ruvmello/zip-quine-generator/pull/3)，所以我也告诉它要用这种方法在多项式时间内解出CRC32的值，而不是爆破。就这样AI花了两个小时左右成功把代码写出来了，效果非常完美，另外它还偷懒地将计算CRC32的算法改成了高斯消元法😆，因为7z格式有3个相互影响的CRC32值，用扩展欧几里得会更复杂一点，不过对7z来说不写入文件的CRC32也不影响，只是会不校验罢了，至少它还是按我要求做了……但其实这个问题也并不是完全不能用扩展欧几里得算法，后来我又强烈要求了一下，AI还是给我写出来了。以下是代码片段，有兴趣的人可以参考一下（不过这个看起来写的就是很复杂，所以我自己只用了高斯消元法）：   
```python
RU_POLY = 0x104C11DB7          # x^32+x^26+x^23+...+1（含 x^32 首项）


def _find_probe(p):
    ret = 0
    for i in range(64):
        if (1 << i) & p:
            ret = i
    return ret


def _mul_raw(p1, p2):
    """多项式乘法（无模）。"""
    ret = 0
    probe = _find_probe(p1)
    for i in range(64):
        if p2 & (1 << i):
            assert probe + i < 64, "多项式乘法溢出"
            ret ^= p1 << i
    return ret


def _poly_divmod(dividend, divisor):
    """多项式长除法，返回 (商, 余)。"""
    probe = _find_probe(divisor)
    probe_bit = 1 << probe
    quot = 0
    rem = dividend
    for i in range(63 - probe, -1, -1):
        if rem & (probe_bit << i):
            quot |= 1 << i
            rem ^= divisor << i
    return quot, rem


def _mul(p1, p2, mod):
    """p1*p2 % mod。"""
    return _poly_divmod(_mul_raw(p1, p2), mod)[1]


def _xgcd(p1, p2):
    """扩展欧几里得：返回 (k1,k2,gcd)，满足 p1*k1+p2*k2=gcd。"""
    if _find_probe(p1) < _find_probe(p2):
        k1, k2, g = _xgcd(p2, p1)
        return k2, k1, g
    if p2 == 0:
        return p1, 0, p1
    q, r = _poly_divmod(p1, p2)
    c1, c2, g = _xgcd(p2, r)
    return c2, c1 ^ _mul_raw(c2, q), g


def _minv(p, mod):
    """p 在环上的乘法逆元；不存在时返回 0。"""
    k1, _, g = _xgcd(p, mod)
    if g != 1:
        return 0
    return _poly_divmod(k1, mod)[1]


def _bitrev32(x):
    """32 位比特反转。CRC 的输出循环冗余（binascii 反射）↔ 本环（非反射）互为 bit-reverse。"""
    return int(format(x & 0xFFFFFFFF, "032b")[::-1], 2)


def _ring_pow_x(k):
    """环内 x^k mod P（P=RU_POLY），二进制幂 O(log k)。变量列就是单个环幂。"""
    res, base, mod, e = 1, 2, RU_POLY, k
    while e:
        if e & 1:
            res = _mul(res, base, mod)
        base = _mul(base, base, mod)
        e >>= 1
    return res


def solve_crc_system(files):
    """解析解 CRC 定点系统

    - 常数列     ：对“变量清零”的数据做一次 binascii.crc32，再 bit-reverse 32 位
                    （binascii 反射 CRC 与本环非反射 CRC 互为 bit-reverse，见 _bitrev32）。
    - 变量列     ：单个环幂 x^(32 + 8*(len-pos-4))，二进制幂 O(log N) 一步算出；
                    同一变量出现在多处时按位异或累加。
    各自 O(#rows) 次 CRC + 少量环幂即可建出整矩阵，Gauss 消元不变。
    """
    n = len(files)
    mod = RU_POLY
    matrix = [[0] * (n + 1) for _ in range(n)]

    for file in range(n):
        data = files[file][0]
        offsets = files[file][1]
        N = len(data)
        zero = bytearray(data)
        for pos in offsets:                      # 未知量占 4 字节，清零后求常数项
            zero[pos:pos + 4] = b"\x00\x00\x00\x00"
        matrix[file][n] = _bitrev32(crc32(bytes(zero)))
        for pos, vid in offsets.items():
            rest = N - pos - 4                    # 变量被 4 字节（x^32）+ 其后字节（x^8/个）推到底
            matrix[file][vid] ^= _ring_pow_x(32 + 8 * rest)
        matrix[file][file] ^= 1

    for sr in range(n):
        ex = sr
        while ex < n and matrix[ex][sr] == 0:
            ex += 1
        if ex == n:
            raise RuntimeError("CRC 多项式系统奇异 @row%d" % sr)
        if ex != sr:
            matrix[sr], matrix[ex] = matrix[ex], matrix[sr]
        inv = _minv(matrix[sr][sr], mod)
        for er in range(sr + 1, n):
            mult = _mul(inv, matrix[er][sr], mod)
            for ec in range(n + 1):
                matrix[er][ec] ^= _mul(mult, matrix[sr][ec], mod)

    res = [0] * n
    for row in range(n - 1, -1, -1):
        v = matrix[row][n]
        for col in range(row + 1, n):
            v ^= _mul(res[col], matrix[row][col], mod)
        res[row] = _mul(v, _minv(matrix[row][row], mod), mod)

    return [_impl_val(res[i]) for i in range(n)]

def _impl_val(math_val):
    imp = 0
    for bit in range(32):
        if math_val & (1 << bit):
            imp |= 1 << (31 - bit)
    return imp

class BlogQuine:
    def solve_crc(self, F, lay, seed):
        T, h, d = lay["T"], lay["h"], lay["d"]
        k, n_sub, crc_base = lay["k"], lay["n_sub"], lay["crc_base"]
        hoff = lay["total"] - h
        vout_f = lay["total"] - 2 * T
        hcopy = vout_f + (T - h)
        # 已知 CRC：seed + 各文件（quine 的是未知量 D）
        known = [crc32(seed)] + [crc32(data) for _, data in self.files]
        assert len(known) == n_sub - 1
        for i, e in enumerate(known):
            struct.pack_into("<I", F, hoff + crc_base + 4 * i, e)
            struct.pack_into("<I", F, hcopy + crc_base + 4 * i, e)
        # 未知量 D N S：D=整个文件、N=头部 F[hoff:hoff+h]、S=签名 F[12:32]
        dpos = crc_base + 4 * (n_sub - 1)
        ncopy = 32 + 3 * k + d                            # C1k 载荷里 F[0:35) 副本起点
        groups = [[hoff + dpos, hcopy + dpos],            # D 出现两处
                  [28, ncopy + 28],                        # N
                  [8, ncopy + 8]]                          # S

        # 构造 3 个“文件”喂给解析解系统：
        #   文件0 = 整个 F，三个未知量各自出现在 groups 两处
        #   文件1 = 头部块，只有 D 出现在相对 dpos（另一处 hcopy+dpos 在头外）
        #   文件2 = 签名块，只有 N 出现在相对 16（28-12）
        whole = bytes(F)
        hdr = bytes(F[hoff:hoff + h])
        sig = bytes(F[12:32])
        f0_off = {hoff + dpos: 0, hcopy + dpos: 0,
                  28: 1, ncopy + 28: 1,
                  8: 2, ncopy + 8: 2}
        f1_off = {dpos: 0}
        f2_off = {28 - 12: 1}
        vals = solve_crc_system([(whole, f0_off), (hdr, f1_off), (sig, f2_off)])

        for g in range(3):
            for p in groups[g]:
                F[p:p + 4] = struct.pack("<I", vals[g])
        real = (crc32(F), crc32(F[hoff:hoff + h]), crc32(F[12:32]))
        assert real == tuple(vals), "CRC 定点失败: %s != %s" % (real, vals)
        return vals
```

  于是我第一时间就把原来的TGZ压缩命令换掉，换成了AI给我写的[blogquine.py](https://github.com/Mabbs/mabbs.github.io/blob/master/_tools/blogquine.py)，现在就可以通过[这里](https://mayx.eu.org/MayxBlog.7z)下载到“完整”包含我博客所有内容的压缩包了。   
  不过唯一的问题就是这样做出来的压缩包并没有压缩😂，相当于给做成了普通的归档了。当然我的博客本身倒是不大，没压缩也多不了多少空间，但相比于能做出“完整”的效果来说，这点浪费的空间也是小问题了。   
## 基于博客压缩包的离线模式（2026.10.03更新）
  既然现在的AI什么都能做了，那上次我因为技术不足仅仅只是用[Service Worker做了个代理](/2025/08/01/sw-proxy.html)，现在也可以升级成下载全站之后让全站离线的功能吧？不过之前做的压缩包并没有压缩，导致整个压缩包有接近20MiB的大小，后来我仔细想了一下我的需求，我只是想让下载全站压缩包的按钮不断链，并没有说解压后的文件一定就必须是它本身，所以我只要用相同的文件名再压缩一次应该就可以了，这样既能满足我的想法，又可以让其他人下载的时候不会花费太多的时间。   
  在我直接压缩之后，整个压缩包占用大概9MiB的空间，其实我已经很满意了，不过压之前是18MiB，也就是说压缩率是50%……虽然也不是不能接受，但我在想这是不是合理的结果呢？我让AI分析了一下50%的压缩率正不正常，它看了一眼之后告诉我文本部分的10MiB压缩完之后有1MiB，图片因为压不动所以直接占用了8MiB😅，这时候我才意识到原来我一直存着一堆占着大量空间的垃圾，而且还是用的PNG/JPG这种压缩率很低的格式……考虑到兼容性和压缩效果，我把占用比较大的图片转换为了WebP格式，最终整个压缩包就只占用了4MiB的空间，一口气又节省了50%的空间。   
  最后做完对压缩包的处理之后，我直接让AI给我基于那个压缩包制作离线模式，它轻轻松松就[做出来](https://mayx.eu.org/offline.html)了，最终使用的是[libarchive库](https://github.com/nika-begiashvili/libarchivejs)，在启用离线模式之后整个网站的速度简直就是0延迟，点击就能瞬间跳转，效果算是相当不错了。   
## 受大佬启发制作了能压缩的7z Quine（2026.10.05更新）
  做完博客压缩包之后我突发奇想，虽然东西是AI做的，但也是在我的手中做出了世界上第一个LZMA2 Quine，那么如果我向全世界第一个制作ZIP Quine的人展示一下我的作品会怎么样呢？目前可以知道，世界上第一个制作ZIP Quine的人是[Erling Ellingsen](https://infosec.exchange/@steike)，所以我向他发了个帖子[展示了一下](https://infosec.exchange/@mayx/117385801954308033)。大佬不愧是大佬，一眼就能看出理论上能压缩的7z Quine是可以做出来的，对我来说，我是完全不知道7-Zip居然还支持链式编解码，能可以通过“double lzma2”的方式做到既可以自包含、又能真正被压缩的压缩包。既然大佬说理论上可以，那我自然是相信的，于是就让AI给我使劲折腾想办法把它做出来。在折腾了一晚上之后AI终于做出来了，真是强得可怕：   
```python
# ============================================================
# 双层 LZMA2 的 7z quine（"double lzma2"）
#
# F = S32 ‖ P ‖ H，folder 的 coder 链 = [LZMA2(外层), LZMA2(内层)]，
# 解码管线：P --外层--> I --内层--> U。
#
#   I = Cseg ‖ LBseg ‖ Mseg ‖ 0x00
#     Cseg : 真实 LZMA2 对 content 的压缩流（内容真正的压缩数据 C）
#     LBseg: 内层 store 链，载荷 = seed（seed 内含一份 C 的参照副本）
#     Mseg : 内层 match 链，输出 quine 区（= F 的逐字节副本）
#   U = content ‖ seed ‖ F
#
# 外层把 I 再压一遍：Cseg 用 store 链原样承载；seed 里的 C 参照副本与 Cseg
# 逐字节相同，被外层的 rep0 回溯匹配消掉，于是成品里只剩一份压缩数据。
# quine 区回引 P 的字节时，源全在 seed 里（C 副本 / 头样本表 / 机械串）。
# ============================================================
def lzma_chunk(tokens, out_pos):
    """编一个 LZMA chunk（0xC0: state+props reset，无 dict reset，无 end marker）。
    match token 的编码字节只取决于 (dist,len,pos)，与历史内容无关（不维护输出历史）。
    解压长度用 21 位（控制字节低 5 位存高 5 位），故单 chunk 输出上限 2 MiB。"""
    enc = LzmaEncoder()
    enc.pos = out_pos
    total = 0
    for t in tokens:
        if t[0] == "m":
            enc.match(t[1], t[2])
            total += t[2]
        else:
            enc.rep_match(t[1])
            total += t[1]
    data = enc.finish()
    u = total - 1
    c = len(data) - 1
    assert 0 <= u < (1 << 21) and 0 <= c < 65536, (total, len(data))
    hdr = bytes([0xC0 | ((u >> 16) & 0x1F)]) + (u & 0xFFFF).to_bytes(2, "big") + \
          (c & 0xFFFF).to_bytes(2, "big") + bytes([PROPS_BYTE])
    return hdr + data, total

LZ2_MAXU = 1 << 21                       # LZMA2 单个 LZMA chunk 的解压上限


def lzma2_raw(data, dict_size, preset=6):
    """FORMAT_RAW + LZMA2 压缩；去掉结尾 0x00 便于后面继续追加 chunk。"""
    c = lzma.LZMACompressor(
        format=lzma.FORMAT_RAW,
        filters=[{"id": lzma.FILTER_LZMA2, "dict_size": dict_size, "preset": preset}])
    out = c.compress(data) + c.flush()
    assert out and out[-1] == 0x00, "LZMA2 流应以 0x00 结尾"
    return out[:-1]


def split_len(n, cap):
    """按 cap 上限切分 n 字节。末片若为 1 字节则从前一片借 1（match 最短为 2）。"""
    Ls, rem = [], n
    while rem > cap:
        Ls.append(cap)
        rem -= cap
    if rem == 1 and Ls:
        Ls[-1] -= 1
        rem = 2
    Ls.append(rem)
    return Ls


class DoubleQuine(BlogQuine):
    """双层 LZMA2 版本：folder = [LZMA2(外层), LZMA2(内层)]。"""

    def entries(self):
        """U 的顺序是 内容文件… ‖ seed ‖ quine，条目顺序必须与之对应。"""
        ent = [{"name": r, "dir": isd} for r, isd in self.walk_entries]
        ent.append({"name": self.seed_name, "dir": False})
        ent.append({"name": self.quine_name, "dir": False})
        return ent

    # ---------- 头部：双 coder + BindPair ----------
    def build_header(self, n, total, d, entries, sub_sizes, size_I):
        n_sub = len(sub_sizes)
        N = len(entries)
        h = bytearray()
        h += b"\x01\x04"                                   # kHeader, kMainStreamsInfo
        h += b"\x06" + varint(0) + varint(1) + b"\x09" + varint(n) + b"\x00"
        h += b"\x07"                                       # kUnpackInfo
        h += b"\x0b" + varint(1) + b"\x00"                 # kFolder: 1, local
        h += varint(2)                                     # NumCoders = 2
        h += b"\x21\x21" + varint(1) + bytes([self.dict_prop_out])   # coder0 = 外层
        h += b"\x21\x21" + varint(1) + bytes([self.dict_prop_in])    # coder1 = 内层
        h += varint(1) + varint(0)             # BindPair = (InIndex=1, OutIndex=0)
        h += b"\x0c" + varint(size_I) + varint(d + total)  # 两个 coder 的输出大小
        h += b"\x00"
        h += b"\x08"                                       # SubStreamsInfo
        h += b"\x0d" + varint(n_sub)
        h += b"\x09" + b"".join(varint(s) for s in sub_sizes[:-1])
        h += b"\x0a" + b"\x01"
        crc_base = len(h)
        h += b"\x00" * (4 * n_sub)
        h += b"\x00\x00"
        h += b"\x05" + varint(N)                           # FilesInfo
        bits = bytearray((N + 7) // 8)
        for i, e in enumerate(entries):
            if e["dir"]:
                bits[i // 8] |= 1 << (7 - i % 8)
        h += b"\x0e" + varint(len(bits)) + bytes(bits)
        mt = b"\x01\x00" + struct.pack("<Q", self.mtime_ft) * N
        h += b"\x14" + varint(len(mt)) + mt
        names = bytearray(b"\x00")
        for e in entries:
            names += e["name"].encode("utf-16-le") + b"\x00\x00"
        h += b"\x11" + varint(len(names)) + bytes(names)
        attrs = b"".join(struct.pack("<I", 0x10 if e["dir"] else 0x20)
                         for e in entries)
        h += b"\x15" + varint(2 + len(attrs)) + b"\x01\x00" + attrs
        h += b"\x00\x00"
        return bytes(h), crc_base

    # ---------- 布局：三层坐标的不动点迭代 ----------
    def layout(self):
        content = self.content
        dc = len(content)
        dict_c = max(1 << 20, 1 << max(20, dc.bit_length()))
        C = lzma2_raw(content, dict_c)
        self._C = C                         # 内容压缩只做一次，finalize 复用
        lc = len(C)
        # 迭代变量：Y = plant 长度, H = 头部长度, M = Mseg 字节数
        Y, H, M = 96, 256, 256
        seen = set()
        for _ in range(200):
            ds = lc + 32 + H + Y            # seed = C副本‖S32‖H‖plant
            d = dc + ds
            Ls_LB = split_len(ds, CHUNK)
            lLB = 3 * len(Ls_LB) + ds
            off_in = lc + lLB
            M1 = M + 1                      # Mseg ‖ 内层流终止符 0x00
            Ls_M = split_len(M1, CHUNK)
            Li = off_in + M1
            self.dict_prop_out, _ = dict_prop_for(max(Li, 1 << 20))
            self.dict_prop_in, _ = dict_prop_for(d + 32 + H + 8192)
            st = self._build_streams(C, lc, ds, d, Ls_LB, lLB, off_in, Ls_M,
                                     M1, H)
            if st is None:
                Y += 8
                continue
            mseg = self._build_mseg(st, d, lc, ds, H, M)
            if mseg is None:
                Y += 8
                continue
            M_new = len(mseg)
            Y_new = len(st["hdr_bytes"]) + len(st["mech"]) + M_new + 2
            total = st["n"] + 32 + H
            file_sizes = [len(x) for _, x in self.files]
            sub_sizes = file_sizes + [ds] + [total]
            entries = self.entries()
            hdr, crc_base = self.build_header(st["n"], total, d, entries,
                                              sub_sizes, Li)
            H_new = len(hdr)
            key = (Y_new, H_new, M_new)
            if key in seen:                 # 再次见到同一组值 = 已收敛
                Y, H, M = Y_new, H_new, M_new
                break
            seen.add(key)
            Y, H, M = Y_new, H_new, M_new
        else:
            raise RuntimeError("double layout 不收敛")
        return {"Y": Y, "H": H, "M": M}

    # ---------- 定稿：用收敛后的 (Y, H, M) 重算全部结构 ----------
    def finalize(self, Y, H, M):
        content = self.content
        dc = len(content)
        C = self._C                         # layout 里已压缩过
        lc = len(C)
        ds = lc + 32 + H + Y
        d = dc + ds
        Ls_LB = split_len(ds, CHUNK)
        lLB = 3 * len(Ls_LB) + ds
        off_in = lc + lLB
        M1 = M + 1
        Ls_M = split_len(M1, CHUNK)
        Li = off_in + M1
        self.dict_prop_out, ds_out = dict_prop_for(max(Li, 1 << 20))
        self.dict_prop_in, ds_in = dict_prop_for(d + 32 + H + 8192)
        st = self._build_streams(C, lc, ds, d, Ls_LB, lLB, off_in, Ls_M, M1, H)
        mseg = self._build_mseg(st, d, lc, ds, H, M)
        assert len(mseg) == M, "Mseg %d != %d" % (len(mseg), M)
        total = st["n"] + 32 + H
        file_sizes = [len(x) for _, x in self.files]
        sub_sizes = file_sizes + [ds] + [total]
        entries = self.entries()
        hdr, crc_base = self.build_header(st["n"], total, d, entries,
                                          sub_sizes, Li)
        assert len(hdr) == H, "header %d != %d" % (len(hdr), H)
        plant = st["hdr_bytes"] + bytes(st["mech"]) + mseg + b"\x00\x00"
        assert len(plant) == Y, "plant %d != %d" % (len(plant), Y)
        return {"C": C, "lc": lc, "dc": dc, "ds": ds, "d": d, "Li": Li,
                "ochunks": st["ochunks"], "hdr_tab": st["hdr_tab"],
                "mseg": mseg, "M": M, "H": H, "n": st["n"], "total": total,
                "header": hdr, "crc_base": crc_base, "plant": plant,
                "dict_size_in": ds_in, "dict_size_out": ds_out,
                "n_sub": len(sub_sizes)}

    # ---------- 外层流 P 的构造 ----------
    def _build_streams(self, C, lc, ds, d, Ls_LB, lLB, off_in, Ls_M, M1, H):
        hdr_tab, hdr_idx = [], {}

        def hidx(b):
            assert len(b) == 3 and b[0] in (0x01, 0x02), b.hex()
            if b not in hdr_idx:
                hdr_idx[b] = len(hdr_tab)
                hdr_tab.append(b)
            return hdr_idx[b]

        ochunks = []
        f, io = 32, 0
        mech = bytearray()

        def put_lzma(tokens, ioff):
            blk, t = lzma_chunk(tokens, ioff)
            ochunks.append({"kind": "lzma", "foff": f, "size": len(blk),
                            "ioff": ioff, "olen": t, "bytes": blk,
                            "mech": len(mech)})
            mech.extend(blk)
            return len(blk), t

        def put_store(ioff, olen, hi, src):
            ochunks.append({"kind": "store", "foff": f, "size": 3 + olen,
                            "ioff": ioff, "olen": olen, "hdr": hi, "src": src})
            return 3 + olen

        # 段 1：store 链承载 Cseg（I[0:lc] = C 的字节；源 = seed 的 C 参照副本）
        Ls_C = split_len(lc, CHUNK)
        c_off = 0
        for L in Ls_C:
            f += put_store(io, L, hidx(store_hdr(L, first=(c_off == 0))),
                           ("seed", c_off))
            io += L
            c_off += L
        assert io == lc

        # 段 2：LBseg（I[lc : lc+lLB]）—— 内层 store 链，载荷 = seed
        lb_off = lc
        seed_off = 0
        for j, L in enumerate(Ls_LB):
            lb_hdr = store_hdr(L, first=False)
            if j == 0 or L != CHUNK:
                # 没有可回引的相同样本，用外层 store chunk 原样携带这 3 字节
                f += put_store(lb_off, 3, hidx(store_hdr(3, first=False)),
                               ("tab", hidx(lb_hdr)))
                io += 3
            else:
                # 与 chunk0 的头逐字节相同，直接从 I[lc:lc+3] 复制
                n, t = put_lzma([("m", lb_off - lc, 3)], lb_off)
                assert t == 3
                f += n
                io += 3
            # 载荷：C 参照副本区走 rep0 回溯匹配（去重发生处），其余走 store
            pay = lb_off + 3
            i = 0
            while i < L:
                if seed_off + i < lc:
                    a = min(L - i, lc - (seed_off + i), LZ2_MAXU)
                    dist = (pay + i) - (seed_off + i)
                    n, t = put_lzma(matches_for(dist, a), pay + i)
                    assert t == a
                    f += n
                    io += a
                    i += a
                else:
                    a = min(L - i, LZ2_MAXU)
                    f += put_store(pay + i, a, hidx(store_hdr(a, first=False)),
                                   ("seed", seed_off + i))
                    io += a
                    i += a
            lb_off += 3 + L
            seed_off += L
        assert lb_off == lc + lLB and io == lc + lLB

        # 段 3：store 链承载 Mseg ‖ 0x00（0x00 是内层流的终止符）
        m_off = 0
        for L in Ls_M:
            f += put_store(off_in + m_off, L,
                           hidx(store_hdr(L, first=False)), ("mseg", m_off))
            io += L
            m_off += L
        # 外层流自己的终止符 0x00
        ochunks.append({"kind": "term", "foff": f, "size": 1, "ioff": io,
                        "olen": 0, "bytes": b"\x00"})
        f += 1
        return {"ochunks": ochunks, "mech": mech, "hdr_tab": hdr_tab,
                "hdr_bytes": b"".join(hdr_tab), "n": f - 32}

    # ---------- 内层 Mseg：把 quine 区的每个 F 区段映射成 match 链 ----------
    def _build_mseg(self, st, d, lc, ds, H, M):
        dc = d - ds
        s_S32 = dc + lc                                  # seed 里 S32 副本
        s_H = dc + lc + 32                               # seed 里 H 副本
        s_tab = dc + lc + 32 + H                         # seed 里头样本表
        s_mech = s_tab + len(st["hdr_bytes"])            # seed 里机械串
        s_mseg = s_mech + len(st["mech"])                # seed 里 Mseg 副本
        total = st["n"] + 32 + H
        hoff = 32 + st["n"]
        segs = [(0, 32, s_S32)]                          # F[0:32) 签名头
        for c in st["ochunks"]:
            if c["kind"] == "store":
                segs.append((c["foff"], 3, s_tab + 3 * c["hdr"]))
                src = c["src"]
                if src[0] == "seed":
                    u = dc + src[1]
                elif src[0] == "tab":
                    u = s_tab + 3 * src[1]
                else:                                    # ("mseg", off)
                    u = s_mseg + src[1]
                segs.append((c["foff"] + 3, c["olen"], u))
            elif c["kind"] == "lzma":
                segs.append((c["foff"], c["size"], s_mech + c["mech"]))
            else:                                        # term：并入前一个载荷段
                pf, pl, pu = segs[-1]
                segs[-1] = (pf, pl + 1, pu)
        segs.append((hoff, H, s_H))                      # F[hoff:] 头部
        pos = 0
        for (fo, ln, u) in segs:
            assert fo == pos, "段不连续: %d != %d" % (fo, pos)
            assert ln >= 2, "段太短 %d @%d" % (ln, fo)
            pos += ln
        assert pos == total, "段总长 %d != total %d" % (pos, total)
        # 生成 match 链，按 2 MiB 上限切成多个 0xC0 chunk
        mseg = bytearray()
        out_pos = d
        cur, cur_len = [], 0
        chunks = []
        for (fo, ln, u) in segs:
            dist = (d + fo) - u
            assert 0 < dist, "dist=%d @%d" % (dist, fo)
            toks = matches_for(dist, ln)
            if cur_len + ln > LZ2_MAXU - MAX_MATCH:
                chunks.append((cur, out_pos, cur_len))
                out_pos += cur_len
                cur, cur_len = [], 0
            cur.extend(toks)
            cur_len += ln
        if cur:
            chunks.append((cur, out_pos, cur_len))
            out_pos += cur_len
        assert out_pos == d + total, "Mseg 输出 %d != %d" % (out_pos, d + total)
        for (toks, op, cl) in chunks:
            blk, t = lzma_chunk(toks, op)
            assert t == cl
            mseg.extend(blk)
        return bytes(mseg)

    # ---------- F 中承载 seed[soff] 的那个字节的偏移 ----------
    def _f_off_of_seed(self, lay, soff):
        """返回 (F 偏移, 该 store 载荷内从 soff 起还剩多少字节)。
        seed_head 超过 64 KiB 时会被切成多片，所以调用方要循环推进。"""
        for c in lay["ochunks"]:
            if c["kind"] == "store" and c["src"][0] == "seed":
                s0 = c["src"][1]
                if s0 <= soff < s0 + c["olen"]:
                    return c["foff"] + 3 + (soff - s0), s0 + c["olen"] - soff
        raise RuntimeError("seed 偏移 %d 未被 store 载荷覆盖" % soff)

    def _f_pos_list(self, lay, soff, length):
        """seed[soff:soff+length] 在 F 中对应的字节位置列表（可能跨多片）。"""
        res = []
        while length > 0:
            p, avail = self._f_off_of_seed(lay, soff)
            a = min(length, avail)
            res.extend(range(p, p + a))
            soff += a
            length -= a
        return res

    # ---------- 装配 ----------
    def assemble(self, lay):
        total, H = lay["total"], lay["H"]
        hoff = total - H
        C, plant = lay["C"], lay["plant"]
        F = bytearray(total)
        # pass A: 签名头 + 所有非 store 载荷字节
        F[0:6] = SIG
        F[6:8] = VER
        struct.pack_into("<Q", F, 12, lay["n"])
        struct.pack_into("<Q", F, 20, H)
        for c in lay["ochunks"]:
            if c["kind"] == "store":
                F[c["foff"]:c["foff"] + 3] = lay["hdr_tab"][c["hdr"]]
            else:
                F[c["foff"]:c["foff"] + c["size"]] = c["bytes"]
        F[hoff:hoff + H] = lay["header"]
        # pass B: seed = C副本 ‖ S32副本 ‖ H副本 ‖ plant
        seed = bytearray()
        seed += C
        seed += bytes(F[0:32])
        seed += bytes(F[hoff:hoff + H])
        seed += plant
        assert len(seed) == lay["ds"], "seed %d != %d" % (len(seed), lay["ds"])
        # pass C: 各 store 的载荷
        msegz = lay["mseg"] + b"\x00"
        for c in lay["ochunks"]:
            if c["kind"] != "store":
                continue
            p = c["foff"] + 3
            src, L = c["src"], c["olen"]
            if src[0] == "seed":
                F[p:p + L] = seed[src[1]:src[1] + L]
            elif src[0] == "tab":
                F[p:p + 3] = lay["hdr_tab"][src[1]]
            else:
                F[p:p + L] = msegz[src[1]:src[1] + L]
        return F, bytes(seed)

    # ---------- CRC 定点（128x128 GF(2)：seed/quine/Next/Start 四个 CRC） ----------
    def solve_crc(self, F, lay, C, plant):
        H, hoff = lay["H"], lay["total"] - lay["H"]
        n_sub, crc_base = lay["n_sub"], lay["crc_base"]
        lc = lay["lc"]
        # seed 里 S32 / H 副本在 F 中的镜像（可能跨多片，逐字节列出）
        scopy0 = self._f_pos_list(lay, lc, 32)
        Fv = memoryview(F)

        def seed_crc():
            v = crc32(C)
            v = crc32(Fv[0:32], v)                    # S32 副本
            v = crc32(Fv[hoff:hoff + H], v)           # H 副本
            return crc32(plant, v)

        def targets():
            return (seed_crc(), crc32(Fv), crc32(Fv[hoff:hoff + H]),
                    crc32(Fv[12:32]))

        # 已知：各内容文件的 CRC，写本体 + seed 里 H 副本的镜像两处
        known = [crc32(data) for _, data in self.files]
        for i, e in enumerate(known):
            slot = crc_base + 4 * i
            b = struct.pack("<I", e)
            for k in range(4):
                F[hoff + slot + k] = b[k]
            mir = self._f_pos_list(lay, lc + 32 + slot, 4)
            assert len(mir) == 4
            for k in range(4):
                F[mir[k]] = b[k]
        # 未知量：D_seed(seed 的 CRC)、D(quine 的 CRC)、N、S
        # 每个未知量 4 字节，每字节有"本体 + seed 镜像"两个落点
        qs = crc_base + 4 * len(known)       # seed 子流的 CRC 槽
        q = crc_base + 4 * (n_sub - 1)       # quine 子流的 CRC 槽
        groups = []
        for slot in (qs, q):
            groups.append([list(range(hoff + slot, hoff + slot + 4)),
                           self._f_pos_list(lay, lc + 32 + slot, 4)])
        groups.append([list(range(28, 32)), scopy0[28:32]])   # NextHeaderCRC
        groups.append([list(range(8, 12)), scopy0[8:12]])     # StartHeaderCRC
        nb = 32 * len(groups)
        base = targets()
        basevec = 0
        for i, v in enumerate(base):
            basevec |= v << (32 * i)
        cols = []
        for g in range(len(groups)):
            own, mir = groups[g]
            for kb in range(32):
                bi, bb = kb // 8, kb % 8
                poss = [own[bi], mir[bi]]
                for p in poss:
                    F[p] ^= (1 << bb)
                t = targets()
                for p in poss:
                    F[p] ^= (1 << bb)
                delta = 0
                for i, v in enumerate(t):
                    delta |= (v ^ base[i]) << (32 * i)
                cols.append(delta)
        eqs = []
        for i in range(nb):
            coeff = 0
            for j in range(nb):
                if (cols[j] >> i) & 1:
                    coeff |= 1 << j
            coeff ^= 1 << i
            eqs.append([coeff, (basevec >> i) & 1])
        for j in range(nb):
            p = next((i for i in range(j, nb) if (eqs[i][0] >> j) & 1), None)
            if p is None:
                raise RuntimeError("GF(2) 奇异 @bit%d" % j)
            eqs[j], eqs[p] = eqs[p], eqs[j]
            for i in range(nb):
                if i != j and ((eqs[i][0] >> j) & 1):
                    eqs[i][0] ^= eqs[j][0]
                    eqs[i][1] ^= eqs[j][1]
        x = 0
        for i in range(nb):
            assert eqs[i][0] == (1 << i)
            if eqs[i][1]:
                x |= 1 << i
        vals = [(x >> (32 * i)) & 0xFFFFFFFF for i in range(len(groups))]
        for g in range(len(groups)):
            own, mir = groups[g]
            b = struct.pack("<I", vals[g])
            for k in range(4):
                F[own[k]] = b[k]
                F[mir[k]] = b[k]
        t = targets()
        assert t == tuple(vals), "CRC 定点失败: %s != %s" % (t, vals)
        return vals

    def build(self):
        l0 = self.layout()
        lay = self.finalize(l0["Y"], l0["H"], l0["M"])
        F, seed = self.assemble(lay)
        crcs = self.solve_crc(F, lay, lay["C"], lay["plant"])
        # CRC 定点会改写 H / S32，而 seed 是它们的镜像，定点后需重建
        hoff = lay["total"] - lay["H"]
        seed = lay["C"] + bytes(F[0:32]) + bytes(F[hoff:hoff + lay["H"]]) \
            + lay["plant"]
        return bytes(F), lay, seed, crcs


def verify_double(F, lay, files, seed, content):
    """串联两个原始 LZMA2 解码器还原 U，逐段校验。"""
    d, total = lay["d"], lay["total"]
    dec_o = lzma.LZMADecompressor(
        format=lzma.FORMAT_RAW,
        filters=[{"id": lzma.FILTER_LZMA2, "dict_size": lay["dict_size_out"]}])
    I = dec_o.decompress(F[32:32 + lay["n"]])
    ok = True
    if len(I) != lay["Li"]:
        print("[verify] 外层输出 %d != I %d" % (len(I), lay["Li"]))
        return False
    dec_i = lzma.LZMADecompressor(
        format=lzma.FORMAT_RAW,
        filters=[{"id": lzma.FILTER_LZMA2, "dict_size": lay["dict_size_in"]}])
    U = dec_i.decompress(I)
    exp = d + total
    if len(U) != exp:
        print("[verify] 内层输出 %d != %d" % (len(U), exp))
        return False
    dc, ds = lay["dc"], lay["ds"]
    if U[:dc] != content:
        print("[verify] 内容不匹配")
        ok = False
    pos = 0
    for rel, data in files:                   # 内容文件排在 U 的最前面
        if U[pos:pos + len(data)] != data:
            print("[verify] 文件不匹配:", rel)
            ok = False
        pos += len(data)
    assert pos == dc
    if U[dc:dc + ds] != seed:
        print("[verify] seed 不匹配")
        ok = False
    if U[d:] != F:
        print("[verify] quine 自复制不匹配")
        ok = False
    print("[verify] 自解码: |I|=%d, |U|=%d, seed/文件/quine 全部匹配: %s"
          % (len(I), len(U), ok))
    return ok
```
  仅仅是大佬的一句话，AI就能做出来，实在是太可怕了。最终我试了一下，官方的7-Zip可以正常解压，但是Windows资源管理器不行……Windows资源管理器使用的也是[libarchive](https://github.com/libarchive/libarchive)，似乎是因为libarchive只支持2个解码器，并且[第二个解码器只能是像BCJ这样的过滤器](https://github.com/libarchive/libarchive/blob/8bb3bbdc7b117a1e22086a2260f2087aafa90687/libarchive/archive_read_support_format_7zip.c#L1475)……明明7-Zip官方是可以解压的，不知道如果把这个问题当作BUG报告给libarchive他们会不会解决？但目前存在兼容性问题的话我博客压缩包就先不用这个方案了吧🥲……   
## 对TXZ格式的尝试
  在做完7z格式的压缩包之后，我发现了一个问题，虽然7z确实很流行，但是在Linux下解压起来有点麻烦，7-Zip历史上主要面向Windows，Linux上长期以来更多依赖p7zip等第三方移植，因此生态集成度不如tar.xz，想要解压7z文件还得额外安装。   
  不过Linux下也有个支持LZMA2算法的压缩软件，那就是前些年出过[后门](https://tukaani.org/xz-backdoor/)的XZ Utils，配合tar就可以做出TXZ（tar.xz）文件，甚至用我[博客终端](https://mabbs.github.io/linux/)中的BusyBox也能解压。我想了一下反正有AI，干脆一句话让AI帮我把blogquine.py改成tar.xz格式的好了，结果倒也没费多少功夫，AI就这样写出来了：   

<details markdown="1">
<summary markdown="span">
Show Code
</summary>

```python
#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import argparse
import binascii
import io
import lzma
import os
import struct
import sys
import tarfile
import time
import ctypes
import ctypes.util

# ============================================================
# Part 1: 最小 LZMA1 range coder（只做编码）
# ============================================================

kNumBitModelTotalBits = 11
kBitModelTotal = 1 << kNumBitModelTotalBits          # 2048
kNumMoveBits = 5
kTopValue = 1 << 24                                   # 0x1000000

kNumStates = 12
kNumLitStates = 7
kNumPosBitsMax = 4
kNumLenToPosStates = 4
kNumAlignBits = 4
kEndPosModelIndex = 14
kNumFullDistances = 1 << (kEndPosModelIndex >> 1)     # 128
kMatchMinLen = 2
kNumLowLenBits = 3
kNumMidLenBits = 3
kNumHighLenBits = 8
kNumLowLenSymbols = 1 << kNumLowLenBits               # 8
kNumMidLenSymbols = 1 << kNumMidLenBits               # 8
kNumPosSlotBits = 6

PROB_INIT = kBitModelTotal >> 1                       # 1024


class RangeEncoder:
    """LZMA 的区间编码器。low 是 64 位（要容纳进位），range 是 32 位。"""

    def __init__(self):
        self.low = 0
        self.range = 0xFFFFFFFF
        self.cache = 0
        self.cache_size = 1          # 初值 1 -> 第一个输出字节恒为 0x00
        self.buf = bytearray()

    def _shift_low(self):
        if (self.low & 0xFFFFFFFF) < 0xFF000000 or (self.low >> 32) != 0:
            temp = self.cache
            while True:
                self.buf.append((temp + (self.low >> 32)) & 0xFF)
                temp = 0xFF
                self.cache_size -= 1
                if self.cache_size == 0:
                    break
            self.cache = (self.low >> 24) & 0xFF
        self.cache_size += 1
        self.low = ((self.low & 0xFFFFFFFF) << 8) & 0xFFFFFFFF

    def encode_bit(self, probs, idx, bit):
        p = probs[idx]
        bound = (self.range >> kNumBitModelTotalBits) * p
        if bit == 0:
            self.range = bound
            probs[idx] = p + ((kBitModelTotal - p) >> kNumMoveBits)
        else:
            self.low += bound
            self.range -= bound
            probs[idx] = p - (p >> kNumMoveBits)
        while self.range < kTopValue:
            self.range = (self.range << 8) & 0xFFFFFFFF
            self._shift_low()

    def encode_direct_bits(self, value, num_bits):
        for i in range(num_bits - 1, -1, -1):
            self.range >>= 1
            if (value >> i) & 1:
                self.low += self.range
            while self.range < kTopValue:
                self.range = (self.range << 8) & 0xFFFFFFFF
                self._shift_low()

    def bittree_encode(self, probs, off, num_bits, symbol):
        m = 1
        for i in range(num_bits - 1, -1, -1):
            bit = (symbol >> i) & 1
            self.encode_bit(probs, off + m, bit)
            m = (m << 1) | bit

    def bittree_reverse_encode(self, probs, off, num_bits, symbol):
        m = 1
        for i in range(num_bits):
            bit = symbol & 1
            symbol >>= 1
            self.encode_bit(probs, off + m, bit)
            m = (m << 1) | bit

    def finish(self):
        for _ in range(5):
            self._shift_low()
        return bytes(self.buf)


def _pos_slot_and_bits(d):
    if d < 4:
        return d, 0, 0
    for slot in range(4, 64):
        n = (slot >> 1) - 1
        base = (2 | (slot & 1)) << n
        if d < base + (1 << n):
            return slot, n, d - base
    raise ValueError("distance too large: %d" % d)


# pb 必须与写进每个 LZMA2 chunk 头的 PROPS_BYTE(0x5D) 一致。
# lc/lp 只影响 literal 编码的概率表索引，而本编码器不实现 literal 路径，故无需常量。
PB = 2


class LzmaEncoder:
    """只实现 quine 用到的两条路径：match 与 rep0-match。

    literal / rep-g1 / rep-g2 三条分支从未被构造，因此它们对应的概率表
    （p_lit、p_is_rep_g1、p_is_rep_g2）以及 prev_byte 都不必存在。
    reps 同理：编码器从不回读（rep0 的距离由解码器自行维护），故不保存。
    """

    def __init__(self):
        self.pos_mask = (1 << PB) - 1
        self.rc = RangeEncoder()
        self.pos = 0
        self.state = 0
        n = PROB_INIT
        self.p_is_match = [n] * (kNumStates << kNumPosBitsMax)
        self.p_is_rep = [n] * kNumStates
        self.p_is_rep_g0 = [n] * kNumStates
        self.p_rep0_long = [n] * (kNumStates << kNumPosBitsMax)
        self.p_pos_slot = [n] * (kNumLenToPosStates << kNumPosSlotBits)
        self.p_spec_pos = [n] * (kNumFullDistances - kEndPosModelIndex)
        self.p_align = [n] * (1 << kNumAlignBits)
        self.p_len_choice = [n] * 2
        self.p_len_low = [n] * (16 * kNumLowLenSymbols)
        self.p_len_mid = [n] * (16 * kNumMidLenSymbols)
        self.p_len_high = [n] * (1 << kNumHighLenBits)
        self.p_rep_len_choice = [n] * 2
        self.p_rep_len_low = [n] * (16 * kNumLowLenSymbols)
        self.p_rep_len_mid = [n] * (16 * kNumMidLenSymbols)
        self.p_rep_len_high = [n] * (1 << kNumHighLenBits)

    @property
    def pos_state(self):
        return self.pos & self.pos_mask

    def _encode_len(self, choice, low, mid, high, length):
        ps = self.pos_state
        l = length - kMatchMinLen
        if l < kNumLowLenSymbols:
            self.rc.encode_bit(choice, 0, 0)
            self.rc.bittree_encode(low, ps << kNumLowLenBits, kNumLowLenBits, l)
        else:
            self.rc.encode_bit(choice, 0, 1)
            l -= kNumLowLenSymbols
            if l < kNumMidLenSymbols:
                self.rc.encode_bit(choice, 1, 0)
                self.rc.bittree_encode(mid, ps << kNumMidLenBits, kNumMidLenBits, l)
            else:
                self.rc.encode_bit(choice, 1, 1)
                self.rc.bittree_encode(high, 0, kNumHighLenBits, l - kNumMidLenSymbols)

    def _write_dist(self, dist, lts):
        d = dist - 1
        slot, n, low_bits = _pos_slot_and_bits(d)
        self.rc.bittree_encode(self.p_pos_slot, lts << kNumPosSlotBits,
                               kNumPosSlotBits, slot)
        if slot >= 4:
            if slot < kEndPosModelIndex:
                base = (2 | (slot & 1)) << n
                off = base - slot - 1
                self.rc.bittree_reverse_encode(self.p_spec_pos, off, n, low_bits)
            else:
                self.rc.encode_direct_bits(low_bits >> kNumAlignBits, n - kNumAlignBits)
                self.rc.bittree_reverse_encode(self.p_align, 0, kNumAlignBits,
                                               low_bits & ((1 << kNumAlignBits) - 1))

    def match(self, dist, length):
        assert kMatchMinLen <= length <= 273, length
        ps = self.pos_state
        self.rc.encode_bit(self.p_is_match, (self.state << kNumPosBitsMax) + ps, 1)
        self.rc.encode_bit(self.p_is_rep, self.state, 0)
        lts = min(length - kMatchMinLen, kNumLenToPosStates - 1)
        self._encode_len(self.p_len_choice,
                         self.p_len_low, self.p_len_mid, self.p_len_high, length)
        self._write_dist(dist, lts)
        self.state = 7 if self.state < kNumLitStates else 10
        self.pos += length

    def rep_match(self, length):
        assert kMatchMinLen <= length <= 273, length
        ps = self.pos_state
        self.rc.encode_bit(self.p_is_match, (self.state << kNumPosBitsMax) + ps, 1)
        self.rc.encode_bit(self.p_is_rep, self.state, 1)
        self.rc.encode_bit(self.p_is_rep_g0, self.state, 0)
        self.rc.encode_bit(self.p_rep0_long, (self.state << kNumPosBitsMax) + ps, 1)
        self._encode_len(self.p_rep_len_choice,
                         self.p_rep_len_low, self.p_rep_len_mid, self.p_rep_len_high, length)
        self.state = 8 if self.state < kNumLitStates else 11
        self.pos += length

    def finish(self):
        return self.rc.finish()


# ============================================================
# Part 2: tar + xz 格式原语
# ============================================================

MAX_MATCH = 273                       # LZMA1 单个 match 长度上限
CHUNK = 65536                          # LZMA2 单 chunk 解压上限
PROPS_BYTE = 0x5D                      # lc=3, lp=0, pb=2
SEED_NOTE = ("\nMayx's Blog!").encode("utf-8")

# xz 格式常量
XZ_MAGIC = b"\xFD7zXZ\x00"
XZ_FOOTER_MAGIC = b"YZ"
XZ_CHECK_CRC64 = 0x04
LZMA2_FILTER_ID = 0x21
CHECK_SIZE = 8  # CRC64 占 8 字节
_XZ_FLAGS = bytes([0x00, XZ_CHECK_CRC64])   # Stream Flags: reserved + check_type

# tar 格式常量
TAR_BLOCK = 512


def round_up_512(n):
    """长度按 tar 块 512 字节向上取整。"""
    return (n + TAR_BLOCK - 1) // TAR_BLOCK * TAR_BLOCK


def crc32(b):
    return binascii.crc32(b) & 0xFFFFFFFF


# ---------- CRC64 (ECMA-182, reflected) ----------

_CRC64_POLY = 0xC96C5795D7870F42  # reflected ECMA-182
_CRC64_INIT = 0xFFFFFFFFFFFFFFFF
_CRC64_XOROUT = 0xFFFFFFFFFFFFFFFF
_CRC64_NON_REFLECTED = 0x142F0E1EBA9EA3693  # 非反射多项式 (65 bit)
_CRC64_MOD_BIT = 1 << 64  # x^64 对应的 bit


_liblzma = None
try:
    _lzma_name = ctypes.util.find_library('lzma')
    if _lzma_name:
        _liblzma = ctypes.CDLL(_lzma_name)
        _liblzma.lzma_crc64.argtypes = [ctypes.c_char_p, ctypes.c_size_t, ctypes.c_uint64]
        _liblzma.lzma_crc64.restype = ctypes.c_uint64
        # 验证：CRC64("123456789") 应为 0x995dc9bbdf1939fa
        if _liblzma.lzma_crc64(b'123456789', 9, 0) != 0x995dc9bbdf1939fa:
            _liblzma = None
except (OSError, AttributeError):
    _liblzma = None


def _make_crc64_table():
    table = []
    for i in range(256):
        crc = i
        for _ in range(8):
            crc = (crc >> 1) ^ _CRC64_POLY if (crc & 1) else crc >> 1
        table.append(crc)
    return table


_CRC64_TABLE = _make_crc64_table()


def _crc64_pure(data):
    """纯 Python CRC64（ECMA-182 反射，init/xorout = 0xFFFF...FFFF）。"""
    crc = _CRC64_INIT
    for byte in data:
        crc = (crc >> 8) ^ _CRC64_TABLE[(crc ^ byte) & 0xFF]
    return crc ^ _CRC64_XOROUT


def _crc64_lib(data):
    """liblzma CRC64（init=0，内部处理 init/xorout）。"""
    return _liblzma.lzma_crc64(data, len(data), 0)


crc64 = _crc64_lib if _liblzma else _crc64_pure


# ---------- GF(2^64) 多项式运算 ----------
# 用于 CRC64 自引用求解。CRC64 的线性贡献可表示为
# bit_reverse(contribution(D)) = D_poly * P (mod G_non)
# 其中 D_poly = bit_reverse(D)，P 是位置决定的多项式。
# 方程 D_poly * (1 ^ P1 ^ P2) = bit_reverse(CRC64(W)) 通过多项式逆元求解。

def _bit_reverse64(v):
    r = 0
    for _ in range(64):
        r = (r << 1) | (v & 1)
        v >>= 1
    return r


def _poly_mul_mod(a, b):
    """GF(2) 多项式乘法 mod G（非反射）。"""
    result = 0
    while b:
        if b & 1:
            result ^= a
        b >>= 1
        a <<= 1
        if a & _CRC64_MOD_BIT:
            a ^= _CRC64_NON_REFLECTED
    return result


def _poly_pow(base, exp):
    """多项式幂：base^exp mod G。"""
    result = 1
    while exp:
        if exp & 1:
            result = _poly_mul_mod(result, base)
        base = _poly_mul_mod(base, base)
        exp >>= 1
    return result


def _poly_minv(p):
    """多项式逆元 p^(-1) mod G，用扩展欧几里得算法。"""
    if p == 0:
        return 0
    old_r, r = p, _CRC64_NON_REFLECTED
    old_s, s = 1, 0
    while r:
        # poly divmod(old_r, r) -> (q, rem)
        probe_r = r.bit_length() - 1
        rem = old_r
        q = 0
        while rem.bit_length() - 1 >= probe_r and rem:
            shift = rem.bit_length() - 1 - probe_r
            q |= 1 << shift
            rem ^= r << shift
        old_r, r = r, rem
        # s = old_s ^ q*s (raw 多项式乘法)
        prod = 0
        a, b = q, s
        while b:
            if b & 1:
                prod ^= a
            b >>= 1
            a <<= 1
        old_s, s = s, old_s ^ prod
    if old_r != 1:
        return 0
    # old_s mod G
    probe_m = _CRC64_NON_REFLECTED.bit_length() - 1
    rem = old_s
    while rem.bit_length() - 1 >= probe_m and rem:
        shift = rem.bit_length() - 1 - probe_m
        rem ^= _CRC64_NON_REFLECTED << shift
    return rem


def store_hdr(payload_len, first=False):
    """LZMA2 uncompressed chunk 头（3 字节，大端 size-1）。"""
    assert 1 <= payload_len <= 65536
    return bytes([0x01 if first else 0x02]) + (payload_len - 1).to_bytes(2, "big")


def matches_for(dist, total):
    """dist 固定、总长 total 的 token 序列：首个 match + 后续 rep0。"""
    assert total >= 2
    toks = []
    first = min(MAX_MATCH, total)
    if total - first == 1:
        first -= 1
    toks.append(("m", dist, first))
    total -= first
    while total > 0:
        l = min(MAX_MATCH, total)
        if total - l == 1:
            l -= 1
        toks.append(("r0", l))
        total -= l
    return toks


def _add_gear(chunks, o, f, q):
    """追加一组标准 gear：store 载荷 x = slip+3，紧跟一个 lzma 把那 x 字节复制一遍。

    lzma chunk 解压出的字节数正好等于 x，所以齿轮转完之后 slip (f - (o-q)) 精确
    归约为 len(cb)（很小的正数，x 被 CHUNK 截断时则按 CHUNK 缩减）。
    _layout_iterate 反复套用把 slip 压到 <= 16，_trim_layouts 用它做相位微调。
    返回追加后的 (o, f)。
    """
    x = min(f - (o - q) + 3, CHUNK)
    chunks.append({"kind": "store", "foff": f, "size": 3 + x,
                   "ooff": o, "olen": x})
    o += x
    f += 3 + x
    cb, cu = lzma_chunk(matches_for(x, x), o)
    chunks.append({"kind": "lzma", "foff": f, "size": len(cb),
                   "ooff": o, "olen": cu, "bytes": cb})
    return o + cu, f + len(cb)


def _forward_vac(F, vac, q):
    """vac_store：把紧随其后的等长字节块前移覆盖自身。"""
    fo = vac["ooff"] - q
    olen = vac["olen"]
    F[fo:fo + olen] = F[fo + olen:fo + 2 * olen]


def dict_prop_for(maxdist):
    """选最小的 LZMA2 dict prop 使字典 >= maxdist。"""
    for p in range(41):
        if (2 | (p & 1)) << (p // 2 + 11) >= maxdist:
            return p, (2 | (p & 1)) << (p // 2 + 11)
    raise ValueError("distance too large")


def lzma_chunk(tokens, out_pos):
    """编一个 LZMA chunk（0xC0: state+props reset，无 dict reset，无 end marker）。"""
    enc = LzmaEncoder()
    enc.pos = out_pos
    total = 0
    for t in tokens:
        if t[0] == "m":
            enc.match(t[1], t[2])
            total += t[2]
        else:
            enc.rep_match(t[1])
            total += t[1]
    data = enc.finish()
    assert total - 1 < 65536 and len(data) - 1 < 65536
    hdr = bytes([0xC0]) + (total - 1).to_bytes(2, "big") + \
          (len(data) - 1).to_bytes(2, "big") + bytes([PROPS_BYTE])
    return hdr + data, total


# ---------- tar 原语 ----------

def tar_header(name, size, mtime, mode=0o644, typeflag=b'0', uid=0, gid=0):
    """构建 512 字节 POSIX ustar tar header。
    注意：tar 数值字段包含 null 终止符，slice 范围必须精确匹配字段宽度。
    mode/uid/gid 各 8 字节（7 octal + NUL），size/mtime 各 12 字节（11 octal + NUL）。
    """
    h = bytearray(512)
    name_bytes = name.encode('utf-8')[:100]
    h[0:len(name_bytes)] = name_bytes
    h[100:108] = b'%07o\x00' % mode       # 8 bytes (field 100-107)
    h[108:116] = b'%07o\x00' % uid        # 8 bytes (field 108-115)
    h[116:124] = b'%07o\x00' % gid        # 8 bytes (field 116-123)
    h[124:136] = b'%011o\x00' % size      # 12 bytes (field 124-135)
    h[136:148] = b'%011o\x00' % mtime     # 12 bytes (field 136-147)
    h[148:156] = b'        '              # checksum placeholder (8 spaces)
    h[156:157] = typeflag
    h[257:263] = b'ustar\x00'
    h[263:265] = b'00'
    assert len(h) == 512, "header length %d != 512" % len(h)
    # 计算校验和：所有字节之和，checksum 字段视为空格
    chksum = sum(h) & 0o7777777
    h[148:156] = b'%06o\x00 ' % chksum    # 6 octal + NUL + space = 8 bytes
    assert len(h) == 512, "header length %d != 512 after checksum" % len(h)
    return bytes(h)


# ---------- xz 原语 ----------

def xz_varint(v):
    """xz 变长整数编码：每字节 7 位数据（LSB first），MSB 为续位。"""
    b = []
    while v >= 0x80:
        b.append((v & 0x7F) | 0x80)
        v >>= 7
    b.append(v & 0x7F)
    return bytes(b)


def xz_stream_header():
    """12 字节 xz stream header (CHECK_CRC64)。
    Stream Flags = [reserved(0x00), check_type(CRC64=0x04)]。
    """
    flags = _XZ_FLAGS
    crc = crc32(flags)
    return XZ_MAGIC + flags + struct.pack('<I', crc)


def xz_block_header(dict_size):
    """xz block header（单 LZMA2 filter）。
    返回 (header_bytes, 实际字典大小)；header 长度即 block header 总长度。
    """
    prop, real_dict = dict_prop_for(dict_size)
    # filter flags: filter_id(1) + props_size(1) + props(1=prop byte)
    filter_flags = bytes([LZMA2_FILTER_ID, 1, prop])
    # block header content: flags(1, 0x00=1 filter) + filter_flags
    content = bytes([0x00]) + filter_flags
    # 填充到 (1 + len(content) + 4) 是 4 的倍数
    total = 1 + len(content) + 4
    pad = (4 - total % 4) % 4
    content += b'\x00' * pad
    bh = 1 + len(content) + 4
    assert bh % 4 == 0, "bh not 4-aligned: %d" % bh
    crc = crc32(bytes([bh // 4 - 1]) + content)
    header = bytes([bh // 4 - 1]) + content + struct.pack('<I', crc)
    assert len(header) == bh
    return header, real_dict


def xz_index(records):
    """xz index。records = [(unpadded_size, uncompressed_size), ...]。"""
    data = bytes([0x00])  # index indicator
    data += xz_varint(len(records))
    for unpadded, uncompressed in records:
        data += xz_varint(unpadded)
        data += xz_varint(uncompressed)
    # 填充到 (len(data) + 4) 是 4 的倍数
    pad = (4 - (len(data) + 4) % 4) % 4
    data += b'\x00' * pad
    return data + struct.pack('<I', crc32(data))


def xz_stream_footer(backward_size):
    """12 字节 xz stream footer (CHECK_CRC64)。
    backward_size = (index_size / 4) - 1。
    Stream Flags = [reserved(0x00), check_type(CRC64=0x04)]。
    CRC32 覆盖 Backward Size + Stream Flags（6 字节，不含 CRC32 和 Footer Magic）。
    """
    flags = _XZ_FLAGS
    crc_data = struct.pack('<I', backward_size) + flags  # 6 bytes, no magic
    crc = crc32(crc_data)
    return struct.pack('<I', crc) + crc_data + XZ_FOOTER_MAGIC


# ============================================================
# Part 3: 多文件 tar.xz quine 构造器
# ============================================================

class TarXzQuine:
    def __init__(self, root, quine_name="quine.tar.xz", seed_name=".this_is_mayx_blog",
                 src_dir=""):
        self.quine_name = quine_name
        self.seed_name = seed_name
        self.src_dir = src_dir.strip("/")
        self.mtime = int(time.time())
        # walk 源目录
        self.walk_entries = []
        self.files = []
        if self.src_dir:
            parts = self.src_dir.split("/")
            for i in range(1, len(parts) + 1):
                self.walk_entries.append(("/".join(parts[:i]), True))
        for dirpath, dirnames, filenames in os.walk(root):
            dirnames.sort()
            for dn in dirnames:
                rel = os.path.relpath(os.path.join(dirpath, dn), root).replace(os.sep, "/")
                self.walk_entries.append((self._prefixed(rel), True))
            for fn in sorted(filenames):
                p = os.path.join(dirpath, fn)
                rel = os.path.relpath(p, root).replace(os.sep, "/")
                with open(p, "rb") as fp:
                    data = fp.read()
                self.walk_entries.append((self._prefixed(rel), False))
                self.files.append((self._prefixed(rel), data))
        # rel -> data 映射，避免下面三处按 rel 回头线性搜索整个 files 列表
        self.file_map = dict(self.files)
        self.dirs = [r for r, isd in self.walk_entries if isd]
        self.content = b"".join(data for _, data in self.files)

    def _prefixed(self, rel):
        return self.src_dir + "/" + rel if self.src_dir else rel

    def tar_entries(self, d_seed, xz_size):
        """计算 tar 归档中每个条目的 (header, data_size, is_dir)。
        顺序：seed, walk_entries (interleaved files+dirs), quine。
        """
        entries = []
        # seed 文件
        seed_hdr = tar_header(self.seed_name, d_seed, self.mtime)
        entries.append({"name": self.seed_name, "hdr": seed_hdr,
                        "data_size": d_seed, "is_dir": False})
        # walk 顺序的文件和目录
        for rel, isd in self.walk_entries:
            if isd:
                hdr = tar_header(rel, 0, self.mtime, mode=0o755, typeflag=b'5')
                entries.append({"name": rel, "hdr": hdr,
                                "data_size": 0, "is_dir": True})
            else:
                # file_map 与 walk_entries 在 __init__ 里同步构造，这里必有
                data = self.file_map[rel]
                entries.append({"name": rel, "hdr": tar_header(rel, len(data), self.mtime),
                                "data_size": len(data), "is_dir": False})
        # quine 文件（放在最后）
        qhdr = tar_header(self.quine_name, xz_size, self.mtime)
        entries.append({"name": self.quine_name, "hdr": qhdr,
                        "data_size": xz_size, "is_dir": False})
        return entries

    # ---------- 结构计算 ----------
    def _compute_q(self, d_seed):
        """计算 xz_bytes 在 tar 中的偏移 q。
        q = seed + files + dirs 的 tar 占用 + quine tar header。
        q 不依赖 xz_size（quine 的 data 在 q 之后）。"""
        q = 0
        # seed 文件
        q += TAR_BLOCK  # seed tar header
        q += round_up_512(d_seed)      # seed data + pad
        # walk 顺序的文件和目录
        for rel, isd in self.walk_entries:
            q += TAR_BLOCK  # tar header
            if not isd:
                q += round_up_512(len(self.file_map[rel]))
        # quine tar header
        q += TAR_BLOCK
        return q

    def _trim_layouts(self, base, o_g, f_g, q, w_plant_off, d_seed):
        """枚举 trim 配置，产出一批「相位」不同的候选布局。

        trim = [可选的裸 store chunk，载荷长度 x0] + 一组标准 gear
               （store 载荷 x = s+3，紧接着一个 lzma 复制这 x 字节）。

        裸 store 把 slip 抬高 3、把 f 抬高 3+x0；随后这组 gear 把 slip 重新归一到
        len(cb)，jump 再归一到 -3。净效果是 (o_pre, f_pre) 被整体平移
        δ ≈ s_g + 6 + len(cb) + 3 + x0，而 δ 决定了自洽方程的模 4 相位。
        旧实现 δ 恒为 0，相位一旦不对就永远无解 —— 而 d_seed += 1 根本不改变
        布局（q 只在跨 512 字节块时才变），所以那 80 次重试是纯粹的无效空转。

        注意：不能只插一个裸的 lzma 复制块。lzma 复制块的输出必须等于
        F[o-q : o-q+olen]，而这只能靠前面那个「载荷 = F[o-q : o-q+x] 且 x = s+3」
        的 store chunk 把字节搬到正确位置来实现；裸插复制块解压出来和 F 对不上。

        返回 [(chunks, o_before_jump, f_before_jump, y, jb), ...]，按文件体积升序。
        """
        s_g = f_g - (o_g - q)
        out = []
        seen = set()
        for x0 in range(0, s_g + 4):
            chunks = list(base)
            o, f = o_g, f_g
            if x0:
                # 裸 store：载荷 = F[o-q : o-q+x0]，要求 x0 <= s+3 以免读到尚未定稿的字节
                chunks.append({"kind": "store", "foff": f, "size": 3 + x0,
                               "ooff": o, "olen": x0})
                o += x0
                f += 3 + x0
            o, f = _add_gear(chunks, o, f, q)   # 一组标准 gear
            # jump 不动点：y = s + 3 + len(jb)
            s = f - (o - q)
            y = max(2, s + 17)
            jb = ju = None
            for _ in range(64):
                try:
                    jb, ju = lzma_chunk([("m", o - w_plant_off, y)], o)
                except AssertionError:
                    jb = None
                    break
                y2 = s + 3 + len(jb)
                if y2 == y:
                    break
                if y2 < 2 or y2 > 273:
                    jb = None
                    break
                y = y2
            if jb is None or ju != y:
                continue
            if y + w_plant_off - TAR_BLOCK > d_seed:
                continue
            key = (o + y, f + len(jb))
            if key in seen:
                continue
            seen.add(key)
            out.append((chunks, o, f, y, jb))

        out.sort(key=lambda t: t[2] + len(t[4]))
        return out

    def _solve_gadget(self, chunks_pre, o_j, f_j, y, jb, q, bh, FEW,
                      block_hdr, dict_size, hdrA, hdrB, d_seed, k):
        """在一个给定相位的布局上求解 gadget（T / gb / suffix / tz / k）。

        关键简化：tz 只依赖 u = gb + suffix 与 k；T = u + tz + 4 也只依赖 (u, k)；
        而 gb 又由 T 唯一确定（len(lzma_chunk(matches_for(T, T))))。
        因此只需一维枚举 u 即可遍历全部解，既不漏解也远快于原来的三重暴力。
        """
        o_pre = o_j + y
        f_pre = f_j + len(jb)
        if f_pre != (o_pre - q) - 3:      # jump 应把 slip 归一到 -3
            return None

        chunks = list(chunks_pre)
        chunks.append({"kind": "lzma", "foff": f_j, "size": len(jb),
                       "ooff": o_j, "olen": y, "bytes": jb, "jump": True})

        best = None
        for u in range(8, 512):
            # 512k 必须落在 [f_pre + 2u + 2059, f_pre + 2u + 3595)
            lo = f_pre + 2 * u + 2059
            hi = f_pre + 2 * u + 3595
            for k_cand in range(max(1, (lo - 512) // 512), (hi + 512) // 512 + 2):
                num = k_cand * 512 - (o_pre + 2 * u + 8 - q - 1024)
                if num % 3 != 0:
                    continue
                tz_cand = num // 3
                if tz_cand < 1024:
                    continue
                T = u + tz_cand + 4
                if T < 2:
                    continue
                gb, gu = lzma_chunk(matches_for(T, T), o_pre + T)
                gb_len = len(gb)
                suffix = u - gb_len
                if suffix < 1:
                    continue

                # 精确自检（不再用带 9 字节偏差的预筛公式）
                f_final = f_pre + 3 + T + gb_len + 3 + tz_cand + 1
                n = f_final - (12 + bh)
                bp = (4 - (12 + bh + n) % 4) % 4
                unpadded = bh + n + CHECK_SIZE
                idx = xz_index([(unpadded, q + k_cand * 512 + 1024)])
                ix = len(idx)
                suffix_actual = bp + CHECK_SIZE + ix + 12
                if suffix_actual != suffix:
                    continue
                xz_size = 12 + bh + n + bp + CHECK_SIZE + ix + 12
                xz_pad_actual = round_up_512(xz_size)
                if xz_pad_actual != k_cand * 512:
                    continue
                total_w_actual = q + xz_pad_actual + 1024
                o_final = o_pre + 2 * T + tz_cand
                if o_final != total_w_actual:
                    continue

                if best is not None and xz_size >= best["xz_size"]:
                    continue          # 已找到更小的解，跳过

                backward_size = ix // 4 - 1
                final = list(chunks)
                final.append({"kind": "store", "foff": f_pre, "size": 3 + T,
                              "ooff": o_pre, "olen": T, "vac": True})
                final.append({"kind": "lzma", "foff": f_pre + 3 + T,
                              "size": gb_len, "ooff": o_pre + T, "olen": gu,
                              "bytes": gb})
                final.append({"kind": "store",
                              "foff": f_pre + 3 + T + gb_len,
                              "size": 3 + tz_cand, "ooff": o_pre + 2 * T,
                              "olen": tz_cand, "trailing": True})
                final.append({"kind": "term",
                              "foff": f_pre + 3 + T + gb_len + 3 + tz_cand,
                              "size": 1, "ooff": o_final, "olen": 0,
                              "bytes": b"\x00"})
                best = {
                    "q": q, "d_seed": d_seed, "k": k,
                    "chunks": final, "block_hdr": block_hdr, "bh": bh,
                    "n": n, "xz_size": xz_size,
                    "T": T, "suffix": suffix_actual,
                    "bp": bp, "ix": ix,
                    "dict_size": dict_size,
                    "FEW": FEW, "hdrA": hdrA,
                    "hdrB": hdrB, "jump_y": y, "index": idx,
                    "stream_hdr": xz_stream_header(),
                    "footer": xz_stream_footer(backward_size),
                    "entries": self.tar_entries(d_seed, xz_size),
                }
        return best

    def _layout_iterate(self, d_seed, maxdist_hint):
        """核心布局。

        阶段 1a：C1 / repro / gears（只依赖 q，所有 trim 配置共用，只算一次）
        阶段 1b：插入 trim 微调块，平移 (o_pre, f_pre) 改变模 4 相位
        阶段 2  ：按 u = gb + suffix 一维搜索自洽解
        """
        block_hdr, dict_size = xz_block_header(maxdist_hint)
        bh = len(block_hdr)
        FEW = 12 + bh + 3
        w_hdrA_off = TAR_BLOCK + 12 + bh
        w_hdrB_off = TAR_BLOCK + 12 + bh + 3
        w_plant_off = TAR_BLOCK + 12 + bh + 6

        q = self._compute_q(d_seed)

        # ---------- 阶段 1a：C1 + repro + gears ----------
        base = []
        o, f = 0, 12 + bh
        Ls = []
        rem = q + FEW
        while rem > CHUNK:
            Ls.append(CHUNK)
            rem -= CHUNK
        Ls.append(rem)
        assert Ls[-1] >= 2, "末 C1 chunk 载荷 %d 太小" % Ls[-1]
        k = len(Ls)
        hdrA = store_hdr(CHUNK, first=False)
        hdrB = store_hdr(Ls[-1], first=False)

        S = 0
        for j, L in enumerate(Ls):
            base.append({"kind": "store", "foff": f, "size": 3 + L,
                         "ooff": o, "olen": L, "first": j == 0,
                         "c1": True, "S": S})
            o += L
            f += 3 + L
            S += L
        assert o == q + FEW

        S = 0
        for j, L in enumerate(Ls):
            if j > 0:
                srcpos = w_hdrA_off if (j < k - 1 or L == CHUNK) else w_hdrB_off
                dist_h = (q + FEW + S + 3 * (j - 1)) - srcpos
                hb, hu = lzma_chunk([("m", dist_h, 3)], o)
                base.append({"kind": "lzma", "foff": f, "size": len(hb),
                             "ooff": o, "olen": hu, "bytes": hb})
                o += hu
                f += len(hb)
            cb, cu = lzma_chunk(matches_for(q + FEW + 3 * j, L), o)
            base.append({"kind": "lzma", "foff": f, "size": len(cb),
                         "ooff": o, "olen": cu, "bytes": cb})
            o += cu
            f += len(cb)
            S += L

        # gears：把 slip 压到 <= 16
        while f - (o - q) > 16:
            o, f = _add_gear(base, o, f, q)

        o_g, f_g = o, f

        # ---------- 阶段 1b + 阶段 2 ----------
        # 相位按文件体积升序枚举；第一个成功的相位通常已经足够好，但不同相位的
        # (u, tz) 不同，xz_size 仍可能相差几百字节，所以再多看几个取最小的。
        tried = 0
        best = None
        since_hit = 0
        for chunks_pre, o_j, f_j, y, jb in self._trim_layouts(
                base, o_g, f_g, q, w_plant_off, d_seed):
            lay = self._solve_gadget(chunks_pre, o_j, f_j, y, jb, q, bh, FEW,
                                     block_hdr, dict_size, hdrA, hdrB,
                                     d_seed, k)
            tried += 1
            if lay is not None and (best is None
                                    or lay["xz_size"] < best["xz_size"]):
                best = lay
            if best is not None:
                since_hit += 1
                if since_hit >= 10:
                    break
            elif tried >= 80:        # 一直无解，放弃后续相位
                break
        if best is not None:
            return best

        raise RuntimeError("layout 不收敛: 无自洽解 (q=%d, f_pre=%d, o_pre=%d)"
                           % (q, f_g, o_g))

    # ---------- 装配 ----------
    def assemble(self, lay):
        """构建 xz 文件 F 和 seed。"""
        F = bytearray(lay["xz_size"])
        q = lay["q"]
        d_seed = lay["d_seed"]
        bh = lay["bh"]
        FEW = lay["FEW"]

        # bytearray 已全零初始化：block padding、CRC64 占位、trailing-zero 载荷
        # 都不必再显式写 0（后面几处赋值只会写到各自独立的区间，不会交叉覆盖）。

        # pass A: 写 xz stream header + block header + 所有 chunk bytes + suffix
        F[0:12] = lay["stream_hdr"]
        F[12:12+bh] = lay["block_hdr"]

        jump_c = None
        for c in lay["chunks"]:
            if c["kind"] == "store":
                F[c["foff"]:c["foff"] + 3] = store_hdr(c["olen"],
                                                       first=c.get("first", False))
            else:
                F[c["foff"]:c["foff"] + c["size"]] = c["bytes"]
                if c.get("jump"):
                    jump_c = c

        # block padding + CRC64(pass D 填) + index + footer
        bp_off = 12 + bh + lay["n"]
        ix_off = bp_off + lay["bp"] + CHECK_SIZE
        F[ix_off:ix_off + lay["ix"]] = lay["index"]
        sf_off = ix_off + lay["ix"]
        F[sf_off:sf_off + 12] = lay["footer"]

        assert jump_c is not None

        # pass B: 构建 seed
        y = lay["jump_y"]
        plant = bytes(F[jump_c["ooff"] - q: jump_c["ooff"] - q + y])
        seed = bytearray(d_seed)
        seed[0:12] = lay["stream_hdr"]
        seed[12:12+bh] = lay["block_hdr"]
        seed[12+bh:12+bh+3] = lay["hdrA"]
        seed[12+bh+3:12+bh+6] = lay["hdrB"]
        seed[12+bh+6:12+bh+6+y] = plant
        pad = (SEED_NOTE * (d_seed // len(SEED_NOTE) + 2))[:d_seed - 12 - bh - 6 - y]
        seed[12+bh+6+y:] = pad

        # 构建 tar 前缀 T（含 seed data）
        T = self._build_tar_prefix_with_seed(lay, seed)
        F_prefix = bytes(F[0:FEW])
        P = T + F_prefix
        assert len(P) == q + FEW, "P 长度 %d != q+FEW %d" % (len(P), q + FEW)

        # pass C: 填充 store payloads
        for c in lay["chunks"]:
            if c["kind"] != "store":
                continue
            ooff, olen = c["ooff"], c["olen"]
            if c.get("c1"):
                F[c["foff"] + 3:c["foff"] + 3 + olen] = P[c["S"]:c["S"] + olen]
            elif c.get("trailing"):
                # 载荷是尾部零：F 全零初始化，且唯一会写到 chunk 之外的 vac_store
                # 目标是 [f_pre+3, f_pre+3+T)（f_pre == (o_pre-q)-3 已由 _solve_gadget
                # 断言），与本区块不重叠，因此无需写入。
                continue
            elif c.get("vac"):
                _forward_vac(F, c, q)
            else:
                # 其余 store 的载荷 = 输出流自身对应位置的字节（自引用复制）
                fo = ooff - q
                F[c["foff"] + 3:c["foff"] + 3 + olen] = F[fo:fo + olen]

        # pass D: 求解 CRC64 自引用
        self._solve_crc64(F, lay, T)

        return bytes(F), bytes(seed)

    def _build_tar_prefix_with_seed(self, lay, seed):
        """构建 tar 前缀 T（含 seed data）。"""
        entries = lay["entries"]
        T = bytearray()
        for e in entries[:-1]:
            T += e["hdr"]
            if not e["is_dir"] and e["data_size"] > 0:
                data = seed if e["name"] == self.seed_name else self.file_map[e["name"]]
                T += data
                T += b'\x00' * (round_up_512(e["data_size"]) - e["data_size"])
        T += entries[-1]["hdr"]  # quine tar header
        return bytes(T)

    def _solve_crc64(self, F, lay, T_prefix):
        """求解 CRC64 自引用。

        CRC64 值 D = CRC64(W)，W = T + F + 尾部零。
        D 在 W 中出现两次：F 的 CRC64 字段 + vac_store 副本。

        解法（多项式逆元）：
          CRC64 的线性贡献可表示为 GF(2^64) 多项式乘法：
            bit_reverse(contribution(D)) = D_poly * P (mod G)
          其中 D_poly = bit_reverse(D)，P = x^(64+trailing) mod G。
          方程 D_poly * (1 ^ P1 ^ P2) = bit_reverse(CRC64(W)) (mod G)
          用扩展欧几里得求 (1 ^ P1 ^ P2) 的逆元，一步求解。
        """
        q = lay["q"]
        bh = lay["bh"]
        n = lay["n"]
        bp = lay["bp"]
        xz_size = lay["xz_size"]
        T = lay["T"]

        # CRC64 位置 1：在 F 中（block padding 后）
        crc_f_off = 12 + bh + n + bp
        crc_w1 = q + crc_f_off

        # CRC64 位置 2：vac_store 副本
        crc_f_copy = crc_f_off - T
        crc_w2 = q + crc_f_copy

        # 构造 W = T + F + 尾部零（先把两处 CRC64 置 0）
        xz_pad = round_up_512(xz_size)
        tz = xz_pad - xz_size + 1024
        W = bytearray(T_prefix) + F + b'\x00' * tz
        W[crc_w1:crc_w1 + CHECK_SIZE] = b'\x00' * CHECK_SIZE
        W[crc_w2:crc_w2 + CHECK_SIZE] = b'\x00' * CHECK_SIZE

        # CRC64(W) 的多项式表示
        crc_poly = _bit_reverse64(crc64(bytes(W)))

        # P1 = x^(64 + 位置1之后的bit数) mod G
        trailing1 = (len(W) - crc_w1 - 8) * 8
        P1 = _poly_pow(2, 64 + trailing1)
        # P2 = x^(64 + 位置2之后的bit数) mod G
        trailing2 = (len(W) - crc_w2 - 8) * 8
        P2 = _poly_pow(2, 64 + trailing2)

        # D_poly = crc_poly * inv(1 ^ P1 ^ P2)
        coeff = 1 ^ P1 ^ P2
        inv = _poly_minv(coeff)
        if inv == 0:
            raise RuntimeError("CRC64 多项式无逆元")
        D_poly = _poly_mul_mod(crc_poly, inv)
        D = _bit_reverse64(D_poly)

        # 写入 D 到 F 的 CRC64 位置
        struct.pack_into('<Q', F, crc_f_off, D)

        # 重新执行 vac_store 副本
        _forward_vac(F, next(c for c in lay["chunks"] if c.get("vac")), q)

        # 验证
        W2 = bytearray(T_prefix) + F + b'\x00' * tz
        assert crc64(bytes(W2)) == D, "CRC64 求解验证失败"

    def build(self, maxdist_hint=None):
        if maxdist_hint is None:
            maxdist_hint = 2 * (len(self.content) + 128) + (1 << 21)
        last_err = None
        # d_seed 在同一 512 字节块内不改变 q（seed 数据按 512 对齐），所以旧的
        # "d_seed += 1" 重试完全不会改变布局，只是空转 80 次。真正需要 d_seed
        # 变化的情况只有两种：seed 装不下 jump 种植串，或需要跨块改变 q 作为兜底。
        for d_seed in (64, 96, 128, 160, 192, 256, 320, 384, 448,
                       576, 704, 832, 960, 1088, 1600, 2112, 2624, 3648):
            try:
                lay = self._layout_iterate(d_seed, maxdist_hint)
                F, seed = self.assemble(lay)
                return F, lay, seed
            except (RuntimeError, AssertionError, ValueError) as e:
                last_err = e
        raise RuntimeError("build 多次失败: %s" % last_err)


# ============================================================
# Part 4: 验证 + main
# ============================================================

def verify(F, lay, files, quine_name):
    """验证：解压 xz → 解析 tar → 检查文件 + quine 自复制。"""
    # 1. 解压 xz
    try:
        dec = lzma.LZMADecompressor(format=lzma.FORMAT_XZ)
        tar_data = dec.decompress(F)
    except Exception as e:
        print("[verify] xz 解压失败: %s" % e)
        return False

    # 2. 检查 quine 自复制
    if tar_data[lay["q"]:lay["q"] + lay["xz_size"]] != F:
        print("[verify] quine 自复制不匹配")
        a = tar_data[lay["q"]:lay["q"] + lay["xz_size"]]
        for i in range(min(len(a), len(F))):
            if a[i] != F[i]:
                print("[verify]   首个不匹配在偏移 %d: tar=%02x vs xz=%02x" % (i, a[i], F[i]))
                break
        return False

    # 3. 解析 tar
    try:
        tf = tarfile.open(fileobj=io.BytesIO(tar_data))
        members = tf.getmembers()
    except Exception as e:
        print("[verify] tar 解析失败: %s" % e)
        return False

    print("[verify] tar 条目: %s" % [m.name for m in members])

    # 4. 检查源文件
    ok = True
    for rel, data in files:
        try:
            f = tf.extractfile(rel)
            if f is None:
                print("[verify] 文件 %s 是目录或不存在" % rel)
                ok = False
                continue
            extracted = f.read()
            if extracted != data:
                print("[verify] 文件 %s 内容不匹配" % rel)
                ok = False
        except KeyError:
            print("[verify] 文件 %s 不在 tar 中" % rel)
            ok = False

    # 5. 检查 quine 文件
    try:
        qf = tf.extractfile(quine_name)
        if qf:
            qdata = qf.read()
            if qdata != F:
                print("[verify] quine 文件内容不匹配 (%d vs %d)" % (len(qdata), len(F)))
                ok = False
            else:
                print("[verify] quine 文件匹配!")
    except KeyError:
        print("[verify] quine 文件不在 tar 中")
        ok = False

    print("[verify] 结果: %s" % ("通过" if ok else "失败"))
    return ok


def main():
    ap = argparse.ArgumentParser(description="多文件 tar.xz quine 生成器")
    ap.add_argument("srcdir")
    ap.add_argument("output")
    ap.add_argument("--quine-name", default=None,
                    help="归档内 quine 文件名（默认 = output 的文件名）")
    ap.add_argument("--seed-name", default=".this_is_mayx_blog")
    ap.add_argument("--src-dir", default="",
                    help="源文件在归档内的前缀目录")
    ap.add_argument("--quine-dir", default="",
                    help="quine 在归档内所在目录")
    args = ap.parse_args()

    quine_name = args.quine_name or os.path.basename(args.output)
    if args.quine_dir:
        quine_dir = args.quine_dir.strip("/")
        quine_name = quine_dir + "/" + quine_name

    bq = TarXzQuine(args.srcdir, quine_name=quine_name, seed_name=args.seed_name,
                    src_dir=args.src_dir)
    print("[blogquine-tarxz] %d 个文件, %d 个目录, 内容 %d 字节"
          % (len(bq.files), len(bq.dirs), len(bq.content)))
    F, lay, seed = bq.build()
    with open(args.output, "wb") as fp:
        fp.write(F)
    print("[blogquine-tarxz] written %s: %d 字节 (q=%d, k=%d chunks, n=%d, xz_size=%d)"
          % (args.output, len(F), lay["q"], lay["k"], lay["n"], lay["xz_size"]))
    print("[blogquine-tarxz] T=%d, suffix=%d (bp=%d, ix=%d), dict_size=%d"
          % (lay["T"], lay["suffix"], lay["bp"], lay["ix"], lay["dict_size"]))
    ok = verify(F, lay, bq.files, quine_name)
    sys.exit(0 if ok else 1)


if __name__ == "__main__":
    main()
```
</details>

  不过对我来说，相比于TXZ格式我还是更喜欢7z一点，一是因为LZMA2本来就是7-Zip的作者发明的，XZ感觉像是摘桃子的，二是TXZ这个名字听起来有点怪，感觉不像压缩包，三是XZ Utils出过后门，尽管整个Linux社区都在使用XZ，但是我还是稍微有点偏见，所以这份TXZ的生成器我就粘贴出来给需要的人吧，我博客用7z格式就好了。   

# 感想
  以前总是有人说AI没有创新能力，只是对曾经在网络上出现的东西进行重组，但人何尝不是这样呢？像这次制作的7z/TXZ Quine生成器在整个网络上没有任何公开信息，当然我也知道这并不是理论上的创新，但谁说组合创新不是创新呢？再看看最近OpenAI又解决了一大堆数学难题，完全可以相信AI是真的拥有智能，所以我相信总有一天AI将能完成人类能做的所有事情，人类将不再需要额外的思考，只需要做自己想做的事情吧。