feat: add dump structural index tools (sqlite + query cli + docs)

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kedou 2026-08-08 00:23:11 +08:00
parent 99d599026d
commit 77788f374d
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# dump.txt 结构化索引 — 使用文档
`dump.txt` 是 Unispect v0.2.4.0 生成的 IL2CPP 类布局 dump(15.8 万行 / 7MB)。
本工具将其解析为 SQLite 数据库 `dump_index.db`,提供毫秒级类型 / 字段 / 偏移检索,
替代对原始文本的暴力搜索。
---
## 1. 快速开始
```powershell
# 构建索引(默认输入 F:\desktop\Release\dump.txt,输出 dump_index.db)
python build_index.py
# 自定义路径
python build_index.py D:\other\dump.txt D:\other\dump_index.db
# 查询统计
python query_index.py stats
```
构建耗时约 1.5 秒,输出:
```
types = 15137 # class 11118 / interface 1118 / struct 1998 / enum 903
fields = 143599 # static 12350 / const 17693
anomaly = 0 # 无法解析的行数(应为 0)
```
---
## 2. 数据库结构(schema)
```sql
CREATE TABLE types (
id INTEGER PRIMARY KEY, -- 类型 ID,查询时可直接用
kind TEXT, -- class / interface / enum / struct
name TEXT, -- 原始名(含 -. 前缀与泛型参数,如 -.Player.FirearmController)
short TEXT, -- 可读短名(去掉 -. 前缀与泛型尾巴,如 Player.FirearmController)
base_type TEXT, -- 基类(接口无基类时为空串)
line_no INTEGER, -- 在 dump.txt 中的行号
src_order INTEGER -- 原始顺序
);
CREATE TABLE fields (
id INTEGER PRIMARY KEY,
type_id INTEGER REFERENCES types(id), -- 所属类型
offset_hex TEXT, -- 十六进制偏移,如 "1D8"
offset_dec INTEGER, -- 十进制偏移(排序用)
is_static INTEGER, -- 1 = 静态字段 [S]
is_const INTEGER, -- 1 = 常量 [C]
name TEXT, -- 字段名
field_type TEXT, -- 字段类型
line_no INTEGER
);
-- FTS5 全文索引(按 rowid 关联)
CREATE VIRTUAL TABLE types_fts USING fts5(name, short, base_type, ...);
CREATE VIRTUAL TABLE fields_fts USING fts5(name, field_type, ...);
```
字段行格式还原(与 dump.txt 一致):
```
[偏移][S|C] 字段名 : 字段类型
[1D8] CoverStruct : -.GStruct13 ← 普通字段
[00][S] staticVar : Int32 ← 静态字段
[00][C] TooLittle : System.Int32 ← 枚举常量 / const
```
---
## 3. 查询命令手册
所有命令:`python query_index.py <命令> [关键词] [--limit N]`
### 3.1 统计总览
```powershell
python query_index.py stats
```
输出类型总数、各类别数量、字段最多的 TOP10 类型(可直接拿 ID 去展开)。
### 3.2 按类型名搜索
```powershell
python query_index.py type Player
python query_index.py type "GClass" --limit 50
```
模糊匹配 `name` 与 `short`,按字段数降序排列,便于快速定位"大头"类。
### 3.3 按基类搜索(继承关系)
```powershell
python query_index.py base MonoBehaviour
python query_index.py base "GClass429"
```
找出所有直接继承自某基类的类型。
### 3.4 全局搜字段名
```powershell
python query_index.py field Health
python query_index.py field "k__BackingField" --limit 100
```
跨所有类型搜索字段名,输出含所属类型、偏移、类型。
### 3.5 按字段类型搜索
```powershell
python query_index.py ftype "List<"
python query_index.py ftype "System.Action"
```
找出所有声明为该类型的字段(如所有 `List<Int32>` 字段)。
### 3.6 展开一个类型的全部字段
```powershell
python query_index.py show 13764 # 按 ID
python query_index.py show EFT.Player # 按名字(唯一匹配时)
```
输出该类型所有字段:偏移、S/C 标记、字段名、类型。按偏移升序。
### 3.7 还原原始 dump 格式
```powershell
python query_index.py dump 12702
```
按 dump.txt 原样格式输出整个类型块,便于与原文对比或导出。
### 3.8 通用选项
| 选项 | 说明 | 默认 |
|---|---|---|
| `--limit N` | 搜索结果上限 | 20 |
| `--db PATH` | 指定索引库路径 | `dump_index.db` |
---
## 4. 高级用法:直接查 SQLite
不经过 CLI,直接用 Python / sqlite3 查询:
```powershell
python -c "
import sqlite3
con = sqlite3.connect(r'F:\desktop\CFramework\dump_index.db')
# 1. 找某类型所有字段
for r in con.execute('''
SELECT offset_hex, name, field_type FROM fields
WHERE type_id = (SELECT id FROM types WHERE name='EFT.Player')
ORDER BY offset_dec'''):
print(r)
"
```
常用 SQL 片段:
```sql
-- 同偏移字段(union/variant 布局分析)
SELECT f.type_id, t.name, f.offset_hex, f.name, f.field_type
FROM fields f JOIN types t ON t.id=f.type_id
WHERE f.offset_hex='00' AND f.is_static=0
GROUP BY f.type_id HAVING COUNT(*)>1;
-- 继承链:所有 EFT.Player 的派生类
SELECT id, name, base_type FROM types WHERE base_type LIKE '%Player%';
-- FTS 快速搜索(token 级,比 LIKE 快)
SELECT t.id, t.name
FROM types_fts JOIN types t ON t.id = types_fts.rowid
WHERE types_fts MATCH 'player';
-- 某类型静态字段清单
SELECT offset_hex, name, field_type FROM fields
WHERE type_id=13764 AND is_static=1 ORDER BY offset_dec;
```
---
## 5. 标记说明
| 标记 | 含义 |
|---|---|
| `[S]` | Static 静态字段(`is_static=1`) |
| `[C]` | Constant 常量 / 枚举值(`is_const=1`) |
| 无标记 | 实例字段 |
| 偏移 | 字段在对象内存布局中的偏移(十六进制),`offset_dec` 为其十进制值 |
注意:枚举类型的枚举值在 dump 中也是 `[C]` 行(偏移恒为 `00`),
展开 enum 时看到的 `[00][C] XXX : System.Int32` 就是枚举成员。
---
## 6. 已知限制
1. **dump 不含方法**:Unispect 默认只导出字段布局,索引同样只有字段。
方法签名 / IL 不在 `dump.txt` 内,无法索引。
2. **异常字符行**:极少数字段名含控制字符(如 `` ` >j\x01 ``),解析时会被跳过,
构建日志中 `anomaly` 计数反映数量(当前为 0)。
3. **同名类型**:不同命名空间下存在同名类型(如多个 `GClass857`),
`show` / `dump` 用名字定位时若多匹配会列出候选,请改用 ID 精确指定。
4. **`-.` 前缀**:表示 global namespace 或嵌套类,`name` 保留原始形式,
搜索时 `short` 列已去掉此前缀,两者都参与匹配。
---
## 7. 常见问题
**Q: 为什么我搜 `type GClass857` 出现多个结果?**
A: 同名类型在多处定义(正常现象),用 `show <id>` 精确定位。
**Q: 想重新生成索引?**
A: 直接重跑 `python build_index.py`,会自动覆盖旧库。
**Q: 查询报"索引不存在"?**
A: 先运行 `python build_index.py`,或确认 `--db` 路径正确。
**Q: 数据库能跨机器用吗?**
A: 能。`dump_index.db` 是纯 SQLite 文件,拷贝即可,无需重装依赖。

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# -*- coding: utf-8 -*-
"""
build_index.py — 把 Unispect dump.txt 流式解析成 SQLite 结构化索引。
用法:
python build_index.py [dump.txt路径] [输出db路径]
特性:
- 流式读取,绝不把整个文件读入内存(文件 7MB / 15.8 万行也毫无压力)
- 表 types: id, kind, name, base_type, line_no, src_order
- 表 fields: id, type_id, offset_hex, offset_dec, is_static, is_const,
name, field_type, line_no
- FTS5 全文索引: types_fts (name/base_type), fields_fts (name/field_type)
- 枚举常量(C)与静态字段(S)独立标记
"""
import io
import os
import re
import sqlite3
import sys
import time
SRC_DEFAULT = r"F:\desktop\Release\dump.txt"
DB_DEFAULT = r"F:\desktop\CFramework\dump_index.db"
TYPE_HEAD_RE = re.compile(
r"^\[(Class|Interface|Enum|Struct)\]\s+(.+?)(?:\s*:\s*(.+))?$"
)
FIELD_RE = re.compile(
r"^\s+\[([0-9A-Fa-f]+)\](?:\[([SC])\])?\s+(.+?)\s*:\s*(.+)$"
)
# 兜底: 缩进但没匹配字段正则的行(异常行, 记录到 log 便于排查, 不影响索引)
INDENTED_RE = re.compile(r"^\s+\S")
KIND_MAP = {"Class": "class", "Interface": "interface", "Enum": "enum", "Struct": "struct"}
def clean_name(name: str) -> str:
"""去掉 Unispect 的 `-.` 内部类前缀与泛型参数尾巴, 得到可读名。"""
n = name.strip()
if n.startswith("-."):
n = n[2:]
# 去掉泛型 `...<...>` 的尖括号部分用于短名
short = re.split(r"[<`]", n, maxsplit=1)[0]
return n, short
def build(src: str, db: str) -> None:
if os.path.exists(db):
os.remove(db)
t0 = time.time()
con = sqlite3.connect(db)
con.execute("PRAGMA journal_mode=OFF")
con.execute("PRAGMA synchronous=OFF")
con.execute("PRAGMA temp_store=MEMORY")
cur = con.cursor()
cur.executescript(
"""
CREATE TABLE types (
id INTEGER PRIMARY KEY,
kind TEXT NOT NULL,
name TEXT NOT NULL, -- 原始名 (含 -. / 泛型)
short TEXT NOT NULL, -- 可读短名
base_type TEXT,
line_no INTEGER,
src_order INTEGER
);
CREATE TABLE fields (
id INTEGER PRIMARY KEY,
type_id INTEGER NOT NULL REFERENCES types(id),
offset_hex TEXT NOT NULL,
offset_dec INTEGER NOT NULL,
is_static INTEGER NOT NULL DEFAULT 0,
is_const INTEGER NOT NULL DEFAULT 0,
name TEXT NOT NULL,
field_type TEXT,
line_no INTEGER
);
CREATE INDEX idx_fields_type ON fields(type_id);
CREATE INDEX idx_fields_name ON fields(name);
CREATE INDEX idx_types_name ON types(name);
CREATE INDEX idx_types_short ON types(short);
CREATE INDEX idx_types_base ON types(base_type);
CREATE VIRTUAL TABLE types_fts USING fts5(
name, short, base_type, content='types', content_rowid='id'
);
CREATE VIRTUAL TABLE fields_fts USING fts5(
name, field_type, content='fields', content_rowid='id'
);
"""
)
type_id = 0
field_id = 0
current = None # (type_id, kind, name)
type_count = 0
field_count = 0
anomaly_log = []
with io.open(src, "r", encoding="utf-8", errors="replace", newline="\n") as f:
for lineno, raw in enumerate(f, 1):
line = raw.rstrip("\r\n")
t = line.strip()
if not t:
continue
m = TYPE_HEAD_RE.match(t)
if m:
kind_raw, name, base = m.group(1), m.group(2), m.group(3)
type_id += 1
name_full, short = clean_name(name)
base_s = (base or "").strip()
cur.execute(
"INSERT INTO types (id, kind, name, short, base_type, line_no, src_order) "
"VALUES (?,?,?,?,?,?,?)",
(type_id, KIND_MAP[kind_raw], name_full, short, base_s,
lineno, type_id),
)
cur.execute(
"INSERT INTO types_fts (rowid, name, short, base_type) VALUES (?,?,?,?)",
(type_id, name_full, short, base_s),
)
current = type_id
type_count += 1
continue
fm = FIELD_RE.match(line)
if fm and current is not None:
off_hex = fm.group(1)
flag = fm.group(2) or ""
fname = fm.group(3).strip()
ftype = fm.group(4).strip()
field_id += 1
cur.execute(
"INSERT INTO fields (id, type_id, offset_hex, offset_dec, is_static, "
"is_const, name, field_type, line_no) VALUES (?,?,?,?,?,?,?,?,?)",
(field_id, current, off_hex, int(off_hex, 16),
1 if flag == "S" else 0,
1 if flag == "C" else 0,
fname, ftype, lineno),
)
cur.execute(
"INSERT INTO fields_fts (rowid, name, field_type) VALUES (?,?,?)",
(field_id, fname, ftype),
)
field_count += 1
continue
# 异常行: 缩进但解析不了, 或类型头后跟的杂行
if INDENTED_RE.match(line) and current is not None:
if len(anomaly_log) < 50:
anomaly_log.append(f"L{lineno}: {t[:80]!r}")
# 重建 FTS 索引内容表一致性
cur.execute("INSERT INTO types_fts(types_fts) VALUES('rebuild')")
cur.execute("INSERT INTO fields_fts(fields_fts) VALUES('rebuild')")
con.commit()
elapsed = time.time() - t0
print(f"types = {type_count}")
print(f"fields = {field_count}")
print(f"anomaly = {len(anomaly_log)}")
for a in anomaly_log:
print(" !", a)
print(f"elapsed = {elapsed:.2f}s")
print(f"db = {db} ({os.path.getsize(db) / 1024:.0f} KB)")
# 内置快速校验
print("\n-- sanity checks --")
for q, label in [
("SELECT kind, COUNT(*) FROM types GROUP BY kind", "types by kind"),
("SELECT COUNT(*) FROM types WHERE base_type IS NULL OR base_type=''", "types w/o base"),
("SELECT COUNT(*) FROM fields WHERE is_static=1", "static fields"),
("SELECT COUNT(*) FROM fields WHERE is_const=1", "const fields"),
]:
rows = cur.execute(q).fetchall()
print(f"{label}: {rows}")
con.close()
if __name__ == "__main__":
src = sys.argv[1] if len(sys.argv) > 1 else SRC_DEFAULT
db = sys.argv[2] if len(sys.argv) > 2 else DB_DEFAULT
build(src, db)

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# -*- coding: utf-8 -*-
"""
query_index.py — 查询 dump SQLite 索引。
用法:
python query_index.py stats
python query_index.py type <名称子串> # 按类型名搜索 (LIKE)
python query_index.py short <短名> # 按可读短名精确/模糊
python query_index.py base <基类子串> # 按基类搜索
python query_index.py field <字段名子串> # 全局搜字段名
python query_index.py ftype <字段类型子串> # 按字段类型搜 (如 List<)
python query_index.py show <type_id 或 完整类型名> # 展开一个类型的全部字段
python query_index.py dump <type_id> # 原始格式还原 (offset + 标记)
选项:
--limit N 默认 20
--db PATH 默认 dump_index.db
"""
import argparse
import os
import sqlite3
import sys
DB_DEFAULT = r"F:\desktop\CFramework\dump_index.db"
def connect(db):
if not os.path.exists(db):
sys.exit(f"[!] 索引不存在: {db}\n 先运行: python build_index.py")
return sqlite3.connect(db)
def cmd_stats(con):
for q, label in [
("SELECT COUNT(*) FROM types", "types"),
("SELECT COUNT(*) FROM fields", "fields"),
("SELECT kind, COUNT(*) FROM types GROUP BY kind", "types by kind"),
]:
print(f"{label}: {con.execute(q).fetchall()}")
# 字段最多/最少的前几个类型
print("\ntop 10 types by field count:")
rows = con.execute(
"""SELECT t.id, t.kind, t.name, COUNT(f.id) c FROM types t
LEFT JOIN fields f ON f.type_id = t.id
GROUP BY t.id ORDER BY c DESC LIMIT 10"""
).fetchall()
for r in rows:
print(f" [{r[0]:>5}] {r[1]:<9} {r[2][:60]:<60} fields={r[3]}")
def cmd_types(con, needle, limit):
like = f"%{needle}%"
rows = con.execute(
"""SELECT id, kind, name, base_type,
(SELECT COUNT(*) FROM fields f WHERE f.type_id=t.id) AS fc
FROM types t WHERE name LIKE ? OR short LIKE ?
ORDER BY fc DESC LIMIT ?""",
(like, like, limit),
).fetchall()
print(f"{len(rows)} match(es) for type name '{needle}':")
for r in rows:
print(f" [{r[0]:>5}] {r[1]:<9} {r[2][:70]:<70} base={r[3] or '-'} fields={r[4]}")
def cmd_base(con, needle, limit):
rows = con.execute(
"""SELECT id, kind, name, base_type,
(SELECT COUNT(*) FROM fields f WHERE f.type_id=t.id) AS fc
FROM types t WHERE base_type LIKE ? ORDER BY fc DESC LIMIT ?""",
(f"%{needle}%", limit),
).fetchall()
print(f"{len(rows)} type(s) with base like '{needle}':")
for r in rows:
print(f" [{r[0]:>5}] {r[1]:<9} {r[2][:70]:<70} base={r[3] or '-'} fields={r[4]}")
def cmd_fields(con, needle, limit):
rows = con.execute(
"""SELECT f.id, t.kind, t.name, f.offset_hex, f.name, f.field_type,
f.is_static, f.is_const
FROM fields f JOIN types t ON t.id = f.type_id
WHERE f.name LIKE ? ORDER BY f.name LIMIT ?""",
(f"%{needle}%", limit),
).fetchall()
print(f"{len(rows)} field(s) named like '{needle}':")
for r in rows:
flags = ("S" if r[6] else "") + ("C" if r[7] else "")
print(f" [{r[0]:>6}] {r[1]:<9} {r[2][:48]:<48} [+{r[3]:>4}]{flags:<3} {r[4]} : {r[5]}")
def cmd_ftype(con, needle, limit):
rows = con.execute(
"""SELECT f.id, t.kind, t.name, f.offset_hex, f.name, f.field_type
FROM fields f JOIN types t ON t.id = f.type_id
WHERE f.field_type LIKE ? ORDER BY f.name LIMIT ?""",
(f"%{needle}%", limit),
).fetchall()
print(f"{len(rows)} field(s) with type like '{needle}':")
for r in rows:
print(f" [{r[0]:>6}] {r[1]:<9} {r[2][:48]:<48} [+{r[3]:>4}] {r[4]} : {r[5]}")
def resolve_type(con, arg):
"""arg 可以是数字 id 或类型名子串; 返回唯一类型或 None"""
if arg.isdigit():
row = con.execute(
"SELECT id, kind, name, base_type, line_no FROM types WHERE id=?",
(int(arg),),
).fetchone()
if row:
return row
rows = con.execute(
"""SELECT id, kind, name, base_type, line_no FROM types
WHERE name = ? OR short = ? LIMIT 5""",
(arg, arg),
).fetchall()
if len(rows) == 1:
return rows[0]
if len(rows) > 1:
print(f"[!] '{arg}' 有 {len(rows)} 个匹配, 用 id 精确定位:")
for r in rows:
print(f" [{r[0]}] {r[1]} {r[2]}")
return None
# 子串兜底
rows = con.execute(
"SELECT id, kind, name, base_type, line_no FROM types WHERE name LIKE ? LIMIT 10",
(f"%{arg}%",),
).fetchall()
if len(rows) == 1:
return rows[0]
if len(rows) > 1:
print(f"[!] '{arg}' 有 {len(rows)} 个匹配:")
for r in rows[:10]:
print(f" [{r[0]}] {r[1]} {r[2]}")
return None
def cmd_show(con, arg):
t = resolve_type(con, arg)
if not t:
sys.exit(f"[!] 未找到类型: {arg}")
tid, kind, name, base, line = t
print(f"== [{tid}] {kind} {name} : {base or '-'} (line {line}) ==")
rows = con.execute(
"""SELECT offset_hex, is_static, is_const, name, field_type
FROM fields WHERE type_id=? ORDER BY offset_dec, id""",
(tid,),
).fetchall()
if not rows:
print(" (无字段)")
for off, st, cs, fname, ftype in rows:
flags = ("[S]" if st else "") + ("[C]" if cs else "")
print(f" +{off:<5} {flags:<4} {fname} : {ftype}")
print(f" -- {len(rows)} fields --")
def cmd_dump(con, arg):
"""按 dump.txt 原始格式还原类型"""
t = resolve_type(con, arg)
if not t:
sys.exit(f"[!] 未找到类型: {arg}")
tid, kind, name, base, line = t
print(f"[{kind.title()}] {name} : {base or ''}")
for off, st, cs, fname, ftype in con.execute(
"""SELECT offset_hex, is_static, is_const, name, field_type
FROM fields WHERE type_id=? ORDER BY offset_dec, id""",
(tid,),
):
flags = ("[S]" if st else "") + ("[C]" if cs else "")
print(f" [{off}]{flags} {fname} : {ftype}")
def main():
ap = argparse.ArgumentParser(description="dump.txt SQLite 索引查询")
ap.add_argument("cmd", choices=["stats", "type", "short", "base", "field", "ftype", "show", "dump"])
ap.add_argument("needle", nargs="?", default="")
ap.add_argument("--limit", type=int, default=20)
ap.add_argument("--db", default=DB_DEFAULT)
args = ap.parse_args()
con = connect(args.db)
if args.cmd == "stats":
cmd_stats(con)
elif args.cmd == "type":
cmd_types(con, args.needle, args.limit)
elif args.cmd == "short":
cmd_types(con, args.needle, args.limit) # short 也走 name+short LIKE
elif args.cmd == "base":
cmd_base(con, args.needle, args.limit)
elif args.cmd == "field":
cmd_fields(con, args.needle, args.limit)
elif args.cmd == "ftype":
cmd_ftype(con, args.needle, args.limit)
elif args.cmd == "show":
cmd_show(con, args.needle)
elif args.cmd == "dump":
cmd_dump(con, args.needle)
con.close()
if __name__ == "__main__":
main()