132 lines
3.9 KiB
Python
132 lines
3.9 KiB
Python
from __future__ import annotations
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import hashlib
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from collections.abc import Iterable, Mapping
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from .device_profile import DeviceProfile
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PERSISTED_CACHE_KEYS = (
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"k6",
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"k8",
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"k16",
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"k19",
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"k23",
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"k27",
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"k29",
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"k40",
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"k105",
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"k110",
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)
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def uq0_s_a(text: str) -> str:
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"""复现 uq0.s.a(): 非空且非 KWE* 时返回 MD5 小写 hex 前 16 位。"""
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if not text or text.startswith("KWE"):
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return text
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return hashlib.md5(text.encode("utf-8")).hexdigest()[:16]
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def java_string_hashcode(text: str) -> int:
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"""Java String.hashCode() 的 32-bit 结果。"""
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value = 0
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for char in text:
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value = (31 * value + ord(char)) & 0xFFFFFFFF
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return value
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def java_hashmap_spread(hashcode: int) -> int:
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"""OpenJDK HashMap.hash(): h ^ (h >>> 16)。"""
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unsigned = hashcode & 0xFFFFFFFF
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return (unsigned ^ (unsigned >> 16)) & 0xFFFFFFFF
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def java_hashmap_to_string(entries: Iterable[tuple[str, object]], capacity: int = 16) -> str:
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"""复现当前 DFP cache_m 使用场景下的 HashMap.toString() 顺序。
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c.s(Context) 只 put 10 个固定 String key，默认 HashMap 首次扩容到 16，
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不会触发二次 resize。这里按 bucket 下标递增、bucket 内插入顺序输出。
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"""
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buckets: list[list[tuple[str, object]]] = [[] for _ in range(capacity)]
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for key, value in entries:
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index = java_hashmap_spread(java_string_hashcode(key)) & (capacity - 1)
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bucket = buckets[index]
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for item_index, (existing_key, _) in enumerate(bucket):
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if existing_key == key:
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bucket[item_index] = (key, value)
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break
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else:
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bucket.append((key, value))
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pairs = [
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f"{key}={'' if value is None else str(value)}"
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for bucket in buckets
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for key, value in bucket
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]
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return "{" + ", ".join(pairs) + "}"
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def _dfp_non_empty(value: object) -> str:
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text = "" if value is None else str(value)
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return text if text else "KWE_N"
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def _target_sdk_grdi(value: str, target_sdk_version: int) -> str:
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if target_sdk_version < 30 or not value or value.startswith("KWE"):
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return value
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try:
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parts = value.split("|")
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return "".join(f"{part}|" for index, part in enumerate(parts) if index != 3)
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except Exception:
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return value
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def persisted_cache_source_values(
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profile: DeviceProfile,
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*,
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target_sdk_version: int = 30,
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) -> dict[str, str]:
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"""构造 com.kuaishou.dfp.c.c.s(Context) 写入 HashMap 的 10 个字段。"""
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hints = profile.runtime_hints
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return {
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"k6": _dfp_non_empty("0"),
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"k8": _dfp_non_empty(profile.build_type),
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"k16": _dfp_non_empty(""),
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"k19": _dfp_non_empty("sun"),
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"k23": _dfp_non_empty(profile.manufacturer),
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"k27": _dfp_non_empty(profile.model),
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"k29": _dfp_non_empty(
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f"Dalvik/2.1.0 (Linux; U; Android {profile.android_release}; "
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f"{profile.model} Build/{profile.build_id})"
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),
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"k40": _dfp_non_empty(""),
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"k105": _dfp_non_empty(_target_sdk_grdi(hints.grdi, target_sdk_version)),
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"k110": _dfp_non_empty(hints.keeper_seed),
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}
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def build_persisted_cache_m_from_values(values: Mapping[str, object]) -> str:
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entries = [(key, values.get(key, "KWE_N")) for key in PERSISTED_CACHE_KEYS]
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return uq0_s_a(java_hashmap_to_string(entries))
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def build_persisted_cache_m(
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profile: DeviceProfile,
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*,
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target_sdk_version: int = 30,
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) -> str:
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values = persisted_cache_source_values(profile, target_sdk_version=target_sdk_version)
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return build_persisted_cache_m_from_values(values)
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__all__ = [
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"PERSISTED_CACHE_KEYS",
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"build_persisted_cache_m",
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"build_persisted_cache_m_from_values",
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"java_hashmap_spread",
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"java_hashmap_to_string",
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"java_string_hashcode",
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"persisted_cache_source_values",
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"uq0_s_a",
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]
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