mirror of
https://github.com/deepmodeling/Uni-Lab-OS
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56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
import json
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from unilabos.utils.type_check import TypeEncoder, json_default
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try:
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import orjson
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def fast_dumps(obj, **kwargs) -> bytes:
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"""JSON 序列化为 bytes，优先使用 orjson。"""
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return orjson.dumps(obj, option=orjson.OPT_NON_STR_KEYS, default=json_default)
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def fast_dumps_pretty(obj, **kwargs) -> bytes:
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"""JSON 序列化为 bytes（带缩进），优先使用 orjson。"""
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return orjson.dumps(
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obj,
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option=orjson.OPT_NON_STR_KEYS | orjson.OPT_INDENT_2,
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default=json_default,
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)
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def fast_loads(data) -> dict:
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"""JSON 反序列化，优先使用 orjson。接受 str / bytes。"""
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return orjson.loads(data)
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def fast_dumps_str(obj, **kwargs) -> str:
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"""JSON 序列化为 str，优先使用 orjson。用于需要 str 而非 bytes 的场景（如 ROS msg）。"""
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return orjson.dumps(obj, option=orjson.OPT_NON_STR_KEYS, default=json_default).decode("utf-8")
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def normalize_json(info: dict) -> dict:
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"""经 JSON 序列化/反序列化一轮来清理非标准类型。"""
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return orjson.loads(orjson.dumps(info, default=json_default))
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except ImportError:
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def fast_dumps(obj, **kwargs) -> bytes: # type: ignore[misc]
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return json.dumps(obj, ensure_ascii=False, cls=TypeEncoder).encode("utf-8")
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def fast_dumps_pretty(obj, **kwargs) -> bytes: # type: ignore[misc]
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return json.dumps(obj, indent=2, ensure_ascii=False, cls=TypeEncoder).encode("utf-8")
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def fast_loads(data) -> dict: # type: ignore[misc]
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if isinstance(data, bytes):
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data = data.decode("utf-8")
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return json.loads(data)
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def fast_dumps_str(obj, **kwargs) -> str: # type: ignore[misc]
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return json.dumps(obj, ensure_ascii=False, cls=TypeEncoder)
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def normalize_json(info: dict) -> dict: # type: ignore[misc]
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return json.loads(json.dumps(info, ensure_ascii=False, cls=TypeEncoder))
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# 辅助函数：将UUID数组转换为字符串
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def uuid_to_str(uuid_array) -> str:
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"""将UUID字节数组转换为十六进制字符串"""
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return "".join(format(byte, "02x") for byte in uuid_array)
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