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Определение специфических рекомендаций (матрица профилей §8):
1. Ж/д слой (закрыт мёртвый railway ×2.5 у РАС):
- /api/v1/water/{case_id} отдаёт railway=rail как LineString
(без service/industrial/military веток), кэш общий v2;
- railway_warning «перекрыть/проверить немедленно» по профилям;
- SearchMap: Polyline слой ж/д (тёмно-красный), счётчики 💧/🚂.
2. cant_swim → профиль не_умеет_плавать (water ×3.0, без изменения
радиуса, critical_warning «обследовать водоёмы НЕМЕДЛЕННО»):
- раньше чекбокс влиял только на текст, в скоринге был пробел;
- derive в analyze._derive_profiles — работает и для closed_cases.
3. unmodeled_profiles: ДЦП/слабое зрение/слух — честная пометка
«вне поведенческой модели» с пояснением (vector_tasks B12:
профили без аналога не выдавать за учтённые); блок на фронте
в карточке здоровья.
Площадь воды: сферический эксцесс, проверен на квадрате 53° (744017 м²
vs 743272 точного). Тесты: 202 passed (новый test_cant_swim_profile).
63 lines
2.3 KiB
Python
63 lines
2.3 KiB
Python
# engine/processors.py
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# Copyright (C) 2010-2026 the SQLAlchemy authors and contributors
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# <see AUTHORS file>
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# Copyright (C) 2010 Gaetan de Menten gdementen@gmail.com
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#
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# This module is part of SQLAlchemy and is released under
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# the MIT License: https://www.opensource.org/licenses/mit-license.php
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"""defines generic type conversion functions, as used in bind and result
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processors.
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They all share one common characteristic: None is passed through unchanged.
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"""
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from __future__ import annotations
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import typing
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from ._py_processors import str_to_datetime_processor_factory # noqa
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from ..util._has_cy import HAS_CYEXTENSION
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if typing.TYPE_CHECKING or not HAS_CYEXTENSION:
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from ._py_processors import int_to_boolean as int_to_boolean
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from ._py_processors import str_to_date as str_to_date
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from ._py_processors import str_to_datetime as str_to_datetime
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from ._py_processors import str_to_time as str_to_time
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from ._py_processors import (
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to_decimal_processor_factory as to_decimal_processor_factory,
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)
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from ._py_processors import to_float as to_float
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from ._py_processors import to_str as to_str
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else:
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from sqlalchemy.cyextension.processors import (
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DecimalResultProcessor,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401
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int_to_boolean as int_to_boolean,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401,E501
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str_to_date as str_to_date,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401
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str_to_datetime as str_to_datetime,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401,E501
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str_to_time as str_to_time,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401,E501
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to_float as to_float,
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)
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from sqlalchemy.cyextension.processors import ( # noqa: F401,E501
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to_str as to_str,
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)
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def to_decimal_processor_factory(target_class, scale):
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# Note that the scale argument is not taken into account for integer
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# values in the C implementation while it is in the Python one.
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# For example, the Python implementation might return
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# Decimal('5.00000') whereas the C implementation will
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# return Decimal('5'). These are equivalent of course.
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return DecimalResultProcessor(target_class, "%%.%df" % scale).process
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