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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).
130 lines
4.6 KiB
Python
130 lines
4.6 KiB
Python
# dialects/mssql/json.py
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# Copyright (C) 2005-2026 the SQLAlchemy authors and contributors
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# <see AUTHORS file>
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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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# mypy: ignore-errors
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from ... import types as sqltypes
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# technically, all the dialect-specific datatypes that don't have any special
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# behaviors would be private with names like _MSJson. However, we haven't been
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# doing this for mysql.JSON or sqlite.JSON which both have JSON / JSONIndexType
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# / JSONPathType in their json.py files, so keep consistent with that
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# sub-convention for now. A future change can update them all to be
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# package-private at once.
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class JSON(sqltypes.JSON):
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"""MSSQL JSON type.
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MSSQL supports JSON-formatted data as of SQL Server 2016.
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The :class:`_mssql.JSON` datatype at the DDL level will represent the
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datatype as ``NVARCHAR(max)``, but provides for JSON-level comparison
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functions as well as Python coercion behavior.
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:class:`_mssql.JSON` is used automatically whenever the base
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:class:`_types.JSON` datatype is used against a SQL Server backend.
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.. seealso::
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:class:`_types.JSON` - main documentation for the generic
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cross-platform JSON datatype.
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The :class:`_mssql.JSON` type supports persistence of JSON values
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as well as the core index operations provided by :class:`_types.JSON`
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datatype, by adapting the operations to render the ``JSON_VALUE``
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or ``JSON_QUERY`` functions at the database level.
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The SQL Server :class:`_mssql.JSON` type necessarily makes use of the
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``JSON_QUERY`` and ``JSON_VALUE`` functions when querying for elements
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of a JSON object. These two functions have a major restriction in that
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they are **mutually exclusive** based on the type of object to be returned.
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The ``JSON_QUERY`` function **only** returns a JSON dictionary or list,
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but not an individual string, numeric, or boolean element; the
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``JSON_VALUE`` function **only** returns an individual string, numeric,
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or boolean element. **both functions either return NULL or raise
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an error if they are not used against the correct expected value**.
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To handle this awkward requirement, indexed access rules are as follows:
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1. When extracting a sub element from a JSON that is itself a JSON
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dictionary or list, the :meth:`_types.JSON.Comparator.as_json` accessor
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should be used::
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stmt = select(data_table.c.data["some key"].as_json()).where(
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data_table.c.data["some key"].as_json() == {"sub": "structure"}
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)
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2. When extracting a sub element from a JSON that is a plain boolean,
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string, integer, or float, use the appropriate method among
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:meth:`_types.JSON.Comparator.as_boolean`,
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:meth:`_types.JSON.Comparator.as_string`,
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:meth:`_types.JSON.Comparator.as_integer`,
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:meth:`_types.JSON.Comparator.as_float`::
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stmt = select(data_table.c.data["some key"].as_string()).where(
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data_table.c.data["some key"].as_string() == "some string"
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)
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.. versionadded:: 1.4
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"""
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# note there was a result processor here that was looking for "number",
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# but none of the tests seem to exercise it.
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# Note: these objects currently match exactly those of MySQL, however since
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# these are not generalizable to all JSON implementations, remain separately
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# implemented for each dialect.
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class _FormatTypeMixin:
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def _format_value(self, value):
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raise NotImplementedError()
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def bind_processor(self, dialect):
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super_proc = self.string_bind_processor(dialect)
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def process(value):
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value = self._format_value(value)
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if super_proc:
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value = super_proc(value)
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return value
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return process
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def literal_processor(self, dialect):
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super_proc = self.string_literal_processor(dialect)
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def process(value):
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value = self._format_value(value)
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if super_proc:
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value = super_proc(value)
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return value
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return process
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class JSONIndexType(_FormatTypeMixin, sqltypes.JSON.JSONIndexType):
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def _format_value(self, value):
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if isinstance(value, int):
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value = "$[%s]" % value
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else:
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value = '$."%s"' % value
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return value
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class JSONPathType(_FormatTypeMixin, sqltypes.JSON.JSONPathType):
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def _format_value(self, value):
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return "$%s" % (
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"".join(
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[
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"[%s]" % elem if isinstance(elem, int) else '."%s"' % elem
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for elem in value
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]
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)
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)
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