126 lines
4.5 KiB
Python
126 lines
4.5 KiB
Python
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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(
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data_table.c.data["some key"].as_json()
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).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(
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data_table.c.data["some key"].as_string()
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).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(object):
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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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