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342 lines
11 KiB
342 lines
11 KiB
# ext/indexable.py
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# Copyright (C) 2005-2024 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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"""Define attributes on ORM-mapped classes that have "index" attributes for
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columns with :class:`_types.Indexable` types.
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"index" means the attribute is associated with an element of an
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:class:`_types.Indexable` column with the predefined index to access it.
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The :class:`_types.Indexable` types include types such as
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:class:`_types.ARRAY`, :class:`_types.JSON` and
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:class:`_postgresql.HSTORE`.
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The :mod:`~sqlalchemy.ext.indexable` extension provides
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:class:`_schema.Column`-like interface for any element of an
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:class:`_types.Indexable` typed column. In simple cases, it can be
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treated as a :class:`_schema.Column` - mapped attribute.
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Synopsis
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========
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Given ``Person`` as a model with a primary key and JSON data field.
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While this field may have any number of elements encoded within it,
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we would like to refer to the element called ``name`` individually
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as a dedicated attribute which behaves like a standalone column::
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from sqlalchemy import Column, JSON, Integer
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.ext.indexable import index_property
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Base = declarative_base()
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class Person(Base):
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__tablename__ = 'person'
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id = Column(Integer, primary_key=True)
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data = Column(JSON)
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name = index_property('data', 'name')
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Above, the ``name`` attribute now behaves like a mapped column. We
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can compose a new ``Person`` and set the value of ``name``::
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>>> person = Person(name='Alchemist')
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The value is now accessible::
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>>> person.name
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'Alchemist'
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Behind the scenes, the JSON field was initialized to a new blank dictionary
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and the field was set::
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>>> person.data
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{"name": "Alchemist'}
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The field is mutable in place::
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>>> person.name = 'Renamed'
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>>> person.name
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'Renamed'
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>>> person.data
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{'name': 'Renamed'}
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When using :class:`.index_property`, the change that we make to the indexable
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structure is also automatically tracked as history; we no longer need
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to use :class:`~.mutable.MutableDict` in order to track this change
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for the unit of work.
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Deletions work normally as well::
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>>> del person.name
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>>> person.data
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{}
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Above, deletion of ``person.name`` deletes the value from the dictionary,
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but not the dictionary itself.
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A missing key will produce ``AttributeError``::
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>>> person = Person()
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>>> person.name
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...
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AttributeError: 'name'
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Unless you set a default value::
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>>> class Person(Base):
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>>> __tablename__ = 'person'
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>>>
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>>> id = Column(Integer, primary_key=True)
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>>> data = Column(JSON)
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>>>
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>>> name = index_property('data', 'name', default=None) # See default
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>>> person = Person()
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>>> print(person.name)
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None
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The attributes are also accessible at the class level.
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Below, we illustrate ``Person.name`` used to generate
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an indexed SQL criteria::
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>>> from sqlalchemy.orm import Session
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>>> session = Session()
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>>> query = session.query(Person).filter(Person.name == 'Alchemist')
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The above query is equivalent to::
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>>> query = session.query(Person).filter(Person.data['name'] == 'Alchemist')
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Multiple :class:`.index_property` objects can be chained to produce
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multiple levels of indexing::
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from sqlalchemy import Column, JSON, Integer
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.ext.indexable import index_property
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Base = declarative_base()
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class Person(Base):
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__tablename__ = 'person'
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id = Column(Integer, primary_key=True)
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data = Column(JSON)
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birthday = index_property('data', 'birthday')
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year = index_property('birthday', 'year')
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month = index_property('birthday', 'month')
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day = index_property('birthday', 'day')
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Above, a query such as::
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q = session.query(Person).filter(Person.year == '1980')
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On a PostgreSQL backend, the above query will render as::
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SELECT person.id, person.data
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FROM person
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WHERE person.data -> %(data_1)s -> %(param_1)s = %(param_2)s
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Default Values
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==============
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:class:`.index_property` includes special behaviors for when the indexed
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data structure does not exist, and a set operation is called:
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* For an :class:`.index_property` that is given an integer index value,
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the default data structure will be a Python list of ``None`` values,
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at least as long as the index value; the value is then set at its
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place in the list. This means for an index value of zero, the list
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will be initialized to ``[None]`` before setting the given value,
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and for an index value of five, the list will be initialized to
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``[None, None, None, None, None]`` before setting the fifth element
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to the given value. Note that an existing list is **not** extended
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in place to receive a value.
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* for an :class:`.index_property` that is given any other kind of index
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value (e.g. strings usually), a Python dictionary is used as the
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default data structure.
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* The default data structure can be set to any Python callable using the
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:paramref:`.index_property.datatype` parameter, overriding the previous
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rules.
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Subclassing
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===========
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:class:`.index_property` can be subclassed, in particular for the common
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use case of providing coercion of values or SQL expressions as they are
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accessed. Below is a common recipe for use with a PostgreSQL JSON type,
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where we want to also include automatic casting plus ``astext()``::
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class pg_json_property(index_property):
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def __init__(self, attr_name, index, cast_type):
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super(pg_json_property, self).__init__(attr_name, index)
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self.cast_type = cast_type
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def expr(self, model):
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expr = super(pg_json_property, self).expr(model)
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return expr.astext.cast(self.cast_type)
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The above subclass can be used with the PostgreSQL-specific
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version of :class:`_postgresql.JSON`::
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from sqlalchemy import Column, Integer
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.dialects.postgresql import JSON
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Base = declarative_base()
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class Person(Base):
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__tablename__ = 'person'
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id = Column(Integer, primary_key=True)
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data = Column(JSON)
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age = pg_json_property('data', 'age', Integer)
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The ``age`` attribute at the instance level works as before; however
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when rendering SQL, PostgreSQL's ``->>`` operator will be used
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for indexed access, instead of the usual index operator of ``->``::
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>>> query = session.query(Person).filter(Person.age < 20)
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The above query will render::
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SELECT person.id, person.data
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FROM person
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WHERE CAST(person.data ->> %(data_1)s AS INTEGER) < %(param_1)s
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""" # noqa
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from .. import inspect
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from ..ext.hybrid import hybrid_property
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from ..orm.attributes import flag_modified
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__all__ = ["index_property"]
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class index_property(hybrid_property): # noqa
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"""A property generator. The generated property describes an object
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attribute that corresponds to an :class:`_types.Indexable`
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column.
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.. seealso::
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:mod:`sqlalchemy.ext.indexable`
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"""
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_NO_DEFAULT_ARGUMENT = object()
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def __init__(
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self,
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attr_name,
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index,
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default=_NO_DEFAULT_ARGUMENT,
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datatype=None,
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mutable=True,
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onebased=True,
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):
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"""Create a new :class:`.index_property`.
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:param attr_name:
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An attribute name of an `Indexable` typed column, or other
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attribute that returns an indexable structure.
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:param index:
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The index to be used for getting and setting this value. This
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should be the Python-side index value for integers.
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:param default:
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A value which will be returned instead of `AttributeError`
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when there is not a value at given index.
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:param datatype: default datatype to use when the field is empty.
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By default, this is derived from the type of index used; a
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Python list for an integer index, or a Python dictionary for
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any other style of index. For a list, the list will be
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initialized to a list of None values that is at least
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``index`` elements long.
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:param mutable: if False, writes and deletes to the attribute will
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be disallowed.
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:param onebased: assume the SQL representation of this value is
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one-based; that is, the first index in SQL is 1, not zero.
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"""
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if mutable:
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super().__init__(self.fget, self.fset, self.fdel, self.expr)
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else:
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super().__init__(self.fget, None, None, self.expr)
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self.attr_name = attr_name
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self.index = index
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self.default = default
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is_numeric = isinstance(index, int)
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onebased = is_numeric and onebased
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if datatype is not None:
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self.datatype = datatype
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else:
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if is_numeric:
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self.datatype = lambda: [None for x in range(index + 1)]
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else:
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self.datatype = dict
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self.onebased = onebased
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def _fget_default(self, err=None):
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if self.default == self._NO_DEFAULT_ARGUMENT:
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raise AttributeError(self.attr_name) from err
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else:
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return self.default
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def fget(self, instance):
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attr_name = self.attr_name
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column_value = getattr(instance, attr_name)
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if column_value is None:
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return self._fget_default()
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try:
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value = column_value[self.index]
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except (KeyError, IndexError) as err:
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return self._fget_default(err)
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else:
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return value
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def fset(self, instance, value):
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attr_name = self.attr_name
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column_value = getattr(instance, attr_name, None)
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if column_value is None:
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column_value = self.datatype()
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setattr(instance, attr_name, column_value)
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column_value[self.index] = value
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setattr(instance, attr_name, column_value)
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if attr_name in inspect(instance).mapper.attrs:
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flag_modified(instance, attr_name)
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def fdel(self, instance):
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attr_name = self.attr_name
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column_value = getattr(instance, attr_name)
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if column_value is None:
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raise AttributeError(self.attr_name)
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try:
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del column_value[self.index]
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except KeyError as err:
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raise AttributeError(self.attr_name) from err
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else:
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setattr(instance, attr_name, column_value)
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flag_modified(instance, attr_name)
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def expr(self, model):
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column = getattr(model, self.attr_name)
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index = self.index
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if self.onebased:
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index += 1
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return column[index]
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