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# ext/index.py
# Copyright (C) 2005-2021 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
"""Define attributes on ORM-mapped classes that have "index" attributes for
columns with :class:`_types.Indexable` types.
"index" means the attribute is associated with an element of an
:class:`_types.Indexable` column with the predefined index to access it.
The :class:`_types.Indexable` types include types such as
:class:`_types.ARRAY`, :class:`_types.JSON` and
:class:`_postgresql.HSTORE`.
The :mod:`~sqlalchemy.ext.indexable` extension provides
:class:`_schema.Column`-like interface for any element of an
:class:`_types.Indexable` typed column. In simple cases, it can be
treated as a :class:`_schema.Column` - mapped attribute.
.. versionadded:: 1.1
Synopsis
========
Given ``Person`` as a model with a primary key and JSON data field.
While this field may have any number of elements encoded within it,
we would like to refer to the element called ``name`` individually
as a dedicated attribute which behaves like a standalone column::
from sqlalchemy import Column, JSON, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.indexable import index_property
Base = declarative_base()
class Person(Base):
__tablename__ = 'person'
id = Column(Integer, primary_key=True)
data = Column(JSON)
name = index_property('data', 'name')
Above, the ``name`` attribute now behaves like a mapped column. We
can compose a new ``Person`` and set the value of ``name``::
>>> person = Person(name='Alchemist')
The value is now accessible::
>>> person.name
'Alchemist'
Behind the scenes, the JSON field was initialized to a new blank dictionary
and the field was set::
>>> person.data
{"name": "Alchemist'}
The field is mutable in place::
>>> person.name = 'Renamed'
>>> person.name
'Renamed'
>>> person.data
{'name': 'Renamed'}
When using :class:`.index_property`, the change that we make to the indexable
structure is also automatically tracked as history; we no longer need
to use :class:`~.mutable.MutableDict` in order to track this change
for the unit of work.
Deletions work normally as well::
>>> del person.name
>>> person.data
{}
Above, deletion of ``person.name`` deletes the value from the dictionary,
but not the dictionary itself.
A missing key will produce ``AttributeError``::
>>> person = Person()
>>> person.name
...
AttributeError: 'name'
Unless you set a default value::
>>> class Person(Base):
>>> __tablename__ = 'person'
>>>
>>> id = Column(Integer, primary_key=True)
>>> data = Column(JSON)
>>>
>>> name = index_property('data', 'name', default=None) # See default
>>> person = Person()
>>> print(person.name)
None
The attributes are also accessible at the class level.
Below, we illustrate ``Person.name`` used to generate
an indexed SQL criteria::
>>> from sqlalchemy.orm import Session
>>> session = Session()
>>> query = session.query(Person).filter(Person.name == 'Alchemist')
The above query is equivalent to::
>>> query = session.query(Person).filter(Person.data['name'] == 'Alchemist')
Multiple :class:`.index_property` objects can be chained to produce
multiple levels of indexing::
from sqlalchemy import Column, JSON, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.indexable import index_property
Base = declarative_base()
class Person(Base):
__tablename__ = 'person'
id = Column(Integer, primary_key=True)
data = Column(JSON)
birthday = index_property('data', 'birthday')
year = index_property('birthday', 'year')
month = index_property('birthday', 'month')
day = index_property('birthday', 'day')
Above, a query such as::
q = session.query(Person).filter(Person.year == '1980')
On a PostgreSQL backend, the above query will render as::
SELECT person.id, person.data
FROM person
WHERE person.data -> %(data_1)s -> %(param_1)s = %(param_2)s
Default Values
==============
:class:`.index_property` includes special behaviors for when the indexed
data structure does not exist, and a set operation is called:
* For an :class:`.index_property` that is given an integer index value,
the default data structure will be a Python list of ``None`` values,
at least as long as the index value; the value is then set at its
place in the list. This means for an index value of zero, the list
will be initialized to ``[None]`` before setting the given value,
and for an index value of five, the list will be initialized to
``[None, None, None, None, None]`` before setting the fifth element
to the given value. Note that an existing list is **not** extended
in place to receive a value.
* for an :class:`.index_property` that is given any other kind of index
value (e.g. strings usually), a Python dictionary is used as the
default data structure.
* The default data structure can be set to any Python callable using the
:paramref:`.index_property.datatype` parameter, overriding the previous
rules.
Subclassing
===========
:class:`.index_property` can be subclassed, in particular for the common
use case of providing coercion of values or SQL expressions as they are
accessed. Below is a common recipe for use with a PostgreSQL JSON type,
where we want to also include automatic casting plus ``astext()``::
class pg_json_property(index_property):
def __init__(self, attr_name, index, cast_type):
super(pg_json_property, self).__init__(attr_name, index)
self.cast_type = cast_type
def expr(self, model):
expr = super(pg_json_property, self).expr(model)
return expr.astext.cast(self.cast_type)
The above subclass can be used with the PostgreSQL-specific
version of :class:`_postgresql.JSON`::
from sqlalchemy import Column, Integer
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.dialects.postgresql import JSON
Base = declarative_base()
class Person(Base):
__tablename__ = 'person'
id = Column(Integer, primary_key=True)
data = Column(JSON)
age = pg_json_property('data', 'age', Integer)
The ``age`` attribute at the instance level works as before; however
when rendering SQL, PostgreSQL's ``->>`` operator will be used
for indexed access, instead of the usual index operator of ``->``::
>>> query = session.query(Person).filter(Person.age < 20)
The above query will render::
SELECT person.id, person.data
FROM person
WHERE CAST(person.data ->> %(data_1)s AS INTEGER) < %(param_1)s
""" # noqa
from __future__ import absolute_import
from .. import inspect
from .. import util
from ..ext.hybrid import hybrid_property
from ..orm.attributes import flag_modified
__all__ = ["index_property"]
class index_property(hybrid_property): # noqa
"""A property generator. The generated property describes an object
attribute that corresponds to an :class:`_types.Indexable`
column.
.. versionadded:: 1.1
.. seealso::
:mod:`sqlalchemy.ext.indexable`
"""
_NO_DEFAULT_ARGUMENT = object()
def __init__(
self,
attr_name,
index,
default=_NO_DEFAULT_ARGUMENT,
datatype=None,
mutable=True,
onebased=True,
):
"""Create a new :class:`.index_property`.
:param attr_name:
An attribute name of an `Indexable` typed column, or other
attribute that returns an indexable structure.
:param index:
The index to be used for getting and setting this value. This
should be the Python-side index value for integers.
:param default:
A value which will be returned instead of `AttributeError`
when there is not a value at given index.
:param datatype: default datatype to use when the field is empty.
By default, this is derived from the type of index used; a
Python list for an integer index, or a Python dictionary for
any other style of index. For a list, the list will be
initialized to a list of None values that is at least
``index`` elements long.
:param mutable: if False, writes and deletes to the attribute will
be disallowed.
:param onebased: assume the SQL representation of this value is
one-based; that is, the first index in SQL is 1, not zero.
"""
if mutable:
super(index_property, self).__init__(
self.fget, self.fset, self.fdel, self.expr
)
else:
super(index_property, self).__init__(
self.fget, None, None, self.expr
)
self.attr_name = attr_name
self.index = index
self.default = default
is_numeric = isinstance(index, int)
onebased = is_numeric and onebased
if datatype is not None:
self.datatype = datatype
else:
if is_numeric:
self.datatype = lambda: [None for x in range(index + 1)]
else:
self.datatype = dict
self.onebased = onebased
def _fget_default(self, err=None):
if self.default == self._NO_DEFAULT_ARGUMENT:
util.raise_(AttributeError(self.attr_name), replace_context=err)
else:
return self.default
def fget(self, instance):
attr_name = self.attr_name
column_value = getattr(instance, attr_name)
if column_value is None:
return self._fget_default()
try:
value = column_value[self.index]
except (KeyError, IndexError) as err:
return self._fget_default(err)
else:
return value
def fset(self, instance, value):
attr_name = self.attr_name
column_value = getattr(instance, attr_name, None)
if column_value is None:
column_value = self.datatype()
setattr(instance, attr_name, column_value)
column_value[self.index] = value
setattr(instance, attr_name, column_value)
if attr_name in inspect(instance).mapper.attrs:
flag_modified(instance, attr_name)
def fdel(self, instance):
attr_name = self.attr_name
column_value = getattr(instance, attr_name)
if column_value is None:
raise AttributeError(self.attr_name)
try:
del column_value[self.index]
except KeyError as err:
util.raise_(AttributeError(self.attr_name), replace_context=err)
else:
setattr(instance, attr_name, column_value)
flag_modified(instance, attr_name)
def expr(self, model):
column = getattr(model, self.attr_name)
index = self.index
if self.onebased:
index += 1
return column[index]