# ext/index.py # Copyright (C) 2005-2019 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 sqlalchemy import inspect 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): if self.default == self._NO_DEFAULT_ARGUMENT: raise AttributeError(self.attr_name) 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): return self._fget_default() 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: raise AttributeError(self.attr_name) 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]