Hybrid Attributes

Define attributes on ORM-mapped classes that have “hybrid” behavior.

“hybrid” means the attribute has distinct behaviors defined at the class level and at the instance level.

The hybrid extension provides a special form of method decorator and has minimal dependencies on the rest of SQLAlchemy. Its basic theory of operation can work with any descriptor-based expression system.

Consider a mapping Interval, representing integer start and end values. We can define higher level functions on mapped classes that produce SQL expressions at the class level, and Python expression evaluation at the instance level. Below, each function decorated with hybrid_method or hybrid_property may receive self as an instance of the class, or may receive the class directly, depending on context:

from __future__ import annotations

from sqlalchemy.ext.hybrid import hybrid_method
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column


class Base(DeclarativeBase):
    pass


class Interval(Base):
    __tablename__ = "interval"

    id: Mapped[int] = mapped_column(primary_key=True)
    start: Mapped[int]
    end: Mapped[int]

    def __init__(self, start: int, end: int):
        self.start = start
        self.end = end

    @hybrid_property
    def length(self) -> int:
        return self.end - self.start

    @hybrid_method
    def contains(self, point: int) -> bool:
        return (self.start <= point) & (point <= self.end)

    @hybrid_method
    def intersects(self, other: Interval) -> bool:
        return self.contains(other.start) | self.contains(other.end)

Above, the length property returns the difference between the end and start attributes. With an instance of Interval, this subtraction occurs in Python, using normal Python descriptor mechanics:

>>> i1 = Interval(5, 10)
>>> i1.length
5

When dealing with the Interval class itself, the hybrid_property descriptor evaluates the function body given the Interval class as the argument, which when evaluated with SQLAlchemy expression mechanics returns a new SQL expression:

>>> from sqlalchemy import select
>>> print(select(Interval.length))

SELECT interval."end" - interval.start AS length
FROM interval

>>> print(select(Interval).filter(Interval.length > 10))

SELECT interval.id, interval.start, interval."end"
FROM interval
WHERE interval."end" - interval.start > :param_1

Filtering methods such as Select.filter_by() are supported with hybrid attributes as well:

>>> print(select(Interval).filter_by(length=5))

SELECT interval.id, interval.start, interval."end"
FROM interval
WHERE interval."end" - interval.start = :param_1

The Interval class example also illustrates two methods, contains() and intersects(), decorated with hybrid_method. This decorator applies the same idea to methods that hybrid_property applies to attributes. The methods return boolean values, and take advantage of the Python | and & bitwise operators to produce equivalent instance-level and SQL expression-level boolean behavior:

>>> i1.contains(6)
True
>>> i1.contains(15)
False
>>> i1.intersects(Interval(7, 18))
True
>>> i1.intersects(Interval(25, 29))
False

>>> print(select(Interval).filter(Interval.contains(15)))

SELECT interval.id, interval.start, interval."end"
FROM interval
WHERE interval.start <= :start_1 AND interval."end" > :end_1

>>> ia = aliased(Interval)
>>> print(select(Interval, ia).filter(Interval.intersects(ia)))

SELECT interval.id, interval.start,
interval."end", interval_1.id AS interval_1_id,
interval_1.start AS interval_1_start, interval_1."end" AS interval_1_end
FROM interval, interval AS interval_1
WHERE interval.start <= interval_1.start
    AND interval."end" > interval_1.start
    OR interval.start <= interval_1."end"
    AND interval."end" > interval_1."end"

Defining Expression Behavior Distinct from Attribute Behavior

In the previous section, our usage of the & and | bitwise operators within the Interval.contains and Interval.intersects methods was fortunate, considering our functions operated on two boolean values to return a new one. In many cases, the construction of an in-Python function and a SQLAlchemy SQL expression have enough differences that two separate Python expressions should be defined. The hybrid decorator defines a modifier hybrid_property.expression() for this purpose. As an example we’ll define the radius of the interval, which requires the usage of the absolute value function:

from sqlalchemy import ColumnElement
from sqlalchemy import Float
from sqlalchemy import func
from sqlalchemy import type_coerce


class Interval(Base):
    # ...

    @hybrid_property
    def radius(self) -> float:
        return abs(self.length) / 2

    @radius.inplace.expression
    @classmethod
    def _radius_expression(cls) -> ColumnElement[float]:
        return type_coerce(func.abs(cls.length) / 2, Float)

In the above example, the hybrid_property first assigned to the name Interval.radius is amended by a subsequent method called Interval._radius_expression, using the decorator @radius.inplace.expression, which chains together two modifiers hybrid_property.inplace and hybrid_property.expression. The use of hybrid_property.inplace indicates that the hybrid_property.expression() modifier should mutate the existing hybrid object at Interval.radius in place, without creating a new object. Notes on this modifier and its rationale are discussed in the next section Using inplace to create pep-484 compliant hybrid properties. The use of @classmethod is optional, and is strictly to give typing tools a hint that cls in this case is expected to be the Interval class, and not an instance of Interval.

Note

hybrid_property.inplace as well as the use of @classmethod for proper typing support are available as of SQLAlchemy 2.0.4, and will not work in earlier versions.

With Interval.radius now including an expression element, the SQL function ABS() is returned when accessing Interval.radius at the class level:

>>> from sqlalchemy import select
>>> print(select(Interval).filter(Interval.radius > 5))

SELECT interval.id, interval.start, interval."end"
FROM interval
WHERE abs(interval."end" - interval.start) / :abs_1 > :param_1

Using inplace to create pep-484 compliant hybrid properties

In the previous section, a hybrid_property decorator is illustrated which includes two separate method-level functions being decorated, both to produce a single object attribute referenced as Interval.radius. There are actually several different modifiers we can use for hybrid_property including hybrid_property.expression(), hybrid_property.setter() and hybrid_property.update_expression().

SQLAlchemy’s hybrid_property decorator intends that adding on these methods may be done in the identical manner as Python’s built-in @property decorator, where idiomatic use is to continue to redefine the attribute repeatedly, using the same attribute name each time, as in the example below that illustrates the use of hybrid_property.setter() and hybrid_property.expression() for the Interval.radius descriptor:

# correct use, however is not accepted by pep-484 tooling


class Interval(Base):
    # ...

    @hybrid_property
    def radius(self):
        return abs(self.length) / 2

    @radius.setter
    def radius(self, value):
        self.length = value * 2

    @radius.expression
    def radius(cls):
        return type_coerce(func.abs(cls.length) / 2, Float)

Above, there are three Interval.radius methods, but as each are decorated, first by the hybrid_property decorator and then by the @radius name itself, the end effect is that Interval.radius is a single attribute with three different functions contained within it. This style of use is taken from Python’s documented use of @property. It is important to note that the way both @property as well as hybrid_property work, a copy of the descriptor is made each time. That is, each call to @radius.expression, @radius.setter etc. make a new object entirely. This allows the attribute to be re-defined in subclasses without issue (see Reusing Hybrid Properties across Subclasses later in this section for how this is used).

However, the above approach is not compatible with typing tools such as mypy and pyright. Python’s own @property decorator does not have this limitation only because these tools hardcode the behavior of @property, meaning this syntax is not available to SQLAlchemy under PEP 484 compliance.

In order to produce a reasonable syntax while remaining typing compliant, the hybrid_property.inplace decorator allows the same decorator to be re-used with different method names, while still producing a single decorator under one name:

# correct use which is also accepted by pep-484 tooling


class Interval(Base):
    # ...

    @hybrid_property
    def radius(self) -> float:
        return abs(self.length) / 2

    @radius.inplace.setter
    def _radius_setter(self, value: float) -> None:
        # for example only
        self.length = value * 2

    @radius.inplace.expression
    @classmethod
    def _radius_expression(cls) -> ColumnElement[float]:
        return type_coerce(func.abs(cls.length) / 2, Float)

Using hybrid_property.inplace further qualifies the use of the decorator that a new copy should not be made, thereby maintaining the Interval.radius name while allowing additional methods Interval._radius_setter and Interval._radius_expression to be differently named.

Added in version 2.0.4: Added hybrid_property.inplace to allow less verbose construction of composite hybrid_property objects while not having to use repeated method names. Additionally allowed the use of @classmethod within hybrid_property.expression, hybrid_property.update_expression, and hybrid_property.comparator to allow typing tools to identify cls as a class and not an instance in the method signature.

Defining Setters

The hybrid_property.setter() modifier allows the construction of a custom setter method, that can modify values on the object:

class Interval(Base):
    # ...

    @hybrid_property
    def length(self) -> int:
        return self.end - self.start

    @length.inplace.setter
    def _length_setter(self, value: int) -> None:
        self.end = self.start + value

The length(self, value) method is now called upon set:

>>> i1 = Interval(5, 10)
>>> i1.length
5
>>> i1.length = 12
>>> i1.end
17

Supporting ORM Bulk INSERT and UPDATE

Hybrids have support for use in ORM Bulk INSERT/UPDATE operations described at ORM-Enabled INSERT, UPDATE, and DELETE statements. There are two distinct hooks that may be used supply a hybrid value within a DML operation:

  1. The hybrid_property.update_expression() hook indicates a method that can provide one or more expressions to render in the SET clause of an UPDATE or INSERT statement, in response to when a hybrid attribute is referenced directly in the UpdateBase.values() method; i.e. the use shown in ORM UPDATE and DELETE with Custom WHERE Criteria and ORM Bulk Insert with Per Row SQL Expressions

  2. The hybrid_property.bulk_dml() hook indicates a method that can intercept individual parameter dictionaries sent to Session.execute(), i.e. the use shown at ORM Bulk INSERT Statements as well as ORM Bulk UPDATE by Primary Key.

Using update_expression with update.values() and insert.values()

The hybrid_property.update_expression() decorator indicates a method that is invoked when a hybrid is used in the ValuesBase.values() clause of an update() or insert() statement. It returns a list of tuple pairs [(x1, y1), (x2, y2), ...] which will expand into the SET clause of an UPDATE statement as SET x1=y1, x2=y2, ....

The from_dml_column() construct is often useful as it can create a SQL expression that refers to another column that may also present in the same INSERT or UPDATE statement, alternatively falling back to referring to the original column if such an expression is not present.

In the example below, the total_price hybrid will derive the price column, by taking the given “total price” value and dividing it by a tax_rate value that is also present in the ValuesBase.values() call:

from sqlalchemy import from_dml_column


class Product(Base):
    __tablename__ = "product"

    id: Mapped[int] = mapped_column(primary_key=True)
    price: Mapped[float]
    tax_rate: Mapped[float]

    @hybrid_property
    def total_price(self) -> float:
        return self.price * (1 + self.tax_rate)

    @total_price.inplace.update_expression
    @classmethod
    def _total_price_update_expression(
        cls, value: Any
    ) -> List[Tuple[Any, Any]]:
        return [(cls.price, value / (1 + from_dml_column(cls.tax_rate)))]

When used in an UPDATE statement, from_dml_column() creates a reference to the tax_rate column that will use the value passed to the ValuesBase.values() method, rather than the existing value on the column in the database. This allows the hybrid to access other values being updated in the same statement:

>>> from sqlalchemy import update
>>> print(
...     update(Product).values(
...         {Product.tax_rate: 0.08, Product.total_price: 125.00}
...     )
... )

UPDATE product SET tax_rate=:tax_rate, price=(:total_price / (:tax_rate + :param_1))

When the column referenced by from_dml_column() (in this case product.tax_rate) is omitted from ValuesBase.values(), the rendered expression falls back to using the original column:

>>> from sqlalchemy import update
>>> print(update(Product).values({Product.total_price: 125.00}))

UPDATE product SET price=(:total_price / (tax_rate + :param_1))

Using bulk_dml to intercept bulk parameter dictionaries

Added in version 2.1.

For bulk operations that pass a list of parameter dictionaries to methods like Session.execute(), the hybrid_property.bulk_dml() decorator provides a hook that can receive each dictionary and populate it with new values.

The implementation for the hybrid_property.bulk_dml() hook can retrieve other column values from the parameter dictionary:

from typing import MutableMapping


class Product(Base):
    __tablename__ = "product"

    id: Mapped[int] = mapped_column(primary_key=True)
    price: Mapped[float]
    tax_rate: Mapped[float]

    @hybrid_property
    def total_price(self) -> float:
        return self.price * (1 + self.tax_rate)

    @total_price.inplace.bulk_dml
    @classmethod
    def _total_price_bulk_dml(
        cls, mapping: MutableMapping[str, Any], value: float
    ) -> None:
        mapping["price"] = value / (1 + mapping["tax_rate"])

This allows for bulk INSERT/UPDATE with derived values:

# Bulk INSERT
session.execute(
    insert(Product),
    [
        {"tax_rate": 0.08, "total_price": 125.00},
        {"tax_rate": 0.05, "total_price": 110.00},
    ],
)

Note that the method decorated by hybrid_property.bulk_dml() is invoked only with parameter dictionaries and does not have the ability to use SQL expressions in the given dictionaries, only literal Python values that will be passed to parameters in the INSERT or UPDATE statement.

See also

ORM-Enabled INSERT, UPDATE, and DELETE statements - includes background on ORM-enabled UPDATE statements

Working with Relationships

There’s no essential difference when creating hybrids that work with related objects as opposed to column-based data. The need for distinct expressions tends to be greater. The two variants we’ll illustrate are the “join-dependent” hybrid, and the “correlated subquery” hybrid.

Join-Dependent Relationship Hybrid

Consider the following declarative mapping which relates a User to a SavingsAccount:

from __future__ import annotations

from decimal import Decimal
from typing import cast
from typing import List
from typing import Optional

from sqlalchemy import ForeignKey
from sqlalchemy import Numeric
from sqlalchemy import String
from sqlalchemy import SQLColumnExpression
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.orm import relationship


class Base(DeclarativeBase):
    pass


class SavingsAccount(Base):
    __tablename__ = "account"
    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("user.id"))
    balance: Mapped[Decimal] = mapped_column(Numeric(15, 5))

    owner: Mapped[User] = relationship(back_populates="accounts")


class User(Base):
    __tablename__ = "user"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(100))

    accounts: Mapped[List[SavingsAccount]] = relationship(
        back_populates="owner", lazy="selectin"
    )

    @hybrid_property
    def balance(self) -> Optional[Decimal]:
        if self.accounts:
            return self.accounts[0].balance
        else:
            return None

    @balance.inplace.setter
    def _balance_setter(self, value: Optional[Decimal]) -> None:
        assert value is not None

        if not self.accounts:
            account = SavingsAccount(owner=self)
        else:
            account = self.accounts[0]
        account.balance = value

    @balance.inplace.expression
    @classmethod
    def _balance_expression(cls) -> SQLColumnExpression[Optional[Decimal]]:
        return cast(
            "SQLColumnExpression[Optional[Decimal]]",
            SavingsAccount.balance,
        )

The above hybrid property balance works with the first SavingsAccount entry in the list of accounts for this user. The in-Python getter/setter methods can treat accounts as a Python list available on self.

Tip

The User.balance getter in the above example accesses the self.acccounts collection, which will normally be loaded via the selectinload() loader strategy configured on the User.balance relationship(). The default loader strategy when not otherwise stated on relationship() is lazyload(), which emits SQL on demand. When using asyncio, on-demand loaders such as lazyload() are not supported, so care should be taken to ensure the self.accounts collection is accessible to this hybrid accessor when using asyncio.

At the expression level, it’s expected that the User class will be used in an appropriate context such that an appropriate join to SavingsAccount will be present:

>>> from sqlalchemy import select
>>> print(
...     select(User, User.balance)
...     .join(User.accounts)
...     .filter(User.balance > 5000)
... )

SELECT "user".id AS user_id, "user".name AS user_name,
account.balance AS account_balance
FROM "user" JOIN account ON "user".id = account.user_id
WHERE account.balance > :balance_1

Note however, that while the instance level accessors need to worry about whether self.accounts is even present, this issue expresses itself differently at the SQL expression level, where we basically would use an outer join:

>>> from sqlalchemy import select
>>> from sqlalchemy import or_
>>> print(
...     select(User, User.balance)
...     .outerjoin(User.accounts)
...     .filter(or_(User.balance < 5000, User.balance == None))
... )

SELECT "user".id AS user_id, "user".name AS user_name,
account.balance AS account_balance
FROM "user" LEFT OUTER JOIN account ON "user".id = account.user_id
WHERE account.balance <  :balance_1 OR account.balance IS NULL

Correlated Subquery Relationship Hybrid

We can, of course, forego being dependent on the enclosing query’s usage of joins in favor of the correlated subquery, which can portably be packed into a single column expression. A correlated subquery is more portable, but often performs more poorly at the SQL level. Using the same technique illustrated at Using column_property, we can adjust our SavingsAccount example to aggregate the balances for all accounts, and use a correlated subquery for the column expression:

from __future__ import annotations

from decimal import Decimal
from typing import List

from sqlalchemy import ForeignKey
from sqlalchemy import func
from sqlalchemy import Numeric
from sqlalchemy import select
from sqlalchemy import SQLColumnExpression
from sqlalchemy import String
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.orm import relationship


class Base(DeclarativeBase):
    pass


class SavingsAccount(Base):
    __tablename__ = "account"
    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("user.id"))
    balance: Mapped[Decimal] = mapped_column(Numeric(15, 5))

    owner: Mapped[User] = relationship(back_populates="accounts")


class User(Base):
    __tablename__ = "user"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(100))

    accounts: Mapped[List[SavingsAccount]] = relationship(
        back_populates="owner", lazy="selectin"
    )

    @hybrid_property
    def balance(self) -> Decimal:
        return sum(
            (acc.balance for acc in self.accounts), start=Decimal("0")
        )

    @balance.inplace.expression
    @classmethod
    def _balance_expression(cls) -> SQLColumnExpression[Decimal]:
        return (
            select(func.sum(SavingsAccount.balance))
            .where(SavingsAccount.user_id == cls.id)
            .label("total_balance")
        )

The above recipe will give us the balance column which renders a correlated SELECT:

>>> from sqlalchemy import select
>>> print(select(User).filter(User.balance > 400))

SELECT "user".id, "user".name
FROM "user"
WHERE (
    SELECT sum(account.balance) AS sum_1 FROM account
    WHERE account.user_id = "user".id
) > :param_1

Building Custom Comparators

The hybrid property also includes a helper that allows construction of custom comparators. A comparator object allows one to customize the behavior of each SQLAlchemy expression operator individually. They are useful when creating custom types that have some highly idiosyncratic behavior on the SQL side.

Note

The hybrid_property.comparator() decorator introduced in this section replaces the use of the hybrid_property.expression() decorator. They cannot be used together.

The example class below allows case-insensitive comparisons on the attribute named word_insensitive:

from __future__ import annotations

from typing import Any

from sqlalchemy import ColumnElement
from sqlalchemy import func
from sqlalchemy.ext.hybrid import Comparator
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column


class Base(DeclarativeBase):
    pass


class CaseInsensitiveComparator(Comparator[str]):
    def __eq__(self, other: Any) -> ColumnElement[bool]:  # type: ignore[override]  # noqa: E501
        return func.lower(self.__clause_element__()) == func.lower(other)


class SearchWord(Base):
    __tablename__ = "searchword"

    id: Mapped[int] = mapped_column(primary_key=True)
    word: Mapped[str]

    @hybrid_property
    def word_insensitive(self) -> str:
        return self.word.lower()

    @word_insensitive.inplace.comparator
    @classmethod
    def _word_insensitive_comparator(cls) -> CaseInsensitiveComparator:
        return CaseInsensitiveComparator(cls.word)

Above, SQL expressions against word_insensitive will apply the LOWER() SQL function to both sides:

>>> from sqlalchemy import select
>>> print(select(SearchWord).filter_by(word_insensitive="Trucks"))

SELECT searchword.id, searchword.word
FROM searchword
WHERE lower(searchword.word) = lower(:lower_1)

The CaseInsensitiveComparator above implements part of the ColumnOperators interface. A “coercion” operation like lowercasing can be applied to all comparison operations (i.e. eq, lt, gt, etc.) using Operators.operate():

class CaseInsensitiveComparator(Comparator):
    def operate(self, op, other, **kwargs):
        return op(
            func.lower(self.__clause_element__()),
            func.lower(other),
            **kwargs,
        )

Reusing Hybrid Properties across Subclasses

A hybrid can be referred to from a superclass, to allow modifying methods like hybrid_property.getter(), hybrid_property.setter() to be used to redefine those methods on a subclass. This is similar to how the standard Python @property object works:

class FirstNameOnly(Base):
    # ...

    first_name: Mapped[str]

    @hybrid_property
    def name(self) -> str:
        return self.first_name

    @name.inplace.setter
    def _name_setter(self, value: str) -> None:
        self.first_name = value


class FirstNameLastName(FirstNameOnly):
    # ...

    last_name: Mapped[str]

    # 'inplace' is not used here; calling getter creates a copy
    # of FirstNameOnly.name that is local to FirstNameLastName
    @FirstNameOnly.name.getter
    def name(self) -> str:
        return self.first_name + " " + self.last_name

    @name.inplace.setter
    def _name_setter(self, value: str) -> None:
        self.first_name, self.last_name = value.split(" ", 1)

Above, the FirstNameLastName class refers to the hybrid from FirstNameOnly.name to repurpose its getter and setter for the subclass.

When overriding hybrid_property.expression() and hybrid_property.comparator() alone as the first reference to the superclass, these names conflict with the same-named accessors on the class- level QueryableAttribute object returned at the class level. To override these methods when referring directly to the parent class descriptor, add the special qualifier hybrid_property.overrides, which will de- reference the instrumented attribute back to the hybrid object:

class FirstNameLastName(FirstNameOnly):
    # ...

    last_name: Mapped[str]

    @FirstNameOnly.name.overrides.expression
    @classmethod
    def name(cls):
        return func.concat(cls.first_name, " ", cls.last_name)

Hybrid Value Objects

In the example shown previously at Building Custom Comparators, if we were to compare the word_insensitive attribute of a SearchWord instance to a plain Python string, the plain Python string would not be coerced to lower case - the CaseInsensitiveComparator we built, being returned by @word_insensitive.comparator, only applies to the SQL side.

A more comprehensive form of the custom comparator is to construct a Hybrid Value Object. This technique applies the target value or expression to a value object which is then returned by the accessor in all cases. The value object allows control of all operations upon the value as well as how compared values are treated, both on the SQL expression side as well as the Python value side. Replacing the previous CaseInsensitiveComparator class with a new CaseInsensitiveWord class:

from sqlalchemy import func
from sqlalchemy.ext.hybrid import Comparator


class CaseInsensitiveWord(Comparator):
    "Hybrid value representing a lower case representation of a word."

    def __init__(self, word):
        if isinstance(word, str):
            self.word = word.lower()
        else:
            self.word = func.lower(word)

    def operate(self, op, other, **kwargs):
        if not isinstance(other, CaseInsensitiveWord):
            other = CaseInsensitiveWord(other)
        return op(self.word, other.word, **kwargs)

    def __clause_element__(self):
        return self.word

    def __str__(self):
        return self.word

    key = "word"
    "Label to apply to Query tuple results"

Above, the CaseInsensitiveWord object represents self.word, which may be a SQL function, or may be a Python native string. The hybrid value object should implement __clause_element__(), which allows the object to be coerced into a SQL-capable value when used in SQL expression constructs, as well as Python comparison methods such as __eq__(), which is accomplished in the above example by subclassing Comparator and overriding the operate() method.

With __clause_element__() provided, our SearchWord class can now deliver the CaseInsensitiveWord object unconditionally from a single hybrid method, returning an object that behaves appropriately in both value-based and SQL contexts:

class SearchWord(Base):
    __tablename__ = "searchword"
    id: Mapped[int] = mapped_column(primary_key=True)
    word: Mapped[str]

    @hybrid_property
    def word_insensitive(self) -> CaseInsensitiveWord:
        return CaseInsensitiveWord(self.word)

The class-level version of CaseInsensitiveWord will work in SQL constructs:

>>> print(select(SearchWord).filter(SearchWord.word_insensitive == "Trucks"))

SELECT searchword.id AS searchword_id, searchword.word AS searchword_word
FROM searchword
WHERE lower(searchword.word) = :lower_1

By also subclassing Comparator and providing an implementation for operate(), the word_insensitive attribute also has case-insensitive comparison behavior universally, including SQL expression and Python expression (note the Python value is converted to lower case on the Python side here):

>>> from sqlalchemy.orm import aliased
>>> sw1 = aliased(SearchWord)
>>> sw2 = aliased(SearchWord)
>>> print(
...     select(sw1.word_insensitive, sw2.word_insensitive).filter(
...         sw1.word_insensitive > sw2.word_insensitive
...     )
... )

SELECT lower(searchword_1.word) AS lower_1,
lower(searchword_2.word) AS lower_2
FROM searchword AS searchword_1, searchword AS searchword_2
WHERE lower(searchword_1.word) > lower(searchword_2.word)

Python only expression:

>>> ws1 = SearchWord(word="SomeWord")
>>> ws1.word_insensitive == "sOmEwOrD"
True
>>> ws1.word_insensitive == "XOmEwOrX"
False
>>> print(ws1.word_insensitive)
someword

The Hybrid Value pattern is very useful for any kind of value that may have multiple representations, such as timestamps, time deltas, units of measurement, currencies and encrypted passwords.

See also

Hybrids and Value Agnostic Types - on the techspot.zzzeek.org blog

Value Agnostic Types, Part II - on the techspot.zzzeek.org blog

Composite Hybrid Value Objects

The functionality of Hybrid Value Objects may also be expanded to support “composite” forms; in this pattern, SQLAlchemy hybrids begin to approximate most (though not all) the same functionality that is available from the ORM natively via the Composite Column Types feature. We can imitate the example of Point and Vertex from that section using hybrids, where Point is modified to become a Hybrid Value Object:

from dataclasses import dataclass

from sqlalchemy import tuple_
from sqlalchemy.ext.hybrid import Comparator
from sqlalchemy import SQLColumnExpression


@dataclass(eq=False)
class Point(Comparator):
    x: int | SQLColumnExpression[int]
    y: int | SQLColumnExpression[int]

    def operate(self, op, other, **kwargs):
        return op(self.x, other.x) & op(self.y, other.y)

    def __clause_element__(self):
        return tuple_(self.x, self.y)

Above, the operate() method is where the most “hybrid” behavior takes place, making use of op() (the Python operator function in use) along with the the bitwise & operator provides us with the SQL AND operator in a SQL context, and boolean “and” in a Python boolean context.

Following from there, the owning Vertex class now uses hybrids to represent start and end:

from sqlalchemy.orm import DeclarativeBase, Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.ext.hybrid import hybrid_property


class Base(DeclarativeBase):
    pass


class Vertex(Base):
    __tablename__ = "vertices"

    id: Mapped[int] = mapped_column(primary_key=True)

    x1: Mapped[int]
    y1: Mapped[int]
    x2: Mapped[int]
    y2: Mapped[int]

    @hybrid_property
    def start(self) -> Point:
        return Point(self.x1, self.y1)

    @start.inplace.setter
    def _set_start(self, value: Point) -> None:
        self.x1 = value.x
        self.y1 = value.y

    @hybrid_property
    def end(self) -> Point:
        return Point(self.x2, self.y2)

    @end.inplace.setter
    def _set_end(self, value: Point) -> None:
        self.x2 = value.x
        self.y2 = value.y

    def __repr__(self) -> str:
        return f"Vertex(start={self.start}, end={self.end})"

Using the above mapping, we can use expressions at the Python or SQL level using Vertex.start and Vertex.end:

>>> v1 = Vertex(start=Point(3, 4), end=Point(15, 10))
>>> v1.end == Point(15, 10)
True
>>> stmt = (
...     select(Vertex)
...     .where(Vertex.start == Point(3, 4))
...     .where(Vertex.end < Point(7, 8))
... )
>>> print(stmt)
SELECT vertices.id, vertices.x1, vertices.y1, vertices.x2, vertices.y2
FROM vertices
WHERE vertices.x1 = :x1_1 AND vertices.y1 = :y1_1 AND vertices.x2 < :x2_1 AND vertices.y2 < :y2_1

DML Support for Composite Value Objects

Composite value objects like Point can also be used with the ORM’s DML features. The hybrid_property.update_expression() decorator allows the hybrid to expand a composite value into multiple column assignments in UPDATE and INSERT statements:

class Location(Base):
    __tablename__ = "location"

    id: Mapped[int] = mapped_column(primary_key=True)
    x: Mapped[int]
    y: Mapped[int]

    @hybrid_property
    def coordinates(self) -> Point:
        return Point(self.x, self.y)

    @coordinates.inplace.update_expression
    @classmethod
    def _coordinates_update_expression(
        cls, value: Any
    ) -> List[Tuple[Any, Any]]:
        assert isinstance(value, Point)
        return [(cls.x, value.x), (cls.y, value.y)]

This allows UPDATE statements to work with the composite value:

>>> from sqlalchemy import update
>>> print(
...     update(Location)
...     .where(Location.id == 5)
...     .values({Location.coordinates: Point(25, 17)})
... )

UPDATE location SET x=:x, y=:y WHERE location.id = :id_1

For bulk operations that use parameter dictionaries, the hybrid_property.bulk_dml() decorator provides a hook to convert composite values into individual column values:

from typing import MutableMapping


class Location(Base):
    # ... (same as above)

    @coordinates.inplace.bulk_dml
    @classmethod
    def _coordinates_bulk_dml(
        cls, mapping: MutableMapping[str, Any], value: Point
    ) -> None:
        mapping["x"] = value.x
        mapping["y"] = value.y

This enables bulk operations with composite values:

# Bulk INSERT
session.execute(
    insert(Location),
    [
        {"id": 1, "coordinates": Point(10, 20)},
        {"id": 2, "coordinates": Point(30, 40)},
    ],
)

# Bulk UPDATE
session.execute(
    update(Location),
    [
        {"id": 1, "coordinates": Point(15, 25)},
        {"id": 2, "coordinates": Point(35, 45)},
    ],
)

API Reference

Object Name Description

Comparator

A helper class that allows easy construction of custom PropComparator classes for usage with hybrids.

hybrid_method

A decorator which allows definition of a Python object method with both instance-level and class-level behavior.

hybrid_property

A decorator which allows definition of a Python descriptor with both instance-level and class-level behavior.

HybridExtensionType
class sqlalchemy.ext.hybrid.hybrid_method

inherits from sqlalchemy.orm.base.InspectionAttrInfo, typing.Generic

A decorator which allows definition of a Python object method with both instance-level and class-level behavior.

Member Name Description

__init__()

Create a new hybrid_method.

expression()

Provide a modifying decorator that defines a SQL-expression producing method.

extension_type

The extension type, if any. Defaults to NotExtension.NOT_EXTENSION

inplace

Return the inplace mutator for this hybrid_method.

is_attribute

True if this object is a Python descriptor.
method sqlalchemy.ext.hybrid.hybrid_method.__init__(func: Callable[[Concatenate[Any, _P]], _R], expr: Callable[[Concatenate[Any, _P]], SQLCoreOperations[_R]] | None = None)

Create a new hybrid_method.

Usage is typically via decorator:

from sqlalchemy.ext.hybrid import hybrid_method


class SomeClass:
    @hybrid_method
    def value(self, x, y):
        return self._value + x + y

    @value.expression
    @classmethod
    def value(cls, x, y):
        return func.some_function(cls._value, x, y)
method sqlalchemy.ext.hybrid.hybrid_method.expression(expr: Callable[[Concatenate[Any, _P]], SQLCoreOperations[_R]]) → hybrid_method[_P, _R]

Provide a modifying decorator that defines a SQL-expression producing method.

attribute sqlalchemy.ext.hybrid.hybrid_method.extension_type: InspectionAttrExtensionType = 'HYBRID_METHOD'

The extension type, if any. Defaults to NotExtension.NOT_EXTENSION

See also

HybridExtensionType

AssociationProxyExtensionType

attribute sqlalchemy.ext.hybrid.hybrid_method.inplace

Return the inplace mutator for this hybrid_method.

The hybrid_method class already performs “in place” mutation when the hybrid_method.expression() decorator is called, so this attribute returns Self.

Added in version 2.0.4.

See also

Using inplace to create pep-484 compliant hybrid properties

attribute sqlalchemy.ext.hybrid.hybrid_method.is_attribute = True

True if this object is a Python descriptor.

This can refer to one of many types. Usually a QueryableAttribute which handles attributes events on behalf of a MapperProperty. But can also be an extension type such as AssociationProxy or hybrid_property. The InspectionAttr.extension_type will refer to a constant identifying the specific subtype.

See also

Mapper.all_orm_descriptors

class sqlalchemy.ext.hybrid.hybrid_property

inherits from sqlalchemy.orm.base.InspectionAttrInfo, sqlalchemy.orm.base.ORMDescriptor

A decorator which allows definition of a Python descriptor with both instance-level and class-level behavior.

Member Name Description

__init__()

Create a new hybrid_property.

bulk_dml()

Define a setter for bulk dml.

comparator()

Provide a modifying decorator that defines a custom comparator producing method.

deleter()

Provide a modifying decorator that defines a deletion method.

expression()

Provide a modifying decorator that defines a SQL-expression producing method.

extension_type

The extension type, if any. Defaults to NotExtension.NOT_EXTENSION

getter()

Provide a modifying decorator that defines a getter method.

inplace

Return the inplace mutator for this hybrid_property.

is_attribute

True if this object is a Python descriptor.

overrides

Prefix for a method that is overriding an existing attribute.

setter()

Provide a modifying decorator that defines a setter method.

update_expression()

Provide a modifying decorator that defines an UPDATE tuple producing method.
method sqlalchemy.ext.hybrid.hybrid_property.__init__(fget: _HybridGetterType[_T], fset: _HybridSetterType[_T] | None = None, fdel: _HybridDeleterType[_T] | None = None, expr: _HybridExprCallableType[_T] | None = None, custom_comparator: Comparator[_T] | None = None, update_expr: _HybridUpdaterType[_T] | None = None, bulk_dml_setter: _HybridBulkDMLType[_T] | None = None)

Create a new hybrid_property.

Usage is typically via decorator:

from sqlalchemy.ext.hybrid import hybrid_property


class SomeClass:
    @hybrid_property
    def value(self):
        return self._value

    @value.setter
    def value(self, value):
        self._value = value
method sqlalchemy.ext.hybrid.hybrid_property.bulk_dml(meth: _HybridBulkDMLType[_T]) → hybrid_property[_T]

Define a setter for bulk dml.

Added in version 2.1.

method sqlalchemy.ext.hybrid.hybrid_property.comparator(comparator: _HybridComparatorCallableType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines a custom comparator producing method.

The return value of the decorated method should be an instance of Comparator.

Note

The hybrid_property.comparator() decorator replaces the use of the hybrid_property.expression() decorator. They cannot be used together.

When a hybrid is invoked at the class level, the Comparator object given here is wrapped inside of a specialized QueryableAttribute, which is the same kind of object used by the ORM to represent other mapped attributes. The reason for this is so that other class-level attributes such as docstrings and a reference to the hybrid itself may be maintained within the structure that’s returned, without any modifications to the original comparator object passed in.

Note

When referring to a hybrid property from an owning class (e.g. SomeClass.some_hybrid), an instance of QueryableAttribute is returned, representing the expression or comparator object as this hybrid object. However, that object itself has accessors called expression and comparator; so when attempting to override these decorators on a subclass, it may be necessary to qualify it using the hybrid_property.overrides modifier first. See that modifier for details.

method sqlalchemy.ext.hybrid.hybrid_property.deleter(fdel: _HybridDeleterType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines a deletion method.

method sqlalchemy.ext.hybrid.hybrid_property.expression(expr: _HybridExprCallableType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines a SQL-expression producing method.

When a hybrid is invoked at the class level, the SQL expression given here is wrapped inside of a specialized QueryableAttribute, which is the same kind of object used by the ORM to represent other mapped attributes. The reason for this is so that other class-level attributes such as docstrings and a reference to the hybrid itself may be maintained within the structure that’s returned, without any modifications to the original SQL expression passed in.

Note

When referring to a hybrid property from an owning class (e.g. SomeClass.some_hybrid), an instance of QueryableAttribute is returned, representing the expression or comparator object as well as this hybrid object. However, that object itself has accessors called expression and comparator; so when attempting to override these decorators on a subclass, it may be necessary to qualify it using the hybrid_property.overrides modifier first. See that modifier for details.

See also

Defining Expression Behavior Distinct from Attribute Behavior

attribute sqlalchemy.ext.hybrid.hybrid_property.extension_type: InspectionAttrExtensionType = 'HYBRID_PROPERTY'

The extension type, if any. Defaults to NotExtension.NOT_EXTENSION

See also

HybridExtensionType

AssociationProxyExtensionType

method sqlalchemy.ext.hybrid.hybrid_property.getter(fget: _HybridGetterType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines a getter method.

attribute sqlalchemy.ext.hybrid.hybrid_property.inplace

Return the inplace mutator for this hybrid_property.

This is to allow in-place mutation of the hybrid, allowing the first hybrid method of a certain name to be re-used in order to add more methods without having to name those methods the same, e.g.:

class Interval(Base):
    # ...

    @hybrid_property
    def radius(self) -> float:
        return abs(self.length) / 2

    @radius.inplace.setter
    def _radius_setter(self, value: float) -> None:
        self.length = value * 2

    @radius.inplace.expression
    def _radius_expression(cls) -> ColumnElement[float]:
        return type_coerce(func.abs(cls.length) / 2, Float)

Added in version 2.0.4.

See also

Using inplace to create pep-484 compliant hybrid properties

attribute sqlalchemy.ext.hybrid.hybrid_property.is_attribute = True

True if this object is a Python descriptor.

This can refer to one of many types. Usually a QueryableAttribute which handles attributes events on behalf of a MapperProperty. But can also be an extension type such as AssociationProxy or hybrid_property. The InspectionAttr.extension_type will refer to a constant identifying the specific subtype.

See also

Mapper.all_orm_descriptors

attribute sqlalchemy.ext.hybrid.hybrid_property.overrides

Prefix for a method that is overriding an existing attribute.

The hybrid_property.overrides accessor just returns this hybrid object, which when called at the class level from a parent class, will de-reference the “instrumented attribute” normally returned at this level, and allow modifying decorators like hybrid_property.expression() and hybrid_property.comparator() to be used without conflicting with the same-named attributes normally present on the QueryableAttribute:

class SuperClass:
    # ...

    @hybrid_property
    def foobar(self):
        return self._foobar


class SubClass(SuperClass):
    # ...

    @SuperClass.foobar.overrides.expression
    def foobar(cls):
        return func.subfoobar(self._foobar)

See also

Reusing Hybrid Properties across Subclasses

method sqlalchemy.ext.hybrid.hybrid_property.setter(fset: _HybridSetterType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines a setter method.

method sqlalchemy.ext.hybrid.hybrid_property.update_expression(meth: _HybridUpdaterType[_T]) → hybrid_property[_T]

Provide a modifying decorator that defines an UPDATE tuple producing method.

The method accepts a single value, which is the value to be rendered into the SET clause of an UPDATE statement. The method should then process this value into individual column expressions that fit into the ultimate SET clause, and return them as a sequence of 2-tuples. Each tuple contains a column expression as the key and a value to be rendered.

E.g.:

class Person(Base):
    # ...

    first_name = Column(String)
    last_name = Column(String)

    @hybrid_property
    def fullname(self):
        return first_name + " " + last_name

    @fullname.update_expression
    def fullname(cls, value):
        fname, lname = value.split(" ", 1)
        return [(cls.first_name, fname), (cls.last_name, lname)]
class sqlalchemy.ext.hybrid.Comparator

inherits from sqlalchemy.orm.PropComparator

A helper class that allows easy construction of custom PropComparator classes for usage with hybrids.

class sqlalchemy.ext.hybrid.HybridExtensionType

inherits from sqlalchemy.orm.base.InspectionAttrExtensionType

Member Name Description

HYBRID_METHOD

Symbol indicating an InspectionAttr that’s of type hybrid_method.

HYBRID_PROPERTY
attribute sqlalchemy.ext.hybrid.HybridExtensionType.HYBRID_METHOD = 'HYBRID_METHOD'

Symbol indicating an InspectionAttr that’s of type hybrid_method.

Is assigned to the InspectionAttr.extension_type attribute.

See also

Mapper.all_orm_attributes

attribute sqlalchemy.ext.hybrid.HybridExtensionType.HYBRID_PROPERTY = 'HYBRID_PROPERTY'
Symbol indicating an InspectionAttr that’s

of type hybrid_method.

Is assigned to the InspectionAttr.extension_type attribute.

See also

Mapper.all_orm_attributes