Range data types

SQLAlchemy-Utils provides wide variety of range data types. All range data types return Interval objects of intervals package. In order to use range data types you need to install intervals with:

pip install intervals

Intervals package provides good chunk of additional interval operators that for example psycopg2 range objects do not support.

Some good reading for practical interval implementations:

http://wiki.postgresql.org/images/f/f0/Range-types.pdf

Range type initialization

from sqlalchemy_utils import IntRangeType


class Event(Base):
    __tablename__ = 'user'
    id = sa.Column(sa.Integer, autoincrement=True)
    name = sa.Column(sa.Unicode(255))
    estimated_number_of_persons = sa.Column(IntRangeType)

You can also set a step parameter for range type. The values that are not multipliers of given step will be rounded up to nearest step multiplier.

from sqlalchemy_utils import IntRangeType


class Event(Base):
    __tablename__ = 'user'
    id = sa.Column(sa.Integer, autoincrement=True)
    name = sa.Column(sa.Unicode(255))
    estimated_number_of_persons = sa.Column(IntRangeType(step=1000))


event = Event(estimated_number_of_persons=[100, 1200])
event.estimated_number_of_persons.lower  # 0
event.estimated_number_of_persons.upper  # 1000

Range type operators

SQLAlchemy-Utils supports many range type operators. These operators follow the intervals package interval coercion rules.

So for example when we make a query such as:

session.query(Car).filter(Car.price_range == 300)

It is essentially the same as:

session.query(Car).filter(Car.price_range == DecimalInterval([300, 300]))

Comparison operators

All range types support all comparison operators (>, >=, ==, !=, <=, <).

Car.price_range < [12, 300]

Car.price_range == [12, 300]

Car.price_range < 300

Car.price_range > (300, 500)

# Whether or not range is strictly left of another range
Car.price_range << [300, 500]

# Whether or not range is strictly right of another range
Car.price_range >> [300, 500]

Membership operators

Car.price_range.contains([300, 500])

Car.price_range.contained_by([300, 500])

Car.price_range.in_([[300, 500], [800, 900]])

~ Car.price_range.in_([[300, 400], [700, 800]])

Length

SQLAlchemy-Utils provides length property for all range types. The implementation of this property varies on different range types.

In the following example we find all cars whose price range’s length is more than 500.

session.query(Car).filter(
    Car.price_range.length > 500
)

DateRangeType

class sqlalchemy_utils.types.range.DateRangeType(*args, **kwargs)[source]

DateRangeType provides way for saving ranges of dates into database. On PostgreSQL this type maps to native DATERANGE type while on other drivers this maps to simple string column.

Example:

from sqlalchemy_utils import DateRangeType


class Reservation(Base):
    __tablename__ = 'user'
    id = sa.Column(sa.Integer, autoincrement=True)
    room_id = sa.Column(sa.Integer))
    during = sa.Column(DateRangeType)

DateTimeRangeType

class sqlalchemy_utils.types.range.DateTimeRangeType(*args, **kwargs)[source]

IntRangeType

class sqlalchemy_utils.types.range.IntRangeType(*args, **kwargs)[source]

IntRangeType provides way for saving ranges of integers into database. On PostgreSQL this type maps to native INT4RANGE type while on other drivers this maps to simple string column.

Example:

from sqlalchemy_utils import IntRangeType


class Event(Base):
    __tablename__ = 'user'
    id = sa.Column(sa.Integer, autoincrement=True)
    name = sa.Column(sa.Unicode(255))
    estimated_number_of_persons = sa.Column(IntRangeType)


party = Event(name=u'party')

# we estimate the party to contain minium of 10 persons and at max
# 100 persons
party.estimated_number_of_persons = [10, 100]

print party.estimated_number_of_persons
# '10-100'

IntRangeType returns the values as IntInterval objects. These objects support many arithmetic operators:

meeting = Event(name=u'meeting')

meeting.estimated_number_of_persons = [20, 40]

total = (
    meeting.estimated_number_of_persons +
    party.estimated_number_of_persons
)
print total
# '30-140'

NumericRangeType

class sqlalchemy_utils.types.range.NumericRangeType(*args, **kwargs)[source]

NumericRangeType provides way for saving ranges of decimals into database. On PostgreSQL this type maps to native NUMRANGE type while on other drivers this maps to simple string column.

Example:

from sqlalchemy_utils import NumericRangeType


class Car(Base):
    __tablename__ = 'car'
    id = sa.Column(sa.Integer, autoincrement=True)
    name = sa.Column(sa.Unicode(255)))
    price_range = sa.Column(NumericRangeType)

RangeComparator

class sqlalchemy_utils.types.range.RangeComparator(expr)[source]