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Django 3.2
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Database Functions

The classes documented below provide a way for users to use functions provided by the underlying database as annotations, aggregations, or filters in Django. Functions are also expressions, so they can be used and combined with other expressions like aggregate functions.

We’ll be using the following model in examples of each function:

Code
class Author(models.Model):
    name = models.CharField(max_length=50)
    age = models.PositiveIntegerField(null=True, blank=True)
    alias = models.CharField(max_length=50, null=True, blank=True)
    goes_by = models.CharField(max_length=50, null=True, blank=True)

We don’t usually recommend allowing null=True for CharField since this allows the field to have two “empty values”, but it’s important for the Coalesce example below.

Comparison and conversion functions

Cast

class Cast(expression, output_field)

Forces the result type of expression to be the one from output_field.

Usage example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cast
>>> Author.objects.create(age=25, name='Margaret Smith')
>>> author = Author.objects.annotate(
...    age_as_float=Cast('age', output_field=FloatField()),
... ).get()
>>> print(author.age_as_float)
25.0

Coalesce

class Coalesce(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the first non-null value (note that an empty string is not considered a null value). Each argument must be of a similar type, so mixing text and numbers will result in a database error.

Usage examples:

Code
>>> # Get a screen name from least to most public
>>> from django.db.models import Sum, Value as V
>>> from django.db.models.functions import Coalesce
>>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
>>> author = Author.objects.annotate(
...    screen_name=Coalesce('alias', 'goes_by', 'name')).get()
>>> print(author.screen_name)
Maggie

>>> # Prevent an aggregate Sum() from returning None
>>> aggregated = Author.objects.aggregate(
...    combined_age=Coalesce(Sum('age'), V(0)),
...    combined_age_default=Sum('age'))
>>> print(aggregated['combined_age'])
0
>>> print(aggregated['combined_age_default'])
None

Collate

class Collate(expression, collation)

Takes an expression and a collation name to query against.

For example, to filter case-insensitively in SQLite:

Code
>>> Author.objects.filter(name=Collate(Value('john'), 'nocase'))
<QuerySet [<Author: John>, <Author: john>]>

It can also be used when ordering, for example with PostgreSQL:

Code
>>> Author.objects.order_by(Collate('name', 'et-x-icu'))
<QuerySet [<Author: Ursula>, <Author: Veronika>, <Author: Ülle>]>

Greatest

class Greatest(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the greatest value. Each argument must be of a similar type, so mixing text and numbers will result in a database error.

Usage example:

Code
class Blog(models.Model):
    body = models.TextField()
    modified = models.DateTimeField(auto_now=True)

class Comment(models.Model):
    body = models.TextField()
    modified = models.DateTimeField(auto_now=True)
    blog = models.ForeignKey(Blog, on_delete=models.CASCADE)

>>> from django.db.models.functions import Greatest
>>> blog = Blog.objects.create(body='Greatest is the best.')
>>> comment = Comment.objects.create(body='No, Least is better.', blog=blog)
>>> comments = Comment.objects.annotate(last_updated=Greatest('modified', 'blog__modified'))
>>> annotated_comment = comments.get()

annotated_comment.last_updated will be the most recent of blog.modified and comment.modified.

JSONObject

class JSONObject(**fields)

Takes a list of key-value pairs and returns a JSON object containing those pairs.

Usage example:

Code
>>> from django.db.models import F
>>> from django.db.models.functions import JSONObject, Lower
>>> Author.objects.create(name='Margaret Smith', alias='msmith', age=25)
>>> author = Author.objects.annotate(json_object=JSONObject(
...     name=Lower('name'),
...     alias='alias',
...     age=F('age') * 2,
... )).get()
>>> author.json_object
{'name': 'margaret smith', 'alias': 'msmith', 'age': 50}

Least

class Least(*expressions, **extra)

Accepts a list of at least two field names or expressions and returns the least value. Each argument must be of a similar type, so mixing text and numbers will result in a database error.

NullIf

class NullIf(expression1, expression2)

Accepts two expressions and returns None if they are equal, otherwise returns expression1.

Date functions

We’ll be using the following model in examples of each function:

Code
class Experiment(models.Model):
    start_datetime = models.DateTimeField()
    start_date = models.DateField(null=True, blank=True)
    start_time = models.TimeField(null=True, blank=True)
    end_datetime = models.DateTimeField(null=True, blank=True)
    end_date = models.DateField(null=True, blank=True)
    end_time = models.TimeField(null=True, blank=True)

Extract

class Extract(expression, lookup_name=None, tzinfo=None, **extra)

Extracts a component of a date as a number.

Takes an expression representing a DateField, DateTimeField, TimeField, or DurationField and a lookup_name, and returns the part of the date referenced by lookup_name as an IntegerField. Django usually uses the databases’ extract function, so you may use any lookup_name that your database supports. A tzinfo subclass, usually provided by pytz, can be passed to extract a value in a specific timezone.

Given the datetime 2015-06-15 23:30:01.000321+00:00, the built-in lookup_names return:

  • “year”: 2015

  • “iso_year”: 2015

  • “quarter”: 2

  • “month”: 6

  • “day”: 15

  • “week”: 25

  • “week_day”: 2

  • “iso_week_day”: 1

  • “hour”: 23

  • “minute”: 30

  • “second”: 1

If a different timezone like Australia/Melbourne is active in Django, then the datetime is converted to the timezone before the value is extracted. The timezone offset for Melbourne in the example date above is +10:00. The values returned when this timezone is active will be the same as above except for:

  • “day”: 16

  • “week_day”: 3

  • “iso_week_day”: 2

  • “hour”: 9

Each lookup_name above has a corresponding Extract subclass (listed below) that should typically be used instead of the more verbose equivalent, e.g. use ExtractYear(...) rather than Extract(..., lookup_name='year').

Usage example:

Code
>>> from datetime import datetime
>>> from django.db.models.functions import Extract
>>> start = datetime(2015, 6, 15)
>>> end = datetime(2015, 7, 2)
>>> Experiment.objects.create(
...    start_datetime=start, start_date=start.date(),
...    end_datetime=end, end_date=end.date())
>>> # Add the experiment start year as a field in the QuerySet.
>>> experiment = Experiment.objects.annotate(
...    start_year=Extract('start_datetime', 'year')).get()
>>> experiment.start_year
2015
>>> # How many experiments completed in the same year in which they started?
>>> Experiment.objects.filter(
...    start_datetime__year=Extract('end_datetime', 'year')).count()
1

DateField extracts

class ExtractYear(expression, tzinfo=None, **extra)
lookup_name = 'year'
class ExtractIsoYear(expression, tzinfo=None, **extra)

Returns the ISO-8601 week-numbering year.

lookup_name = 'iso_year'
class ExtractMonth(expression, tzinfo=None, **extra)
lookup_name = 'month'
class ExtractDay(expression, tzinfo=None, **extra)
lookup_name = 'day'
class ExtractWeekDay(expression, tzinfo=None, **extra)
lookup_name = 'week_day'
class ExtractIsoWeekDay(expression, tzinfo=None, **extra)

Returns the ISO-8601 week day with day 1 being Monday and day 7 being Sunday.

lookup_name = 'iso_week_day'
class ExtractWeek(expression, tzinfo=None, **extra)
lookup_name = 'week'
class ExtractQuarter(expression, tzinfo=None, **extra)
lookup_name = 'quarter'

These are logically equivalent to Extract('date_field', lookup_name). Each class is also a Transform registered on DateField and DateTimeField as __(lookup_name), e.g. __year.

Since DateFields don’t have a time component, only Extract subclasses that deal with date-parts can be used with DateField:

Code
>>> from datetime import datetime
>>> from django.utils import timezone
>>> from django.db.models.functions import (
...     ExtractDay, ExtractMonth, ExtractQuarter, ExtractWeek,
...     ExtractIsoWeekDay, ExtractWeekDay, ExtractIsoYear, ExtractYear,
... )
>>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
>>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
>>> Experiment.objects.create(
...    start_datetime=start_2015, start_date=start_2015.date(),
...    end_datetime=end_2015, end_date=end_2015.date())
>>> Experiment.objects.annotate(
...     year=ExtractYear('start_date'),
...     isoyear=ExtractIsoYear('start_date'),
...     quarter=ExtractQuarter('start_date'),
...     month=ExtractMonth('start_date'),
...     week=ExtractWeek('start_date'),
...     day=ExtractDay('start_date'),
...     weekday=ExtractWeekDay('start_date'),
...     isoweekday=ExtractIsoWeekDay('start_date'),
... ).values(
...     'year', 'isoyear', 'quarter', 'month', 'week', 'day', 'weekday',
...     'isoweekday',
... ).get(end_date__year=ExtractYear('start_date'))
{'year': 2015, 'isoyear': 2015, 'quarter': 2, 'month': 6, 'week': 25,
 'day': 15, 'weekday': 2, 'isoweekday': 1}

DateTimeField extracts

In addition to the following, all extracts for DateField listed above may also be used on DateTimeFields .

class ExtractHour(expression, tzinfo=None, **extra)
lookup_name = 'hour'
class ExtractMinute(expression, tzinfo=None, **extra)
lookup_name = 'minute'
class ExtractSecond(expression, tzinfo=None, **extra)
lookup_name = 'second'

These are logically equivalent to Extract('datetime_field', lookup_name). Each class is also a Transform registered on DateTimeField as __(lookup_name), e.g. __minute.

DateTimeField examples:

Code
>>> from datetime import datetime
>>> from django.utils import timezone
>>> from django.db.models.functions import (
...     ExtractDay, ExtractHour, ExtractMinute, ExtractMonth,
...     ExtractQuarter, ExtractSecond, ExtractWeek, ExtractIsoWeekDay,
...     ExtractWeekDay, ExtractIsoYear, ExtractYear,
... )
>>> start_2015 = datetime(2015, 6, 15, 23, 30, 1, tzinfo=timezone.utc)
>>> end_2015 = datetime(2015, 6, 16, 13, 11, 27, tzinfo=timezone.utc)
>>> Experiment.objects.create(
...    start_datetime=start_2015, start_date=start_2015.date(),
...    end_datetime=end_2015, end_date=end_2015.date())
>>> Experiment.objects.annotate(
...     year=ExtractYear('start_datetime'),
...     isoyear=ExtractIsoYear('start_datetime'),
...     quarter=ExtractQuarter('start_datetime'),
...     month=ExtractMonth('start_datetime'),
...     week=ExtractWeek('start_datetime'),
...     day=ExtractDay('start_datetime'),
...     weekday=ExtractWeekDay('start_datetime'),
...     isoweekday=ExtractIsoWeekDay('start_datetime'),
...     hour=ExtractHour('start_datetime'),
...     minute=ExtractMinute('start_datetime'),
...     second=ExtractSecond('start_datetime'),
... ).values(
...     'year', 'isoyear', 'month', 'week', 'day',
...     'weekday', 'isoweekday', 'hour', 'minute', 'second',
... ).get(end_datetime__year=ExtractYear('start_datetime'))
{'year': 2015, 'isoyear': 2015, 'quarter': 2, 'month': 6, 'week': 25,
 'day': 15, 'weekday': 2, 'isoweekday': 1, 'hour': 23, 'minute': 30,
 'second': 1}

When USE_TZ is True then datetimes are stored in the database in UTC. If a different timezone is active in Django, the datetime is converted to that timezone before the value is extracted. The example below converts to the Melbourne timezone (UTC +10:00), which changes the day, weekday, and hour values that are returned:

Code
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')  # UTC+10:00
>>> with timezone.override(melb):
...    Experiment.objects.annotate(
...        day=ExtractDay('start_datetime'),
...        weekday=ExtractWeekDay('start_datetime'),
...        isoweekday=ExtractIsoWeekDay('start_datetime'),
...        hour=ExtractHour('start_datetime'),
...    ).values('day', 'weekday', 'isoweekday', 'hour').get(
...        end_datetime__year=ExtractYear('start_datetime'),
...    )
{'day': 16, 'weekday': 3, 'isoweekday': 2, 'hour': 9}

Explicitly passing the timezone to the Extract function behaves in the same way, and takes priority over an active timezone:

Code
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> Experiment.objects.annotate(
...     day=ExtractDay('start_datetime', tzinfo=melb),
...     weekday=ExtractWeekDay('start_datetime', tzinfo=melb),
...     isoweekday=ExtractIsoWeekDay('start_datetime', tzinfo=melb),
...     hour=ExtractHour('start_datetime', tzinfo=melb),
... ).values('day', 'weekday', 'isoweekday', 'hour').get(
...     end_datetime__year=ExtractYear('start_datetime'),
... )
{'day': 16, 'weekday': 3, 'isoweekday': 2, 'hour': 9}

Now

class Now

Returns the database server’s current date and time when the query is executed, typically using the SQL CURRENT_TIMESTAMP.

Usage example:

Code
>>> from django.db.models.functions import Now
>>> Article.objects.filter(published__lte=Now())
<QuerySet [<Article: How to Django>]>

Trunc

class Trunc(expression, kind, output_field=None, tzinfo=None, is_dst=None, **extra)

Truncates a date up to a significant component.

When you only care if something happened in a particular year, hour, or day, but not the exact second, then Trunc (and its subclasses) can be useful to filter or aggregate your data. For example, you can use Trunc to calculate the number of sales per day.

Trunc takes a single expression, representing a DateField, TimeField, or DateTimeField, a kind representing a date or time part, and an output_field that’s either DateTimeField(), TimeField(), or DateField(). It returns a datetime, date, or time depending on output_field, with fields up to kind set to their minimum value. If output_field is omitted, it will default to the output_field of expression. A tzinfo subclass, usually provided by pytz, can be passed to truncate a value in a specific timezone.

The is_dst parameter indicates whether or not pytz should interpret nonexistent and ambiguous datetimes in daylight saving time. By default (when is_dst=None), pytz raises an exception for such datetimes.

Given the datetime 2015-06-15 14:30:50.000321+00:00, the built-in kinds return:

  • “year”: 2015-01-01 00:00:00+00:00

  • “quarter”: 2015-04-01 00:00:00+00:00

  • “month”: 2015-06-01 00:00:00+00:00

  • “week”: 2015-06-15 00:00:00+00:00

  • “day”: 2015-06-15 00:00:00+00:00

  • “hour”: 2015-06-15 14:00:00+00:00

  • “minute”: 2015-06-15 14:30:00+00:00

  • “second”: 2015-06-15 14:30:50+00:00

If a different timezone like Australia/Melbourne is active in Django, then the datetime is converted to the new timezone before the value is truncated. The timezone offset for Melbourne in the example date above is +10:00. The values returned when this timezone is active will be:

  • “year”: 2015-01-01 00:00:00+11:00

  • “quarter”: 2015-04-01 00:00:00+10:00

  • “month”: 2015-06-01 00:00:00+10:00

  • “week”: 2015-06-16 00:00:00+10:00

  • “day”: 2015-06-16 00:00:00+10:00

  • “hour”: 2015-06-16 00:00:00+10:00

  • “minute”: 2015-06-16 00:30:00+10:00

  • “second”: 2015-06-16 00:30:50+10:00

The year has an offset of +11:00 because the result transitioned into daylight saving time.

Each kind above has a corresponding Trunc subclass (listed below) that should typically be used instead of the more verbose equivalent, e.g. use TruncYear(...) rather than Trunc(..., kind='year').

The subclasses are all defined as transforms, but they aren’t registered with any fields, because the lookup names are already reserved by the Extract subclasses.

Usage example:

Code
>>> from datetime import datetime
>>> from django.db.models import Count, DateTimeField
>>> from django.db.models.functions import Trunc
>>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 30, 50, 321))
>>> Experiment.objects.create(start_datetime=datetime(2015, 6, 15, 14, 40, 2, 123))
>>> Experiment.objects.create(start_datetime=datetime(2015, 12, 25, 10, 5, 27, 999))
>>> experiments_per_day = Experiment.objects.annotate(
...    start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
... ).values('start_day').annotate(experiments=Count('id'))
>>> for exp in experiments_per_day:
...     print(exp['start_day'], exp['experiments'])
...
2015-06-15 00:00:00 2
2015-12-25 00:00:00 1
>>> experiments = Experiment.objects.annotate(
...    start_day=Trunc('start_datetime', 'day', output_field=DateTimeField())
... ).filter(start_day=datetime(2015, 6, 15))
>>> for exp in experiments:
...     print(exp.start_datetime)
...
2015-06-15 14:30:50.000321
2015-06-15 14:40:02.000123

DateField truncation

class TruncYear(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'year'
class TruncMonth(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'month'
class TruncWeek(expression, output_field=None, tzinfo=None, is_dst=None, **extra)

Truncates to midnight on the Monday of the week.

kind = 'week'
class TruncQuarter(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'quarter'

These are logically equivalent to Trunc('date_field', kind). They truncate all parts of the date up to kind which allows grouping or filtering dates with less precision. expression can have an output_field of either DateField or DateTimeField.

Since DateFields don’t have a time component, only Trunc subclasses that deal with date-parts can be used with DateField:

Code
>>> from datetime import datetime
>>> from django.db.models import Count
>>> from django.db.models.functions import TruncMonth, TruncYear
>>> from django.utils import timezone
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> start2 = datetime(2015, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
>>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
>>> Experiment.objects.create(start_datetime=start2, start_date=start2.date())
>>> Experiment.objects.create(start_datetime=start3, start_date=start3.date())
>>> experiments_per_year = Experiment.objects.annotate(
...    year=TruncYear('start_date')).values('year').annotate(
...    experiments=Count('id'))
>>> for exp in experiments_per_year:
...     print(exp['year'], exp['experiments'])
...
2014-01-01 1
2015-01-01 2

>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> experiments_per_month = Experiment.objects.annotate(
...    month=TruncMonth('start_datetime', tzinfo=melb)).values('month').annotate(
...    experiments=Count('id'))
>>> for exp in experiments_per_month:
...     print(exp['month'], exp['experiments'])
...
2015-06-01 00:00:00+10:00 1
2016-01-01 00:00:00+11:00 1
2014-06-01 00:00:00+10:00 1

DateTimeField truncation

class TruncDate(expression, tzinfo=None, **extra)
lookup_name = 'date'
output_field = DateField()

TruncDate casts expression to a date rather than using the built-in SQL truncate function. It’s also registered as a transform on DateTimeField as __date.

class TruncTime(expression, tzinfo=None, **extra)
lookup_name = 'time'
output_field = TimeField()

TruncTime casts expression to a time rather than using the built-in SQL truncate function. It’s also registered as a transform on DateTimeField as __time.

class TruncDay(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'day'
class TruncHour(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'hour'
class TruncMinute(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'minute'
class TruncSecond(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'second'

These are logically equivalent to Trunc('datetime_field', kind). They truncate all parts of the date up to kind and allow grouping or filtering datetimes with less precision. expression must have an output_field of DateTimeField.

Usage example:

Code
>>> from datetime import date, datetime
>>> from django.db.models import Count
>>> from django.db.models.functions import (
...     TruncDate, TruncDay, TruncHour, TruncMinute, TruncSecond,
... )
>>> from django.utils import timezone
>>> import pytz
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
>>> melb = pytz.timezone('Australia/Melbourne')
>>> Experiment.objects.annotate(
...     date=TruncDate('start_datetime'),
...     day=TruncDay('start_datetime', tzinfo=melb),
...     hour=TruncHour('start_datetime', tzinfo=melb),
...     minute=TruncMinute('start_datetime'),
...     second=TruncSecond('start_datetime'),
... ).values('date', 'day', 'hour', 'minute', 'second').get()
{'date': datetime.date(2014, 6, 15),
 'day': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
 'hour': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=<DstTzInfo 'Australia/Melbourne' AEST+10:00:00 STD>),
 'minute': 'minute': datetime.datetime(2014, 6, 15, 14, 30, tzinfo=<UTC>),
 'second': datetime.datetime(2014, 6, 15, 14, 30, 50, tzinfo=<UTC>)
}

TimeField truncation

class TruncHour(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'hour'
class TruncMinute(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'minute'
class TruncSecond(expression, output_field=None, tzinfo=None, is_dst=None, **extra)
kind = 'second'

These are logically equivalent to Trunc('time_field', kind). They truncate all parts of the time up to kind which allows grouping or filtering times with less precision. expression can have an output_field of either TimeField or DateTimeField.

Since TimeFields don’t have a date component, only Trunc subclasses that deal with time-parts can be used with TimeField:

Code
>>> from datetime import datetime
>>> from django.db.models import Count, TimeField
>>> from django.db.models.functions import TruncHour
>>> from django.utils import timezone
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> start2 = datetime(2014, 6, 15, 14, 40, 2, 123, tzinfo=timezone.utc)
>>> start3 = datetime(2015, 12, 31, 17, 5, 27, 999, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_time=start1.time())
>>> Experiment.objects.create(start_datetime=start2, start_time=start2.time())
>>> Experiment.objects.create(start_datetime=start3, start_time=start3.time())
>>> experiments_per_hour = Experiment.objects.annotate(
...    hour=TruncHour('start_datetime', output_field=TimeField()),
... ).values('hour').annotate(experiments=Count('id'))
>>> for exp in experiments_per_hour:
...     print(exp['hour'], exp['experiments'])
...
14:00:00 2
17:00:00 1

>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> experiments_per_hour = Experiment.objects.annotate(
...    hour=TruncHour('start_datetime', tzinfo=melb),
... ).values('hour').annotate(experiments=Count('id'))
>>> for exp in experiments_per_hour:
...     print(exp['hour'], exp['experiments'])
...
2014-06-16 00:00:00+10:00 2
2016-01-01 04:00:00+11:00 1

Math Functions

We’ll be using the following model in math function examples:

Code
class Vector(models.Model):
    x = models.FloatField()
    y = models.FloatField()

Abs

class Abs(expression, **extra)

Returns the absolute value of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Abs
>>> Vector.objects.create(x=-0.5, y=1.1)
>>> vector = Vector.objects.annotate(x_abs=Abs('x'), y_abs=Abs('y')).get()
>>> vector.x_abs, vector.y_abs
(0.5, 1.1)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Abs
>>> FloatField.register_lookup(Abs)
>>> # Get vectors inside the unit cube
>>> vectors = Vector.objects.filter(x__abs__lt=1, y__abs__lt=1)

ACos

class ACos(expression, **extra)

Returns the arccosine of a numeric field or expression. The expression value must be within the range -1 to 1.

Usage example:

Code
>>> from django.db.models.functions import ACos
>>> Vector.objects.create(x=0.5, y=-0.9)
>>> vector = Vector.objects.annotate(x_acos=ACos('x'), y_acos=ACos('y')).get()
>>> vector.x_acos, vector.y_acos
(1.0471975511965979, 2.6905658417935308)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ACos
>>> FloatField.register_lookup(ACos)
>>> # Get vectors whose arccosine is less than 1
>>> vectors = Vector.objects.filter(x__acos__lt=1, y__acos__lt=1)

ASin

class ASin(expression, **extra)

Returns the arcsine of a numeric field or expression. The expression value must be in the range -1 to 1.

Usage example:

Code
>>> from django.db.models.functions import ASin
>>> Vector.objects.create(x=0, y=1)
>>> vector = Vector.objects.annotate(x_asin=ASin('x'), y_asin=ASin('y')).get()
>>> vector.x_asin, vector.y_asin
(0.0, 1.5707963267948966)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ASin
>>> FloatField.register_lookup(ASin)
>>> # Get vectors whose arcsine is less than 1
>>> vectors = Vector.objects.filter(x__asin__lt=1, y__asin__lt=1)

ATan

class ATan(expression, **extra)

Returns the arctangent of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import ATan
>>> Vector.objects.create(x=3.12, y=6.987)
>>> vector = Vector.objects.annotate(x_atan=ATan('x'), y_atan=ATan('y')).get()
>>> vector.x_atan, vector.y_atan
(1.2606282660069106, 1.428638798133829)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import ATan
>>> FloatField.register_lookup(ATan)
>>> # Get vectors whose arctangent is less than 2
>>> vectors = Vector.objects.filter(x__atan__lt=2, y__atan__lt=2)

ATan2

class ATan2(expression1, expression2, **extra)

Returns the arctangent of expression1 / expression2.

Usage example:

Code
>>> from django.db.models.functions import ATan2
>>> Vector.objects.create(x=2.5, y=1.9)
>>> vector = Vector.objects.annotate(atan2=ATan2('x', 'y')).get()
>>> vector.atan2
0.9209258773829491

Ceil

class Ceil(expression, **extra)

Returns the smallest integer greater than or equal to a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Ceil
>>> Vector.objects.create(x=3.12, y=7.0)
>>> vector = Vector.objects.annotate(x_ceil=Ceil('x'), y_ceil=Ceil('y')).get()
>>> vector.x_ceil, vector.y_ceil
(4.0, 7.0)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Ceil
>>> FloatField.register_lookup(Ceil)
>>> # Get vectors whose ceil is less than 10
>>> vectors = Vector.objects.filter(x__ceil__lt=10, y__ceil__lt=10)

Cos

class Cos(expression, **extra)

Returns the cosine of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Cos
>>> Vector.objects.create(x=-8.0, y=3.1415926)
>>> vector = Vector.objects.annotate(x_cos=Cos('x'), y_cos=Cos('y')).get()
>>> vector.x_cos, vector.y_cos
(-0.14550003380861354, -0.9999999999999986)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cos
>>> FloatField.register_lookup(Cos)
>>> # Get vectors whose cosine is less than 0.5
>>> vectors = Vector.objects.filter(x__cos__lt=0.5, y__cos__lt=0.5)

Cot

class Cot(expression, **extra)

Returns the cotangent of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Cot
>>> Vector.objects.create(x=12.0, y=1.0)
>>> vector = Vector.objects.annotate(x_cot=Cot('x'), y_cot=Cot('y')).get()
>>> vector.x_cot, vector.y_cot
(-1.5726734063976826, 0.642092615934331)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Cot
>>> FloatField.register_lookup(Cot)
>>> # Get vectors whose cotangent is less than 1
>>> vectors = Vector.objects.filter(x__cot__lt=1, y__cot__lt=1)

Degrees

class Degrees(expression, **extra)

Converts a numeric field or expression from radians to degrees.

Usage example:

Code
>>> from django.db.models.functions import Degrees
>>> Vector.objects.create(x=-1.57, y=3.14)
>>> vector = Vector.objects.annotate(x_d=Degrees('x'), y_d=Degrees('y')).get()
>>> vector.x_d, vector.y_d
(-89.95437383553924, 179.9087476710785)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Degrees
>>> FloatField.register_lookup(Degrees)
>>> # Get vectors whose degrees are less than 360
>>> vectors = Vector.objects.filter(x__degrees__lt=360, y__degrees__lt=360)

Exp

class Exp(expression, **extra)

Returns the value of e (the natural logarithm base) raised to the power of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Exp
>>> Vector.objects.create(x=5.4, y=-2.0)
>>> vector = Vector.objects.annotate(x_exp=Exp('x'), y_exp=Exp('y')).get()
>>> vector.x_exp, vector.y_exp
(221.40641620418717, 0.1353352832366127)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Exp
>>> FloatField.register_lookup(Exp)
>>> # Get vectors whose exp() is greater than 10
>>> vectors = Vector.objects.filter(x__exp__gt=10, y__exp__gt=10)

Floor

class Floor(expression, **extra)

Returns the largest integer value not greater than a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Floor
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_floor=Floor('x'), y_floor=Floor('y')).get()
>>> vector.x_floor, vector.y_floor
(5.0, -3.0)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Floor
>>> FloatField.register_lookup(Floor)
>>> # Get vectors whose floor() is greater than 10
>>> vectors = Vector.objects.filter(x__floor__gt=10, y__floor__gt=10)

Ln

class Ln(expression, **extra)

Returns the natural logarithm a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Ln
>>> Vector.objects.create(x=5.4, y=233.0)
>>> vector = Vector.objects.annotate(x_ln=Ln('x'), y_ln=Ln('y')).get()
>>> vector.x_ln, vector.y_ln
(1.6863989535702288, 5.4510384535657)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Ln
>>> FloatField.register_lookup(Ln)
>>> # Get vectors whose value greater than e
>>> vectors = Vector.objects.filter(x__ln__gt=1, y__ln__gt=1)

Log

class Log(expression1, expression2, **extra)

Accepts two numeric fields or expressions and returns the logarithm of the first to base of the second.

Usage example:

Code
>>> from django.db.models.functions import Log
>>> Vector.objects.create(x=2.0, y=4.0)
>>> vector = Vector.objects.annotate(log=Log('x', 'y')).get()
>>> vector.log
2.0

Mod

class Mod(expression1, expression2, **extra)

Accepts two numeric fields or expressions and returns the remainder of the first divided by the second (modulo operation).

Usage example:

Code
>>> from django.db.models.functions import Mod
>>> Vector.objects.create(x=5.4, y=2.3)
>>> vector = Vector.objects.annotate(mod=Mod('x', 'y')).get()
>>> vector.mod
0.8

Pi

class Pi(**extra)

Returns the value of the mathematical constant π.

Power

class Power(expression1, expression2, **extra)

Accepts two numeric fields or expressions and returns the value of the first raised to the power of the second.

Usage example:

Code
>>> from django.db.models.functions import Power
>>> Vector.objects.create(x=2, y=-2)
>>> vector = Vector.objects.annotate(power=Power('x', 'y')).get()
>>> vector.power
0.25

Radians

class Radians(expression, **extra)

Converts a numeric field or expression from degrees to radians.

Usage example:

Code
>>> from django.db.models.functions import Radians
>>> Vector.objects.create(x=-90, y=180)
>>> vector = Vector.objects.annotate(x_r=Radians('x'), y_r=Radians('y')).get()
>>> vector.x_r, vector.y_r
(-1.5707963267948966, 3.141592653589793)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Radians
>>> FloatField.register_lookup(Radians)
>>> # Get vectors whose radians are less than 1
>>> vectors = Vector.objects.filter(x__radians__lt=1, y__radians__lt=1)

Random

class Random(**extra)

Returns a random value in the range 0.0 ≤ x < 1.0.

Round

class Round(expression, **extra)

Rounds a numeric field or expression to the nearest integer. Whether half values are rounded up or down depends on the database.

Usage example:

Code
>>> from django.db.models.functions import Round
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_r=Round('x'), y_r=Round('y')).get()
>>> vector.x_r, vector.y_r
(5.0, -2.0)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Round
>>> FloatField.register_lookup(Round)
>>> # Get vectors whose round() is less than 20
>>> vectors = Vector.objects.filter(x__round__lt=20, y__round__lt=20)

Sign

class Sign(expression, **extra)

Returns the sign (-1, 0, 1) of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Sign
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_sign=Sign('x'), y_sign=Sign('y')).get()
>>> vector.x_sign, vector.y_sign
(1, -1)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Sign
>>> FloatField.register_lookup(Sign)
>>> # Get vectors whose signs of components are less than 0.
>>> vectors = Vector.objects.filter(x__sign__lt=0, y__sign__lt=0)

Sin

class Sin(expression, **extra)

Returns the sine of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Sin
>>> Vector.objects.create(x=5.4, y=-2.3)
>>> vector = Vector.objects.annotate(x_sin=Sin('x'), y_sin=Sin('y')).get()
>>> vector.x_sin, vector.y_sin
(-0.7727644875559871, -0.7457052121767203)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Sin
>>> FloatField.register_lookup(Sin)
>>> # Get vectors whose sin() is less than 0
>>> vectors = Vector.objects.filter(x__sin__lt=0, y__sin__lt=0)

Sqrt

class Sqrt(expression, **extra)

Returns the square root of a nonnegative numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Sqrt
>>> Vector.objects.create(x=4.0, y=12.0)
>>> vector = Vector.objects.annotate(x_sqrt=Sqrt('x'), y_sqrt=Sqrt('y')).get()
>>> vector.x_sqrt, vector.y_sqrt
(2.0, 3.46410)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Sqrt
>>> FloatField.register_lookup(Sqrt)
>>> # Get vectors whose sqrt() is less than 5
>>> vectors = Vector.objects.filter(x__sqrt__lt=5, y__sqrt__lt=5)

Tan

class Tan(expression, **extra)

Returns the tangent of a numeric field or expression.

Usage example:

Code
>>> from django.db.models.functions import Tan
>>> Vector.objects.create(x=0, y=12)
>>> vector = Vector.objects.annotate(x_tan=Tan('x'), y_tan=Tan('y')).get()
>>> vector.x_tan, vector.y_tan
(0.0, -0.6358599286615808)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import FloatField
>>> from django.db.models.functions import Tan
>>> FloatField.register_lookup(Tan)
>>> # Get vectors whose tangent is less than 0
>>> vectors = Vector.objects.filter(x__tan__lt=0, y__tan__lt=0)

Text functions

Chr

class Chr(expression, **extra)

Accepts a numeric field or expression and returns the text representation of the expression as a single character. It works the same as Python’s chr() function.

Like Length, it can be registered as a transform on IntegerField. The default lookup name is chr.

Usage example:

Code
>>> from django.db.models.functions import Chr
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.filter(name__startswith=Chr(ord('M'))).get()
>>> print(author.name)
Margaret Smith

Concat

class Concat(*expressions, **extra)

Accepts a list of at least two text fields or expressions and returns the concatenated text. Each argument must be of a text or char type. If you want to concatenate a TextField() with a CharField(), then be sure to tell Django that the output_field should be a TextField(). Specifying an output_field is also required when concatenating a Value as in the example below.

This function will never have a null result. On backends where a null argument results in the entire expression being null, Django will ensure that each null part is converted to an empty string first.

Usage example:

Code
>>> # Get the display name as "name (goes_by)"
>>> from django.db.models import CharField, Value as V
>>> from django.db.models.functions import Concat
>>> Author.objects.create(name='Margaret Smith', goes_by='Maggie')
>>> author = Author.objects.annotate(
...     screen_name=Concat(
...         'name', V(' ('), 'goes_by', V(')'),
...         output_field=CharField()
...     )
... ).get()
>>> print(author.screen_name)
Margaret Smith (Maggie)

Left

class Left(expression, length, **extra)

Returns the first length characters of the given text field or expression.

Usage example:

Code
>>> from django.db.models.functions import Left
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(first_initial=Left('name', 1)).get()
>>> print(author.first_initial)
M

Length

class Length(expression, **extra)

Accepts a single text field or expression and returns the number of characters the value has. If the expression is null, then the length will also be null.

Usage example:

Code
>>> # Get the length of the name and goes_by fields
>>> from django.db.models.functions import Length
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(
...    name_length=Length('name'),
...    goes_by_length=Length('goes_by')).get()
>>> print(author.name_length, author.goes_by_length)
(14, None)

It can also be registered as a transform. For example:

Code
>>> from django.db.models import CharField
>>> from django.db.models.functions import Length
>>> CharField.register_lookup(Length)
>>> # Get authors whose name is longer than 7 characters
>>> authors = Author.objects.filter(name__length__gt=7)

Lower

class Lower(expression, **extra)

Accepts a single text field or expression and returns the lowercase representation.

It can also be registered as a transform as described in Length.

Usage example:

Code
>>> from django.db.models.functions import Lower
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_lower=Lower('name')).get()
>>> print(author.name_lower)
margaret smith

LPad

class LPad(expression, length, fill_text=Value(' '), **extra)

Returns the value of the given text field or expression padded on the left side with fill_text so that the resulting value is length characters long. The default fill_text is a space.

Usage example:

Code
>>> from django.db.models import Value
>>> from django.db.models.functions import LPad
>>> Author.objects.create(name='John', alias='j')
>>> Author.objects.update(name=LPad('name', 8, Value('abc')))
1
>>> print(Author.objects.get(alias='j').name)
abcaJohn

LTrim

class LTrim(expression, **extra)

Similar to Trim, but removes only leading spaces.

MD5

class MD5(expression, **extra)

Accepts a single text field or expression and returns the MD5 hash of the string.

It can also be registered as a transform as described in Length.

Usage example:

Code
>>> from django.db.models.functions import MD5
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_md5=MD5('name')).get()
>>> print(author.name_md5)
749fb689816b2db85f5b169c2055b247

Ord

class Ord(expression, **extra)

Accepts a single text field or expression and returns the Unicode code point value for the first character of that expression. It works similar to Python’s ord() function, but an exception isn’t raised if the expression is more than one character long.

It can also be registered as a transform as described in Length. The default lookup name is ord.

Usage example:

Code
>>> from django.db.models.functions import Ord
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_code_point=Ord('name')).get()
>>> print(author.name_code_point)
77

Repeat

class Repeat(expression, number, **extra)

Returns the value of the given text field or expression repeated number times.

Usage example:

Code
>>> from django.db.models.functions import Repeat
>>> Author.objects.create(name='John', alias='j')
>>> Author.objects.update(name=Repeat('name', 3))
1
>>> print(Author.objects.get(alias='j').name)
JohnJohnJohn

Replace

class Replace(expression, text, replacement=Value(''), **extra)

Replaces all occurrences of text with replacement in expression. The default replacement text is the empty string. The arguments to the function are case-sensitive.

Usage example:

Code
>>> from django.db.models import Value
>>> from django.db.models.functions import Replace
>>> Author.objects.create(name='Margaret Johnson')
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.update(name=Replace('name', Value('Margaret'), Value('Margareth')))
2
>>> Author.objects.values('name')
<QuerySet [{'name': 'Margareth Johnson'}, {'name': 'Margareth Smith'}]>

Reverse

class Reverse(expression, **extra)

Accepts a single text field or expression and returns the characters of that expression in reverse order.

It can also be registered as a transform as described in Length. The default lookup name is reverse.

Usage example:

Code
>>> from django.db.models.functions import Reverse
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(backward=Reverse('name')).get()
>>> print(author.backward)
htimS teragraM

RPad

class RPad(expression, length, fill_text=Value(' '), **extra)

Similar to LPad, but pads on the right side.

RTrim

class RTrim(expression, **extra)

Similar to Trim, but removes only trailing spaces.

SHA1, SHA224, SHA256, SHA384, and SHA512

class SHA1(expression, **extra)
class SHA224(expression, **extra)
class SHA256(expression, **extra)
class SHA384(expression, **extra)
class SHA512(expression, **extra)

Accepts a single text field or expression and returns the particular hash of the string.

They can also be registered as transforms as described in Length.

Usage example:

Code
>>> from django.db.models.functions import SHA1
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_sha1=SHA1('name')).get()
>>> print(author.name_sha1)
b87efd8a6c991c390be5a68e8a7945a7851c7e5c

StrIndex

class StrIndex(string, substring, **extra)

Returns a positive integer corresponding to the 1-indexed position of the first occurrence of substring inside string, or 0 if substring is not found.

Usage example:

Code
>>> from django.db.models import Value as V
>>> from django.db.models.functions import StrIndex
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.create(name='Smith, Margaret')
>>> Author.objects.create(name='Margaret Jackson')
>>> Author.objects.filter(name='Margaret Jackson').annotate(
...     smith_index=StrIndex('name', V('Smith'))
... ).get().smith_index
0
>>> authors = Author.objects.annotate(
...    smith_index=StrIndex('name', V('Smith'))
... ).filter(smith_index__gt=0)
<QuerySet [<Author: Margaret Smith>, <Author: Smith, Margaret>]>

Substr

class Substr(expression, pos, length=None, **extra)

Returns a substring of length length from the field or expression starting at position pos. The position is 1-indexed, so the position must be greater than 0. If length is None, then the rest of the string will be returned.

Usage example:

Code
>>> # Set the alias to the first 5 characters of the name as lowercase
>>> from django.db.models.functions import Lower, Substr
>>> Author.objects.create(name='Margaret Smith')
>>> Author.objects.update(alias=Lower(Substr('name', 1, 5)))
1
>>> print(Author.objects.get(name='Margaret Smith').alias)
marga

Trim

class Trim(expression, **extra)

Returns the value of the given text field or expression with leading and trailing spaces removed.

Usage example:

Code
>>> from django.db.models.functions import Trim
>>> Author.objects.create(name='  John  ', alias='j')
>>> Author.objects.update(name=Trim('name'))
1
>>> print(Author.objects.get(alias='j').name)
John

Upper

class Upper(expression, **extra)

Accepts a single text field or expression and returns the uppercase representation.

It can also be registered as a transform as described in Length.

Usage example:

Code
>>> from django.db.models.functions import Upper
>>> Author.objects.create(name='Margaret Smith')
>>> author = Author.objects.annotate(name_upper=Upper('name')).get()
>>> print(author.name_upper)
MARGARET SMITH

Window functions

There are a number of functions to use in a Window expression for computing the rank of elements or the Ntile of some rows.

CumeDist

class CumeDist(*expressions, **extra)

Calculates the cumulative distribution of a value within a window or partition. The cumulative distribution is defined as the number of rows preceding or peered with the current row divided by the total number of rows in the frame.

DenseRank

class DenseRank(*expressions, **extra)

Equivalent to Rank but does not have gaps.

FirstValue

class FirstValue(expression, **extra)

Returns the value evaluated at the row that’s the first row of the window frame, or None if no such value exists.

Lag

class Lag(expression, offset=1, default=None, **extra)

Calculates the value offset by offset, and if no row exists there, returns default.

default must have the same type as the expression, however, this is only validated by the database and not in Python.

LastValue

class LastValue(expression, **extra)

Comparable to FirstValue, it calculates the last value in a given frame clause.

Lead

class Lead(expression, offset=1, default=None, **extra)

Calculates the leading value in a given frame. Both offset and default are evaluated with respect to the current row.

default must have the same type as the expression, however, this is only validated by the database and not in Python.

NthValue

class NthValue(expression, nth=1, **extra)

Computes the row relative to the offset nth (must be a positive value) within the window. Returns None if no row exists.

Some databases may handle a nonexistent nth-value differently. For example, Oracle returns an empty string rather than None for character-based expressions. Django doesn’t do any conversions in these cases.

Ntile

class Ntile(num_buckets=1, **extra)

Calculates a partition for each of the rows in the frame clause, distributing numbers as evenly as possible between 1 and num_buckets. If the rows don’t divide evenly into a number of buckets, one or more buckets will be represented more frequently.

PercentRank

class PercentRank(*expressions, **extra)

Computes the percentile rank of the rows in the frame clause. This computation is equivalent to evaluating:

Code
(rank - 1) / (total rows - 1)

The following table explains the calculation for the percentile rank of a row:

Row #

Value

Rank

Calculation

Percent Rank

1

15

1

(1-1)/(7-1)

0.0000

2

20

2

(2-1)/(7-1)

0.1666

3

20

2

(2-1)/(7-1)

0.1666

4

20

2

(2-1)/(7-1)

0.1666

5

30

5

(5-1)/(7-1)

0.6666

6

30

5

(5-1)/(7-1)

0.6666

7

40

7

(7-1)/(7-1)

1.0000

Rank

class Rank(*expressions, **extra)

Comparable to RowNumber, this function ranks rows in the window. The computed rank contains gaps. Use DenseRank to compute rank without gaps.

RowNumber

class RowNumber(*expressions, **extra)

Computes the row number according to the ordering of either the frame clause or the ordering of the whole query if there is no partitioning of the window frame.

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