Database Functions

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:

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)[source]

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

Usage example:

>>> 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)[source]

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:

>>> # Get a screen name from least to most public
>>> from django.db.models import Sum
>>> 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
>>> # The aggregate default argument uses Coalesce() under the hood.
>>> aggregated = Author.objects.aggregate(
...     combined_age=Sum("age"),
...     combined_age_default=Sum("age", default=0),
...     combined_age_coalesce=Coalesce(Sum("age"), 0),
... )
>>> print(aggregated["combined_age"])
None
>>> print(aggregated["combined_age_default"])
0
>>> print(aggregated["combined_age_coalesce"])
0

Warning

A Python value passed to Coalesce on MySQL may be converted to an incorrect type unless explicitly cast to the correct database type:

>>> from django.db.models import DateTimeField
>>> from django.db.models.functions import Cast, Coalesce
>>> from django.utils import timezone
>>> now = timezone.now()
>>> Coalesce("updated", Cast(now, DateTimeField()))

Collate

class Collate(expression , collation)[source]

Takes an expression and a collation name to query against.

For example, to filter case-insensitively in SQLite:

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

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

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

Greatest

class Greatest(expressions_ , _*extra)[source]

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:

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.

Warning

The behavior of Greatest when one or more expression may be null varies between databases:

• PostgreSQL: Greatest will return the largest non-null expression, or null if all expressions are null.
• SQLite, Oracle, and MySQL: If any expression is null, Greatest will return null.

The PostgreSQL behavior can be emulated using Coalesce if you know a sensible minimum value to provide as a default.

JSONObject

class JSONObject(**fields)[source]

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

Usage example:

>>> 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)[source]

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.

Warning

The behavior of Least when one or more expression may be null varies between databases:

• PostgreSQL: Least will return the smallest non-null expression, or null if all expressions are null.
• SQLite, Oracle, and MySQL: If any expression is null, Least will return null.

The PostgreSQL behavior can be emulated using Coalesce if you know a sensible maximum value to provide as a default.

NullIf

class NullIf(expression1 , expression2)[source]

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

Caveats on Oracle

Due to an Oracle convention, this function returns the empty string instead of None when the expressions are of type CharField.

Passing Value(None) to expression1 is prohibited on Oracle since Oracle doesn’t accept NULL as the first argument.

Date functions

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

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)[source]

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 zoneinfo, 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

week_day values

The week_day lookup_type is calculated differently from most databases and from Python’s standard functions. This function will return 1 for Sunday, 2 for Monday, through 7 for Saturday.

The equivalent calculation in Python is:

>>> from datetime import datetime
>>> dt = datetime(2015, 6, 15)
>>> (dt.isoweekday() % 7) + 1
2

week values

The week lookup_type is calculated based on ISO-8601, i.e., a week starts on a Monday. The first week of a year is the one that contains the year’s first Thursday, i.e. the first week has the majority (four or more) of its days in the year. The value returned is in the range 1 to 52 or 53.

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:

>>> 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)[source]

• lookup_name = 'year'

class ExtractIsoYear(expression , tzinfo=None , **extra)[source]

Returns the ISO-8601 week-numbering year.

• lookup_name = 'iso_year'

class ExtractMonth(expression , tzinfo=None , **extra)[source]

• lookup_name = 'month'

class ExtractDay(expression , tzinfo=None , **extra)[source]

• lookup_name = 'day'

class ExtractWeekDay(expression , tzinfo=None , **extra)[source]

• lookup_name = 'week_day'

class ExtractIsoWeekDay(expression , tzinfo=None , **extra)[source]

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)[source]

• lookup_name = 'week'

class ExtractQuarter(expression , tzinfo=None , **extra)[source]

• 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:

>>> from datetime import datetime, 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)[source]

• lookup_name = 'hour'

class ExtractMinute(expression , tzinfo=None , **extra)[source]

• lookup_name = 'minute'

class ExtractSecond(expression , tzinfo=None , **extra)[source]

• 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:

>>> from datetime import datetime, 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:

>>> from django.utils import timezone
>>> import zoneinfo
>>> melb = zoneinfo.ZoneInfo("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:

>>> import zoneinfo
>>> melb = zoneinfo.ZoneInfo("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[source]

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

Usage example:

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

PostgreSQL considerations

On PostgreSQL, the SQL CURRENT_TIMESTAMP returns the time that the current transaction started. Therefore for cross-database compatibility, Now() uses STATEMENT_TIMESTAMP instead. If you need the transaction timestamp, use django.contrib.postgres.functions.TransactionNow.

Oracle

On Oracle, the SQL LOCALTIMESTAMP is used to avoid issues with casting CURRENT_TIMESTAMP to DateTimeField.

Changed in Django 5.0:

In older versions, the SQL CURRENT_TIMESTAMP was used on Oracle instead of LOCALTIMESTAMP.

Trunc

class Trunc(expression , kind , output_field=None , tzinfo=None , **extra)[source]

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 zoneinfo, can be passed to truncate a value in a specific timezone.

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:

>>> 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 , **extra)[source]

• kind = 'year'

class TruncMonth(expression , output_field=None , tzinfo=None , **extra)[source]

• kind = 'month'

class TruncWeek(expression , output_field=None , tzinfo=None , **extra)[source]

Truncates to midnight on the Monday of the week.

• kind = 'week'

class TruncQuarter(expression , output_field=None , tzinfo=None , **extra)[source]

• 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:

>>> from datetime import datetime, timezone
>>> from django.db.models import Count
>>> from django.db.models.functions import TruncMonth, TruncYear
>>> 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 zoneinfo
>>> melb = zoneinfo.ZoneInfo("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)[source]

• 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)[source]

• 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 , **extra)[source]

• kind = 'day'

class TruncHour(expression , output_field=None , tzinfo=None , **extra)[source]

• kind = 'hour'

class TruncMinute(expression , output_field=None , tzinfo=None , **extra)[source]

• kind = 'minute'

class TruncSecond(expression , output_field=None , tzinfo=None , **extra)[source]

• 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:

>>> from datetime import date, datetime, timezone
>>> from django.db.models import Count
>>> from django.db.models.functions import (
...     TruncDate,
...     TruncDay,
...     TruncHour,
...     TruncMinute,
...     TruncSecond,
... )
>>> import zoneinfo
>>> start1 = datetime(2014, 6, 15, 14, 30, 50, 321, tzinfo=timezone.utc)
>>> Experiment.objects.create(start_datetime=start1, start_date=start1.date())
>>> melb = zoneinfo.ZoneInfo("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=zoneinfo.ZoneInfo('Australia/Melbourne')),
 'hour': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo('Australia/Melbourne')),
 'minute': 'minute': datetime.datetime(2014, 6, 15, 14, 30, tzinfo=timezone.utc),
 'second': datetime.datetime(2014, 6, 15, 14, 30, 50, tzinfo=timezone.utc)
}

TimeField truncation

class TruncHour(expression , output_field=None , tzinfo=None , **extra)[source]

• kind = 'hour'

class TruncMinute(expression , output_field=None , tzinfo=None , **extra)[source]

• kind = 'minute'

class TruncSecond(expression , output_field=None , tzinfo=None , **extra)[source]

• 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:

>>> from datetime import datetime, timezone
>>> from django.db.models import Count, TimeField
>>> from django.db.models.functions import TruncHour
>>> 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 zoneinfo
>>> melb = zoneinfo.ZoneInfo("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:

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

Abs

class Abs(expression , **extra)[source]

Returns the absolute value of a numeric field or expression.

Usage example:

>>> 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:

>>> 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)[source]

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

Usage example:

>>> 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:

>>> 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)[source]

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

Usage example:

>>> 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:

>>> 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)[source]

Returns the arctangent of a numeric field or expression.

Usage example:

>>> 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:

>>> 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)[source]

Returns the arctangent of expression1 / expression2.

Usage example:

>>> 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)[source]

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

Usage example:

>>> 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:

>>> 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)[source]

Returns the cosine of a numeric field or expression.

Usage example:

>>> 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:

>>> 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)[source]

Returns the cotangent of a numeric field or expression.

Usage example:

>>> 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:

>>> 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)[source]

Converts a numeric field or expression from radians to degrees.

Usage example:

>>> 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:

>>> 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)[source]

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

Usage example:

>>> 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:

>>> 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)[source]

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

Usage example:

>>> 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:

>>> 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)[source]

Returns the natural logarithm a numeric field or expression.

Usage example:

>>> 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:

>>> 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)[source]

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

Usage example:

>>> 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)[source]

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

Usage example:

>>> 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)[source]

Returns the value of the mathematical constant π.

Power

class Power(expression1 , expression2 , **extra)[source]

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

Usage example:

>>> 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)[source]

Converts a numeric field or expression from degrees to radians.

Usage example:

>>> 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:

>>> 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)[source]

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

（本文超出站点单文档体积上限，已按小节截断）