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
>>> Value.objects.create(integer=4)
>>> value = Value.objects.annotate(as_float=Cast('integer', FloatField())).get()
>>> print(value.as_float)
4.0
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, 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
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
.
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.
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 pytz
, can be passed to extract a value in a specific timezone.
Support for DurationField
was added.
Given the datetime 2015-06-15 23:30:01.000321+00:00
, the built-in lookup_name
s return:
- “year”: 2015
- “quarter”: 2
- “month”: 6
- “day”: 15
- “week”: 25
- “week_day”: 2
- “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
- “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:
>>> 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
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
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 DateField
s don’t have a time component, only Extract
subclasses that deal with date-parts can be used with DateField
:
>>> from datetime import datetime
>>> from django.utils import timezone
>>> from django.db.models.functions import (
... ExtractDay, ExtractMonth, ExtractQuarter, ExtractWeek,
... ExtractWeekDay, 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'),
... quarter=ExtractQuarter('start_date'),
... month=ExtractMonth('start_date'),
... week=ExtractWeek('start_date'),
... day=ExtractDay('start_date'),
... weekday=ExtractWeekDay('start_date'),
... ).values('year', 'quarter', 'month', 'week', 'day', 'weekday').get(
... end_date__year=ExtractYear('start_date'),
... )
{'year': 2015, 'quarter': 2, 'month': 6, 'week': 25, 'day': 15, 'weekday': 2}
DateTimeField
extracts
In addition to the following, all extracts for DateField
listed above may also be used on DateTimeField
s .
- 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
>>> from django.utils import timezone
>>> from django.db.models.functions import (
... ExtractDay, ExtractHour, ExtractMinute, ExtractMonth,
... ExtractQuarter, ExtractSecond, ExtractWeek, ExtractWeekDay,
... 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'),
... quarter=ExtractQuarter('start_datetime'),
... month=ExtractMonth('start_datetime'),
... week=ExtractWeek('start_datetime'),
... day=ExtractDay('start_datetime'),
... weekday=ExtractWeekDay('start_datetime'),
... hour=ExtractHour('start_datetime'),
... minute=ExtractMinute('start_datetime'),
... second=ExtractSecond('start_datetime'),
... ).values(
... 'year', 'month', 'week', 'day', 'weekday', 'hour', 'minute', 'second',
... ).get(end_datetime__year=ExtractYear('start_datetime'))
{'year': 2015, 'quarter': 2, 'month': 6, 'week': 25, 'day': 15, 'weekday': 2,
'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:
>>> 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'),
... hour=ExtractHour('start_datetime'),
... ).values('day', 'weekday', 'hour').get(
... end_datetime__year=ExtractYear('start_datetime'),
... )
{'day': 16, 'weekday': 3, 'hour': 9}
Explicitly passing the timezone to the Extract
function behaves in the same way, and takes priority over an active timezone:
>>> import pytz
>>> melb = pytz.timezone('Australia/Melbourne')
>>> Experiment.objects.annotate(
... day=ExtractDay('start_datetime', tzinfo=melb),
... weekday=ExtractWeekDay('start_datetime', tzinfo=melb),
... hour=ExtractHour('start_datetime', tzinfo=melb),
... ).values('day', 'weekday', 'hour').get(
... end_datetime__year=ExtractYear('start_datetime'),
... )
{'day': 16, 'weekday': 3, '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>]>
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 pytz
, 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 kind
s 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
- “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
- “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 obvious 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
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 DateField
s don’t have a time component, only Trunc
subclasses that deal with date-parts can be used with DateField
:
>>> 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, **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, **extra)[source]
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
>>> 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, **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 TimeField
s don’t have a date component, only Trunc
subclasses that deal with time-parts can be used with TimeField
:
>>> 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
Text functions
Concat
- class
Concat
(*expressions, **extra)[source]
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:
>>> # 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)
Length
- class
Length
(expression, **extra)[source]
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:
>>> # 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:
>>> from django.db.models import CharField
>>> from django.db.models.functions import Length
>>> CharField.register_lookup(Length, 'length')
>>> # Get authors whose name is longer than 7 characters
>>> authors = Author.objects.filter(name__length__gt=7)
Lower
- class
Lower
(expression, **extra)[source]
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:
>>> 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
StrIndex
- class
StrIndex
(string, substring, **extra)[source]
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:
>>> 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)[source]
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:
>>> # 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
Upper
- class
Upper
(expression, **extra)[source]
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:
>>> 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)[source]
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.
FirstValue
- class
FirstValue
(expression, **extra)[source]
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)[source]
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)[source]
Comparable to FirstValue
, it calculates the last value in a given frame clause.
NthValue
- class
NthValue
(expression, nth=1, **extra)[source]
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)[source]
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)[source]
Computes the percentile rank of the rows in the frame clause. This computation is equivalent to evaluating:
(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)[source]
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)[source]
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.