================== Database Functions ================== .. module:: django.db.models.functions :synopsis: 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 :doc:`expressions `, so they can be used and combined with other expressions like :ref:`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-functions: 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:: >>> 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) 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 .. 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())) ``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:: 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. ``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. .. 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) Accepts two expressions and returns ``None`` if they are equal, otherwise returns ``expression1``. .. admonition:: Caveats on Oracle Due to an :ref:`Oracle convention`, this function returns the empty string instead of ``None`` when the expressions are of type :class:`~django.db.models.CharField`. Passing ``Value(None)`` to ``expression1`` is prohibited on Oracle since Oracle doesn't accept ``NULL`` as the first argument. .. _date-functions: 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) 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_name``\s return: * "year": 2015 * "iso_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 .. admonition:: ``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 .. admonition:: ``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) .. attribute:: lookup_name = 'year' .. class:: ExtractIsoYear(expression, tzinfo=None, **extra) Returns the ISO-8601 week-numbering year. .. attribute:: lookup_name = 'iso_year' .. class:: ExtractMonth(expression, tzinfo=None, **extra) .. attribute:: lookup_name = 'month' .. class:: ExtractDay(expression, tzinfo=None, **extra) .. attribute:: lookup_name = 'day' .. class:: ExtractWeekDay(expression, tzinfo=None, **extra) .. attribute:: lookup_name = 'week_day' .. class:: ExtractWeek(expression, tzinfo=None, **extra) .. attribute:: lookup_name = 'week' .. class:: ExtractQuarter(expression, tzinfo=None, **extra) .. attribute:: 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, 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'), ... ).values('year', 'isoyear', 'quarter', 'month', 'week', 'day', 'weekday').get( ... end_date__year=ExtractYear('start_date'), ... ) {'year': 2015, 'isoyear': 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) .. attribute:: lookup_name = 'hour' .. class:: ExtractMinute(expression, tzinfo=None, **extra) .. attribute:: lookup_name = 'minute' .. class:: ExtractSecond(expression, tzinfo=None, **extra) .. attribute:: 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, ... 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'), ... hour=ExtractHour('start_datetime'), ... minute=ExtractMinute('start_datetime'), ... second=ExtractSecond('start_datetime'), ... ).values( ... 'year', 'isoyear', 'month', 'week', 'day', ... 'weekday', 'hour', 'minute', 'second', ... ).get(end_datetime__year=ExtractYear('start_datetime')) {'year': 2015, 'isoyear': 2015, 'quarter': 2, 'month': 6, 'week': 25, 'day': 15, 'weekday': 2, 'hour': 23, 'minute': 30, 'second': 1} When :setting:`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() 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()) ]> .. admonition:: 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 :class:`django.contrib.postgres.functions.TransactionNow`. ``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. .. versionadded:: 3.0 The ``is_dst`` parameter was added. 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 * "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 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, is_dst=None, **extra) .. attribute:: kind = 'year' .. class:: TruncMonth(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: kind = 'month' .. class:: TruncWeek(expression, output_field=None, tzinfo=None, is_dst=None, **extra) Truncates to midnight on the Monday of the week. .. attribute:: kind = 'week' .. class:: TruncQuarter(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: 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) .. attribute:: lookup_name = 'date' .. attribute:: 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) .. attribute:: lookup_name = 'time' .. attribute:: 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) .. attribute:: kind = 'day' .. class:: TruncHour(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: kind = 'hour' .. class:: TruncMinute(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: kind = 'minute' .. class:: TruncSecond(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: 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=), 'hour': datetime.datetime(2014, 6, 16, 0, 0, tzinfo=), 'minute': 'minute': datetime.datetime(2014, 6, 15, 14, 30, tzinfo=), 'second': datetime.datetime(2014, 6, 15, 14, 30, 50, tzinfo=) } ``TimeField`` truncation ~~~~~~~~~~~~~~~~~~~~~~~~ .. class:: TruncHour(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: kind = 'hour' .. class:: TruncMinute(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: kind = 'minute' .. class:: TruncSecond(expression, output_field=None, tzinfo=None, is_dst=None, **extra) .. attribute:: 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 .. _math-functions: 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) Accepts two numeric fields or expressions and returns the logarithm of the first to base of the second. 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) 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) 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:: >>> 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:: >>> 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) ``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:: >>> 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:: >>> 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) .. versionadded:: 3.0 Returns the sign (-1, 0, 1) of a numeric field or expression. Usage example:: >>> 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:: >>> 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:: >>> 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:: >>> 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:: >>> 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:: >>> 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:: >>> 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:: >>> 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: 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 :func:`chr` function. Like :class:`Length`, it can be registered as a transform on ``IntegerField``. The default lookup name is ``chr``. Usage example:: >>> 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:: >>> # 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:: >>> 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:: >>> # 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) >>> # 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 :class:`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 ``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:: >>> 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 :class:`~django.db.models.functions.Trim`, but removes only leading spaces. ``MD5`` ------- .. class:: MD5(expression, **extra) .. versionadded:: 3.0 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 :class:`Length`. Usage example:: >>> 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 :func:`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 :class:`Length`. The default lookup name is ``ord``. Usage example:: >>> 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:: >>> 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:: >>> 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') ``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 :class:`Length`. The default lookup name is ``reverse``. Usage example:: >>> 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 ``Right`` --------- .. class:: Right(expression, length, **extra) Returns the last ``length`` characters of the given text field or expression. Usage example:: >>> from django.db.models.functions import Right >>> Author.objects.create(name='Margaret Smith') >>> author = Author.objects.annotate(last_letter=Right('name', 1)).get() >>> print(author.last_letter) h ``RPad`` -------- .. class:: RPad(expression, length, fill_text=Value(' '), **extra) Similar to :class:`~django.db.models.functions.LPad`, but pads on the right side. ``RTrim`` --------- .. class:: RTrim(expression, **extra) Similar to :class:`~django.db.models.functions.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) .. versionadded:: 3.0 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 :class:`Length`. Usage example:: >>> 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 .. admonition:: PostgreSQL The `pgcrypto extension `_ must be installed. You can use the :class:`~django.contrib.postgres.operations.CryptoExtension` migration operation to install it. .. admonition:: Oracle Oracle doesn't support the ``SHA224`` function. ``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:: >>> 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) , ]> .. warning:: In MySQL, a database table's :ref:`collation` determines whether string comparisons (such as the ``expression`` and ``substring`` of this function) are case-sensitive. Comparisons are case-insensitive by default. ``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:: >>> # 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:: >>> 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 :class:`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: Window functions ================ There are a number of functions to use in a :class:`~django.db.models.expressions.Window` expression for computing the rank of elements or the :class:`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 :class:`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. .. admonition:: MariaDB and ``default`` MariaDB `doesn't support `_ the ``default`` parameter. ``LastValue`` ------------- .. class:: LastValue(expression, **extra) Comparable to :class:`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 :ref:`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. .. admonition:: MariaDB and ``default`` MariaDB `doesn't support `_ the ``default`` parameter. ``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:: (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 :class:`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 :ref:`window frame `.