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Code Issues 32 Releases Wiki Activity

Refs #34140 -- Corrected rst code-block and various formatting issues in docs.

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This commit is contained in:
Joseph Victor Zammit
2023-01-23 21:29:05 +01:00
committed by Mariusz Felisiak
parent c67ea79aa9
commit ba755ca131
57 changed files with 443 additions and 269 deletions
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4
docs/ref/models/database-functions.txt
View File

@@ -1885,7 +1885,9 @@ more frequently.
.. class:: PercentRank(*expressions, **extra)
Computes the relative rank of the rows in the frame clause. This computation is
equivalent to evaluating::
equivalent to evaluating:
.. code-block:: text
(rank - 1) / (total rows - 1)

96
docs/ref/models/expressions.txt
View File

@@ -21,20 +21,20 @@ constants, variables, and even other expressions.
Some examples
=============
.. code-block:: python
.. code-block:: pycon
from django.db.models import Count, F, Value
from django.db.models.functions import Length, Upper
from django.db.models.lookups import GreaterThan
>>> from django.db.models import Count, F, Value
>>> from django.db.models.functions import Length, Upper
>>> from django.db.models.lookups import GreaterThan
# Find companies that have more employees than chairs.
Company.objects.filter(num_employees__gt=F('num_chairs'))
>>> Company.objects.filter(num_employees__gt=F('num_chairs'))
# Find companies that have at least twice as many employees
# as chairs. Both the querysets below are equivalent.
Company.objects.filter(num_employees__gt=F('num_chairs') * 2)
Company.objects.filter(
num_employees__gt=F('num_chairs') + F('num_chairs'))
>>> Company.objects.filter(num_employees__gt=F('num_chairs') * 2)
>>> Company.objects.filter(
... num_employees__gt=F('num_chairs') + F('num_chairs'))
# How many chairs are needed for each company to seat all employees?
>>> company = Company.objects.filter(
@@ -813,12 +813,12 @@ the same studio in the same genre and release year:
>>> from django.db.models import Avg, F, Window
>>> Movie.objects.annotate(
>>> avg_rating=Window(
>>> expression=Avg('rating'),
>>> partition_by=[F('studio'), F('genre')],
>>> order_by='released__year',
>>> ),
>>> )
... avg_rating=Window(
... expression=Avg('rating'),
... partition_by=[F('studio'), F('genre')],
... order_by='released__year',
... ),
... )
This allows you to check if a movie is rated better or worse than its peers.
@@ -833,20 +833,20 @@ to reduce repetition:
>>> from django.db.models import Avg, F, Max, Min, Window
>>> window = {
>>> 'partition_by': [F('studio'), F('genre')],
>>> 'order_by': 'released__year',
>>> }
... 'partition_by': [F('studio'), F('genre')],
... 'order_by': 'released__year',
... }
>>> Movie.objects.annotate(
>>> avg_rating=Window(
>>> expression=Avg('rating'), **window,
>>> ),
>>> best=Window(
>>> expression=Max('rating'), **window,
>>> ),
>>> worst=Window(
>>> expression=Min('rating'), **window,
>>> ),
>>> )
... avg_rating=Window(
... expression=Avg('rating'), **window,
... ),
... best=Window(
... expression=Max('rating'), **window,
... ),
... worst=Window(
... expression=Min('rating'), **window,
... ),
... )
Filtering against window functions is supported as long as lookups are not
disjunctive (not using ``OR`` or ``XOR`` as a connector) and against a queryset
@@ -860,13 +860,13 @@ from groups to be included:
.. code-block:: pycon
>>> qs = Movie.objects.annotate(
>>> category_rank=Window(
>>> Rank(), partition_by='category', order_by='-rating'
>>> ),
>>> scenes_count=Count('actors'),
>>> ).filter(
>>> Q(category_rank__lte=3) | Q(title__contains='Batman')
>>> )
... category_rank=Window(
... Rank(), partition_by='category', order_by='-rating'
... ),
... scenes_count=Count('actors'),
... ).filter(
... Q(category_rank__lte=3) | Q(title__contains='Batman')
... )
>>> list(qs)
NotImplementedError: Heterogeneous disjunctive predicates against window functions
are not implemented when performing conditional aggregation.
@@ -945,13 +945,13 @@ with the average rating of a movie's two prior and two following peers:
>>> from django.db.models import Avg, F, RowRange, Window
>>> Movie.objects.annotate(
>>> avg_rating=Window(
>>> expression=Avg('rating'),
>>> partition_by=[F('studio'), F('genre')],
>>> order_by='released__year',
>>> frame=RowRange(start=-2, end=2),
>>> ),
>>> )
... avg_rating=Window(
... expression=Avg('rating'),
... partition_by=[F('studio'), F('genre')],
... order_by='released__year',
... frame=RowRange(start=-2, end=2),
... ),
... )
If the database supports it, you can specify the start and end points based on
values of an expression in the partition. If the ``released`` field of the
@@ -963,13 +963,13 @@ released between twelve months before and twelve months after the each movie:
>>> from django.db.models import Avg, F, ValueRange, Window
>>> Movie.objects.annotate(
>>> avg_rating=Window(
>>> expression=Avg('rating'),
>>> partition_by=[F('studio'), F('genre')],
>>> order_by='released__year',
>>> frame=ValueRange(start=-12, end=12),
>>> ),
>>> )
... avg_rating=Window(
... expression=Avg('rating'),
... partition_by=[F('studio'), F('genre')],
... order_by='released__year',
... frame=ValueRange(start=-12, end=12),
... ),
... )
.. currentmodule:: django.db.models

3
docs/ref/models/relations.txt
View File

@@ -24,7 +24,8 @@ Related objects reference
In the above example, the methods below will be available on
the manager ``blog.entry_set``.
* Both sides of a :class:`~django.db.models.ManyToManyField` relation::
* Both sides of a :class:`~django.db.models.ManyToManyField` relation
::
class Topping(models.Model):
# ...