How could I specify the order of columns in SELECT query in Django ORM?
I am trying to union elements from two tables, but apparently elements in union are matched by the order of columns in SELECT, instead of the names of the columns (even if name of the columns are the same).
Consider following Models:
class Person(models.Model):
first_name = models.CharField(max_length=256)
last_name = models.CharField(max_length=256)
age = models.IntegerField()
class Car(models.Model):
number = models.IntegerField()
brand = models.CharField(max_length=256)
name = models.CharField(max_length=256)
and following piece of code:
Person.objects.create(first_name="John", last_name="Smith", age=25)
Car.objects.create(number=42, name="Cybertruck", brand="Tesla")
q1 = Person.objects.all().annotate(name=F('first_name'), group=F('last_name'), number=F('age')).values(
'name', 'group', 'number')
q2 = Car.objects.all().annotate(group=F('brand')).values('name', 'group', 'number')
data = q1.union(q2)
print(data.query)
assert list(data) == [
{'name': 'John', 'group': 'Smith', 'number': 25},
{'name': 'Cybertruck', 'group': 'Tesla', 'number': 42},
])
As you can see I put correct order in .values().
What one could expect is that columns in union would be matched in the order passed to values (or by column names), but this is what happens:
SELECT "testunion_person"."first_name" AS "name", "testunion_person"."last_name" AS "group", "testunion_person"."age" AS "number" FROM "testunion_person" UNION SELECT "testunion_car"."name", "testunion_car"."number", "testunion_car"."brand" AS "group" FROM "testunion_car"
In the queries "testunion_car"."number" is before "testunion_car"."brand", which makes the Car in UNION have a values:
{'name': 'Cybertruck', 'group': '42', 'number': 'Tesla'}
EDIT: I am using 2.2 (LTS) version of Django
Instead of specifying the alias under annotate(), you can also specify them straight under values():
q1 = Person.objects.all().values(
name=F('first_name'), group=F('last_name'), xnumber=F('age'))
q2 = Car.objects.all().values(
'name', group=F('brand'), xnumber=F('number'))
I noticed that even then, it wasn't ordering the fields properly. I renamed the number field to xnumber to avoid conflicts with the model field of the same name and everything is grouped properly.
You can set the order of the fields using .values_list.
qs1 = Person.objects.values_list('name', 'group', 'number')
qs2 = Car.objects.values_list('brand', 'name', 'number')
qs1.union(qs2)
Check the docs for more detailed explanation.
Not a Django bug. Although query columns not sorted as values, the queryset display the right order:
In [13]: print(data)
<QuerySet [{'name': 'Cybertruck', 'group': 42, 'number': 'Tesla'}, {'name': 'John', 'group': 'Smith', 'number': 25}]>
It is because the data will be sorted after fetch from database. Source code snippet of QuerySet:
class QuerySet:
def __iter__(self):
"""
The queryset iterator protocol uses three nested iterators in the
default case:
1. sql.compiler.execute_sql()
- Returns 100 rows at time (constants.GET_ITERATOR_CHUNK_SIZE)
using cursor.fetchmany(). This part is responsible for
doing some column masking, and returning the rows in chunks.
2. sql.compiler.results_iter()
- Returns one row at time. At this point the rows are still just
tuples. In some cases the return values are converted to
Python values at this location.
3. self.iterator()
- Responsible for turning the rows into model objects.
"""
self._fetch_all()
return iter(self._result_cache)
Related
I have a table that gets new rows for eg. I'd add more than 100 features like phone_number, username to the processed_donors to this table very soon.IS it possible to simplify this json_object(****) so It's not an evergrowing list? Some way to use pandas+python, select * etc?
--- read_cur.execute("""
select a.donor_id,
json_object('city', a.city,
'name', a.name,
'zip', a.zip,
'state', a.state,
'address', a.address),
b.donor_id,
json_object('city', b.city,
'name', b.name,
'zip', b.zip,
'state', b.state,
'address', b.address)
from (select DISTINCT l.donor_id as east, r.donor_id as west
from blocking_map as l
INNER JOIN blocking_map as r
using (block_key)
where l.donor_id < r.donor_id) ids
INNER JOIN processed_donors a on ids.east=a.donor_id
INNER JOIN processed_donors b on ids.west=b.donor_id
--- """)
I think you could do this in two steps.
First, you need to get all the columns of the processed_donors table. Then you can use this result to build your query string.
read_cur.execute('DESCRIBE processed_donors')
describe_result = read_cur.fetchall()
column_names = [row[0] for row in describe_result]
# column_names should be ['city', 'name', 'zip', 'state']
pairs = [f"'{col}', a.{col}" for col in column_names]
jo_a = f'json_object({", ".join(pairs)})'
# jo_a is json_object('city', a.city, 'name', a.name, 'zip', a.zip, 'state', a.state)
Note that I don't have a mysql DB running here, so I can't check if that's the correct way how to build the column_names, but I hope you get the idea. You can use the same process to build the json_object for b and then build a query string.
Please keep in mind that normally, creating a SQL query manually like this is a bad idea do to SQL injection vulnerabilities, but I presume there's no user input involved here and you control the names of the columns, so it should be fine.
I'm using Django and Python 3.7. I have the following model ...
class ArticleStat(models.Model):
objects = ArticleStatManager()
article = models.ForeignKey(Article, on_delete=models.CASCADE, related_name='articlestats')
elapsed_time_in_seconds = models.IntegerField(default=0, null=False)
score = models.FloatField(default=0, null=False)
I want to write a MAX/GROUP BY query subject to certain conditions. Specifically I want each row to contain
MAX(ArticleStat.elapsed_time_in_seconds)
ArticleStat.Article.id
ArticleStat.Article.title
ArticleStat.score
in which the columns "ArticleStat.Article.id," "ArticleStat.Article.title," and "ArticleStat.score" are unique per result set row. So I tried this ...
def get_current_articles(self, article):
qset = ArticleStat.objects.values('article__id', 'article__title', 'score').filter(
article__article=article).values('elapsed_time_in_seconds').annotate(\
max_date=Max('elapsed_time_in_seconds'))
print(qset.query)
return qset
However, the resulting SQL does not include the values I want to use in my GROUP BY clause (notice that neither "article" nor "score" is in the GROUP BY) ...
SELECT "myproject_articlestat"."elapsed_time_in_seconds",
MAX("myproject_articlestat"."elapsed_time_in_seconds") AS "max_date"
FROM "myproject_articlestat"
INNER JOIN "myproject_article" ON ("myproject_articlestat"."article_id" = "myproject_article"."id")
WHERE ("myproject_article"."article_id" = 2) GROUP BY "myproject_articlestat"."elapsed_time_in_seconds"
How do I modify my Django query to generate SQL consistent with what I want?
I don't think the answer by #Oleg will work but it's close..
A Subquery expression can be used to select a single value from another queryset. To accomplish this you sort by the value you wish to target then select the first value.
sq = (
ArticleStat.objects
.filter(article=OuterRef('pk'))
.order_by('-elapsed_time_in_seconds')
)
articles = (
Article.objects
.annotate(
max_date=Subquery(sq.values('elapsed_time_in_seconds')[:1]),
score=Subquery(sq.values('score')[:1]),
)
# .values('id', 'path', 'title', 'score', 'max_date')
)
You should not use the 'elapsed_time_in_seconds' in your .values(..) clause, and add the GROUP BY property in the .order_by(..) clause:
qset = ArticleStat.objects.filter(
article__article=article
).values(
'article__path', 'article__title', 'score'
).annotate(
max_date=Max('elapsed_time_in_seconds')
).order_by('article__path', 'article__title', 'score')
This will thus make a QuerySet of dictionaries such that each dictionary contains four elements: 'article__path', 'article__title', 'score', and 'max_date'.
As far as I see, there is no one-step way of doing this in Django.
One way of doing it is with 2 queries and to get use of .annotate() to
add the max id of the related object revision for each revision, then
get all those objectrevisions
Example:
objects = Object.objects.all().annotate(revision_id=Max
('objectrevision__id'))
objectrevisions = ObjectRevision.objects.filter(id__in=
[o.revision_id for o in objects])
This is untested and also its a bit slow, so may be you can also try to write custom SQL as mentioned by Wolfram Kriesing in the blog here
If I understand correctly from all the comments:
Result is to get Articles (id, path, title) filtered by the article argument of get_current_articles method with additional data - maximum elapsed_time_in_seconds from all the ArticleStats of each filtered article and also score of its ArticleStat with maximum elapsed_time.
If so, when the base query can be on Article model: Article.objects.filter(article=article).
Which we can annotate with the Max() of corresponding ArticleStats. This can be done directly on main query .annotate(max_date=Max(articlestats__elapsed_time_in_seconds)) or with Subquery on ArticleStat also filtered the same way as base query on article (we want subquery to run on the same set of article objects as the main query), i.e.
max_sq = ArticleStat.objects.filter(
article__article=OuterRef('article')
).annotate(max_date=Max('elapsed_time_in_seconds'))
Now, to add score column to the result. Max() is aggregate function and it has no row info. In order to get score for the maximum elapsed_time we can make another subquery and filter by max elapsed_time from previous column.
Note: This filter can return multiple ArticleStats objects for the same maximum elapsed_time and article but we will use only the first one. It is for your data structure to make sure that filter returns only one row or provide additional filtering or ordering such that first result will be the one required.
score_sq = ArticleStat.objects.filter(
article__article=OuterRef('article'),
elapsed_time_in_seconds=OuterRef('max_date')
)
And use our subqueries in the main query
qset = Article.objects.filter(
article=article
).annotate(
max_date=Max('articlestats__elapsed_time_in_seconds'),
""" or
max_date=Subquery(
max_sq.values('max_date')[:1]
),
"""
score=Subquery(
score_sq.values('score')[:1]
)
).values(
'id', 'path', 'title', 'score', 'max_date'
)
And somewhat tricky option without using Max() function
but emulating it with ORDER BY and fetching the first row.
artstat_sq = ArticleStat.objects.filter(
article__article=OuterRef('article')
).order_by().order_by('-elapsed_time_in_seconds', '-score')
# empty order_by() to clear any base ordering
qset = Article.objects.filter(
article=article
).annotate(
max_date=Subquery(
artstat_sq.values('elapsed_time_in_seconds')[:1]
),
score=Subquery(
artstat_sq.values('score')[:1]
)
).values(
'id', 'path', 'title', 'score', 'max_date'
)
While constructing a complexe QuerySet with several annotations, I ran into an issue that I could reproduce with the following simple setup.
Here are the models:
class Player(models.Model):
name = models.CharField(max_length=200)
class Unit(models.Model):
player = models.ForeignKey(Player, on_delete=models.CASCADE,
related_name='unit_set')
rarity = models.IntegerField()
class Weapon(models.Model):
unit = models.ForeignKey(Unit, on_delete=models.CASCADE,
related_name='weapon_set')
With my test database, I obtain the following (correct) results:
Player.objects.annotate(weapon_count=Count('unit_set__weapon_set'))
[{'id': 1, 'name': 'James', 'weapon_count': 23},
{'id': 2, 'name': 'Max', 'weapon_count': 41},
{'id': 3, 'name': 'Bob', 'weapon_count': 26}]
Player.objects.annotate(rarity_sum=Sum('unit_set__rarity'))
[{'id': 1, 'name': 'James', 'rarity_sum': 42},
{'id': 2, 'name': 'Max', 'rarity_sum': 89},
{'id': 3, 'name': 'Bob', 'rarity_sum': 67}]
If I now combine both annotations in the same QuerySet, I obtain a different (inaccurate) results:
Player.objects.annotate(
weapon_count=Count('unit_set__weapon_set', distinct=True),
rarity_sum=Sum('unit_set__rarity'))
[{'id': 1, 'name': 'James', 'weapon_count': 23, 'rarity_sum': 99},
{'id': 2, 'name': 'Max', 'weapon_count': 41, 'rarity_sum': 183},
{'id': 3, 'name': 'Bob', 'weapon_count': 26, 'rarity_sum': 113}]
Notice how rarity_sum have now different values than before. Removing distinct=True does not affect the result. I also tried to use the DistinctSum function from this answer, in which case all rarity_sum are set to 18 (also inaccurate).
Why is this? How can I combine both annotations in the same QuerySet?
Edit: here is the sqlite query generated by the combined QuerySet:
SELECT "sandbox_player"."id",
"sandbox_player"."name",
COUNT(DISTINCT "sandbox_weapon"."id") AS "weapon_count",
SUM("sandbox_unit"."rarity") AS "rarity_sum"
FROM "sandbox_player"
LEFT OUTER JOIN "sandbox_unit" ON ("sandbox_player"."id" = "sandbox_unit"."player_id")
LEFT OUTER JOIN "sandbox_weapon" ON ("sandbox_unit"."id" = "sandbox_weapon"."unit_id")
GROUP BY "sandbox_player"."id", "sandbox_player"."name"
The data used for the results above is available here.
This isn't the problem with Django ORM, this is just the way relational databases work. When you're constructing simple querysets like
Player.objects.annotate(weapon_count=Count('unit_set__weapon_set'))
or
Player.objects.annotate(rarity_sum=Sum('unit_set__rarity'))
ORM does exactly what you expect it to do - join Player with Weapon
SELECT "sandbox_player"."id", "sandbox_player"."name", COUNT("sandbox_weapon"."id") AS "weapon_count"
FROM "sandbox_player"
LEFT OUTER JOIN "sandbox_unit"
ON ("sandbox_player"."id" = "sandbox_unit"."player_id")
LEFT OUTER JOIN "sandbox_weapon"
ON ("sandbox_unit"."id" = "sandbox_weapon"."unit_id")
GROUP BY "sandbox_player"."id", "sandbox_player"."name"
or Player with Unit
SELECT "sandbox_player"."id", "sandbox_player"."name", SUM("sandbox_unit"."rarity") AS "rarity_sum"
FROM "sandbox_player"
LEFT OUTER JOIN "sandbox_unit" ON ("sandbox_player"."id" = "sandbox_unit"."player_id")
GROUP BY "sandbox_player"."id", "sandbox_player"."name"
and perform either COUNT or SUM aggregation on them.
Note that although the first query has two joins between three tables, the intermediate table Unit is neither in columns referenced in SELECT, nor in the GROUP BY clause. The only role that Unit plays here is to join Player with Weapon.
Now if you look at your third queryset, things get more complicated. Again, as in the first query the joins are between three tables, but now Unit is referenced in SELECT as there is SUM aggregation for Unit.rarity:
SELECT "sandbox_player"."id",
"sandbox_player"."name",
COUNT(DISTINCT "sandbox_weapon"."id") AS "weapon_count",
SUM("sandbox_unit"."rarity") AS "rarity_sum"
FROM "sandbox_player"
LEFT OUTER JOIN "sandbox_unit" ON ("sandbox_player"."id" = "sandbox_unit"."player_id")
LEFT OUTER JOIN "sandbox_weapon" ON ("sandbox_unit"."id" = "sandbox_weapon"."unit_id")
GROUP BY "sandbox_player"."id", "sandbox_player"."name"
And this is the crucial difference between the second and the third queries. In the second query, you're joining Player to Unit, so a single Unit will be listed once for each player that it references.
But in the third query you're joining Player to Unit and then Unit to Weapon, so not only a single Unit will be listed once for each player that it references, but also for each weapon that references Unit.
Let's take a look at the simple example:
insert into sandbox_player values (1, "player_1");
insert into sandbox_unit values(1, 10, 1);
insert into sandbox_weapon values (1, 1), (2, 1);
One player, one unit and two weapons that reference the same unit.
Confirm that the problem exists:
>>> from sandbox.models import Player
>>> from django.db.models import Count, Sum
>>> Player.objects.annotate(weapon_count=Count('unit_set__weapon_set')).values()
<QuerySet [{'id': 1, 'name': 'player_1', 'weapon_count': 2}]>
>>> Player.objects.annotate(rarity_sum=Sum('unit_set__rarity')).values()
<QuerySet [{'id': 1, 'name': 'player_1', 'rarity_sum': 10}]>
>>> Player.objects.annotate(
... weapon_count=Count('unit_set__weapon_set', distinct=True),
... rarity_sum=Sum('unit_set__rarity')).values()
<QuerySet [{'id': 1, 'name': 'player_1', 'weapon_count': 2, 'rarity_sum': 20}]>
From this example it's easy to see that the problem is that in the combined query the unit will be listed twice, one time for each of the weapons referencing it:
sqlite> SELECT "sandbox_player"."id",
...> "sandbox_player"."name",
...> "sandbox_weapon"."id",
...> "sandbox_unit"."rarity"
...> FROM "sandbox_player"
...> LEFT OUTER JOIN "sandbox_unit" ON ("sandbox_player"."id" = "sandbox_unit"."player_id")
...> LEFT OUTER JOIN "sandbox_weapon" ON ("sandbox_unit"."id" = "sandbox_weapon"."unit_id");
id name id rarity
---------- ---------- ---------- ----------
1 player_1 1 10
1 player_1 2 10
What should you do?
As #ivissani mentioned, one of the easiest solutions would be to write subqueries for each of the aggregations:
>>> from django.db.models import Count, IntegerField, OuterRef, Subquery, Sum
>>> weapon_count = Player.objects.annotate(weapon_count=Count('unit_set__weapon_set')).filter(pk=OuterRef('pk'))
>>> rarity_sum = Player.objects.annotate(rarity_sum=Sum('unit_set__rarity')).filter(pk=OuterRef('pk'))
>>> qs = Player.objects.annotate(
... weapon_count=Subquery(weapon_count.values('weapon_count'), output_field=IntegerField()),
... rarity_sum=Subquery(rarity_sum.values('rarity_sum'), output_field=IntegerField())
... )
>>> qs.values()
<QuerySet [{'id': 1, 'name': 'player_1', 'weapon_count': 2, 'rarity_sum': 10}]>
which produces the following SQL
SELECT "sandbox_player"."id", "sandbox_player"."name",
(
SELECT COUNT(U2."id") AS "weapon_count"
FROM "sandbox_player" U0
LEFT OUTER JOIN "sandbox_unit" U1
ON (U0."id" = U1."player_id")
LEFT OUTER JOIN "sandbox_weapon" U2
ON (U1."id" = U2."unit_id")
WHERE U0."id" = ("sandbox_player"."id")
GROUP BY U0."id", U0."name"
) AS "weapon_count",
(
SELECT SUM(U1."rarity") AS "rarity_sum"
FROM "sandbox_player" U0
LEFT OUTER JOIN "sandbox_unit" U1
ON (U0."id" = U1."player_id")
WHERE U0."id" = ("sandbox_player"."id")
GROUP BY U0."id", U0."name") AS "rarity_sum"
FROM "sandbox_player"
A few notes to complement rktavi's excellent answer:
1) This issues has apparently been considered a bug for 10 years already. It is even referred to in the official documentation.
2) While converting my actual project's QuerySets to subqueries (as per rktavi's answer), I noticed that combining bare-bone annotations (for the distinct=True counts that always worked correctly) with a Subquery (for the sums) yields extremely long processing (35 sec vs. 100 ms) and incorrect results for the sum. This is true in my actual setup (11 filtered counts on various nested relations and 1 filtered sum on a multiply-nested relation, SQLite3) but cannot be reproduced with the simple models above. This issue can be tricky because another part of your code could add an annotation to your QuerySet (e.g a Table.order_FOO() function), leading to the issue.
3) With the same setup, I have anecdotical evidence that subquery-type QuerySets are faster compared to bare-bone annotation QuerySets (in cases where you have only distinct=True counts, of course). I could observe this both with local SQLite3 (83 ms vs 260 ms) and hosted PostgreSQL (320 ms vs 540 ms).
As a result of the above, I will completely avoid using bare-bone annotations in favour of subqueries.
Based on the excellent answer from #rktavi, I created two helpers classes that simplify the Subquery/Count and Subquery/Sum patterns:
class SubqueryCount(Subquery):
template = "(SELECT count(*) FROM (%(subquery)s) _count)"
output_field = PositiveIntegerField()
class SubquerySum(Subquery):
template = '(SELECT sum(_sum."%(column)s") FROM (%(subquery)s) _sum)'
def __init__(self, queryset, column, output_field=None, **extra):
if output_field is None:
output_field = queryset.model._meta.get_field(column)
super().__init__(queryset, output_field, column=column, **extra)
One can use these helpers like so:
from django.db.models import OuterRef
weapons = Weapon.objects.filter(unit__player_id=OuterRef('id'))
units = Unit.objects.filter(player_id=OuterRef('id'))
qs = Player.objects.annotate(weapon_count=SubqueryCount(weapons),
rarity_sum=SubquerySum(units, 'rarity'))
Thanks #rktavi for your amazing answer!!
Here's my use case:
Using Django DRF.
I needed to get Sum and Count from different FK's inside the annotate so that it would all be part of one queryset in order to add these fields to the ordering_fields in DRF.
The Sum and Count were clashing and returning wrong results.
Your answer really helped me put it all together.
The annotate was occasionally returning the dates as strings, so I needed to Cast it to DateTimeField.
donation_filter = Q(payments__status='donated') & ~Q(payments__payment_type__payment_type='coupon')
total_donated_SQ = User.objects.annotate(total_donated=Sum('payments__sum', filter=donation_filter )).filter(pk=OuterRef('pk'))
message_count_SQ = User.objects.annotate(message_count=Count('events__id', filter=Q(events__event_id=6))).filter(pk=OuterRef('pk'))
queryset = User.objects.annotate(
total_donated=Subquery(total_donated_SQ.values('total_donated'), output_field=IntegerField()),
last_donation_date=Cast(Max('payments__updated', filter=donation_filter ), output_field=DateTimeField()),
message_count=Subquery(message_count_SQ.values('message_count'), output_field=IntegerField()),
last_message_date=Cast(Max('events__updated', filter=Q(events__event_id=6)), output_field=DateTimeField())
)
I have a list cities = ['Rome', 'Barcelona', 'Budapest', 'Ljubljana']
Then,
I have a sqlalchemy model as follows -
class Fly(Base):
__tablename__ = 'fly'
pkid = Column('pkid', INTEGER(unsigned=True), primary_key=True, nullable=False)
city = Column('city', VARCHAR(45), unique=True, nullable=False)
country = Column('country', VARCHAR(45))
flight_no = Column('Flight', VARCHAR(45))
I need to check if ALL the values in given cities list exists in fly table or not using sqlalchemy. Return true only if ALL the cities exists in table. Even if a single city doesn't exist in table, I need to return false and list of cities that doesn't exist. How to do that? Any ideas/hints/suggestions? I'm using MYSQL
One way would be to create a (temporary) relation based on the given list and take the set difference between it and the cities from the fly table. In other words create a union of the values from the list1:
from sqlalchemy import union, select, literal
cities_union = union(*[select([literal(v)]) for v in cities])
Then take the difference:
sq = cities_union.select().except_(select([Fly.city]))
and check that no rows are left after the difference:
res = session.query(~exists(sq)).scalar()
For a list of cities lacking from fly table omit the (NOT) EXISTS:
res = session.execute(sq).fetchall()
1 Other database vendors may offer alternative methods for producing relations from arrays, such as Postgresql and its unnest().
A part of the model that I have, which uses Django Model field, is like the following:
class SalesModel(models.Model):
some_data = models.PositiveIntegerField(db_index=True)
some_other_data = models.CharField(max_length=50)
json_data = JSONField(blank=True, null=True)
Now following is the format of the JsonData field:
[{"id": val, "contribution": "some_val", }, {"id": some_val, "contribution": "some_other_val",}, {"id": other_val, "contribution": "some_another_val"}]
i.e., the format is:
[{'id':XX, 'contribution':XX},{'id':YY, 'contribution':YY},{'id':ZZ, 'contribution':ZZ}]
Currently I can filter the Django table with the val of ID. I would now, like to know the contribution of that particular ID.
For eg, if val = 1, I would like to filter the model SalesModel which has JsonField with id = 1, and I want to show the related contribution. So, that would mean, out of the 3 possible dictionaries (as per the field construction), I would only show one dictionary (filtered by the 'ID' key of that dictionary). That would mean, if the 2nd dictionary has a matching ID, show only the 2nd contribution, if the 1st ID is matching show only the 1st contribution, and similarly for the 3rd dictionary.
Is there a way that can be done?
You could restructure your JSONField differently, by giving it a dict where the key, value pairs are id: contribution directly. This way you could use the has_key filter and KeyTransform will work, as I'm not sure it works on an array of dicts. So assuming your json_data looks like this:
{1: 'xx', 3: 'yy', 9: 'zz'}
you could query this way, based on #vanojx1 contribution:
SalesModel.filter(json_data__has_key=id)\
.annotate(contrib=KeyTransform(id, 'json_data')\
.values('contrib')
Alternatively, using raw jsonb in postgresql:
SalesModel.filter(json_data__has_key=id)\
.extra(select={'contrib': "json_data->{0}".format(id)})\
.values('contrib')
This should work DOC
SalesModel.objects.filter(json_data__id=1).values('id', 'json_data__contribution')
Yes, I guess. If I have understood it right, you will have an id to be matched or a list of ID's. So if your ID is 2:
my_id = 2
dict1 = [{"id":1, "contribution":10},{"id":2, "contribution":20},{"id":3, "contribution":30}]
for i in dict1:
if i["id"] == my_id:
print(i["contribution"])