A string-based Django query language
Project description
Djaq - pronounced “Jack” - is an alternative to the Django QuerySet API.
What sets it apart:
No need to import models
Clearer, more natural query syntax
More powerful expressions
More consistent query syntax without resorting to hacks like F() expressions, annotate(), aggregate()
Column expressions are entirely evaluated in the database
Extensible: you can write your own functions
Pandas: Easily turn a query into Pandas Dataframe
There is also a JSON representation of queries, so you can send queries from a client. It’s an instant API to your data. No need to write backend classes and serializers.
Djaq queries are strings. A query string for our example dataset might look like this:
DQ("Book", "name as title, publisher.name as publisher").go()
This retrieves a list of book titles with book publisher. But you can formulate far more sophisticated queries; see below. You can send Djaq queries from any language, Java, Javascript, golang, etc. to a Django application and get results as JSON. In contrast to REST frameworks, like TastyPie or Django Rest Framework (DRF), you have natural access to the Django ORM from the client.
Djaq sits on top of the Django ORM. It can happily be used alongside QuerySets.
Here’s an example comparison between Djaq and Django QuerySets:
DQ("Book", """
sumif(rating < 3, rating, 0) as below_3,
sumif(rating >= 3, rating, 0) as above_3
""")
compared to QuerySet:
from django.db.models import Count, Q
above_3 = Count('book', filter=Q(book__rating__gt=3))
below_3 = Count('book', filter=Q(book__rating__lte=3))
Publisher.objects.annotate(below_3=below_3).annotate(above_3=above_3)
Get average, maximum, minimum price of books:
DQ("Book", "avg(price), max(price), min(price)")
compared to QuerySet:
Book.objects.aggregate(Avg('price'), Max('price'), Min('price'))
Get the difference from the average off the maximum price:
DQ("Book", "publisher.name, max(price) - avg(price) as price_diff")
compared to QuerySet:
from django.db.models import FloatField, Avg, Max
Book.objects.values("publisher__name")
.annotate(price_diff=Max('price', output_field=FloatField()) - Avg('price', output_field=FloatField()))
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