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https://github.com/paul-wolf/djaq

Django queries
https://github.com/paul-wolf/djaq

django-application django-models django-orm djaq-query query-language

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Django queries

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README 

        
Djaq

====



|Python tests| |RTD build| |Python versions| |PyPi version| 



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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 idiosyncratic methods 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:



.. code:: shell



   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.



-  `Documentation `__

-  `Installation `__

-  `Settings `__

-  `Query

   Usage `__

-  `Sample

   Project `__



Here's an example comparison between Djaq and Django QuerySets that gets every

publisher and counts the books for each that are above and below a rating

threshold.



.. code:: python



   DQ("Book", """publisher.name,

       sumif(rating < 3, 1, 0) as below_3,

       sumif(rating >= 3, 1, 0) as above_3

       """)



compared to QuerySet:



.. code:: python

   

   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:



.. code:: python



   DQ("Book", "avg(price), max(price), min(price)")



compared to QuerySet:



.. code:: python



   Book.objects.aggregate(Avg('price'), Max('price'), Min('price'))



Get the difference from the average off the maximum price for each publisher:



.. code:: python



   DQ("Book", "publisher.name, max(price) - avg(price) as price_diff")



compared to QuerySet:



.. code:: python



   from django.db.models import Avg, Max

   Book.objects.values("publisher__name") \

      .annotate(price_diff=Max('price') - Avg('price'))