Should I use raw SQL queries or something else?

[dmemb...@robottions.com]

After using Django for 4 months and enjoying it, now I'm trying DRF. While it's suited for most of my needs, I found an issue and I don't know how to deal with.

Let's say I have a TrainTravel model, with fields such as: passengers, average_km_hour, arrival_timestamp, departure_timestamp, and so on.

It's easy to query DRF for all TrainTravel , or for just all Trains with at least 50 passengers or Trains with an average of 150km/h.

The problem is when I want to do big queries, and those queries will return fields that don't exist in the model of the database. I'll explain:

Let's say I want a query that returns the average of passengers by day on the last 2 months, grouped by day and the average km/hour.

With normal SQL I would query the database and just return 'average_passagers', 'average_km_hour_by_day' and 'datetime' (the actual fields are a random example). But in DRF I can:

1) Get all TrainTravel objects instances and manipulate the data with Python: Super slow if I've to pull every register on the database

2) Perform a raw query with SQL. The problem is that it doesn't correspond with any existing model in the API. And I create a new model for every query, it will create a new table in the database.

So, in short: Sometimes I want to perform queries in the database that don't return the same fields of any model (sometimes I get info from 3 tables), but I just want to return a Json from the query.

It is DRF for me in this case?

[gordon]

I think this is what you're looking for

https://docs.djangoproject.com/en/2.0/topics/db/aggregation/

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[Julio Biason]

Hi Dmembrives,

If I'm not mistaken, you can add calculated fields in DRF serializers. So you can add @property fields (calculated values) on your models and just return those values. You can see an example of a calculated field here: https://docs.djangoproject.com/en/2.0/topics/db/models/#model-methods

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