python 38 lines · 1 tab

Django ORM window functions for analytics

Priya Sharma Jan 2026

1 tab

from django.db.models import F, Window
from django.db.models.functions import RowNumber, Rank, DenseRank
from products.models import Sale


def get_sales_with_ranking():
    """Add rank to sales by amount."""
    sales = Sale.objects.annotate(
        rank=Window(
            expression=Rank(),
            order_by=F('amount').desc()
        ),
        row_number=Window(
            expression=RowNumber(),
            order_by=F('created_at').desc()
        )
    )
    return sales


def get_salesperson_rankings():
    """Rank salespeople within each region."""
    from django.db.models import Sum

    sales = Sale.objects.values(
        'salesperson__name',
        'salesperson__region'
    ).annotate(
        total_sales=Sum('amount')
    ).annotate(
        region_rank=Window(
            expression=Rank(),
            partition_by=[F('salesperson__region')],
            order_by=F('total_sales').desc()
        )
    ).order_by('salesperson__region', 'region_rank')

    return sales

1 file · python Explain with highlit

Window functions perform calculations across rows related to the current row. I use them for running totals, rankings, and moving averages. Django's Window expression with functions like RowNumber, Rank, DenseRank provide SQL window function support. This is more efficient than Python-side calculations. I partition data with partition_by and order with order_by. Window functions are perfect for leaderboards, time-series analysis, and comparative metrics. They require PostgreSQL or other databases supporting window functions.

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