Using TimescaleDB with Django ORM for OHLC Calculations

To use TimescaleDB's time_bucket function with Django ORM for calculating OHLC values, you'll need to create a custom query using Django's RawSQL or a custom manager. Since TimescaleDB's specialized functions aren't directly available in Django's ORM, you'll need to create a bridge between them.

Here's how you can implement this:

1. Create a Custom Manager

PYTHONCopied
from django.db import models
from django.db.models.expressions import RawSQL
from django.db.models import Min, Max, F

class FinancialDataManager(models.Manager):
    def get_ohlc(self, interval='1 hour', start_time=None, end_time=None):
        """
        Get OHLC data using TimescaleDB's time_bucket function
        
        Args:
            interval: A string like '1 hour', '30 minutes', '1 day'
            start_time: Optional datetime to filter from
            end_time: Optional datetime to filter to
        """
        query = self.get_queryset()
        
        if start_time:
            query = query.filter(timestamp__gte=start_time)
        if end_time:
            query = query.filter(timestamp__lte=end_time)
            
        # Use RawSQL to incorporate time_bucket
        query = query.annotate(
            bucket=RawSQL("time_bucket(%s, timestamp)", (interval,))
        ).values('bucket').annotate(
            open_price=RawSQL("first(open, timestamp)", ()),
            close_price=RawSQL("last(close, timestamp)", ()),
            high_price=Max('high'),
            low_price=Min('low')
        ).order_by('bucket')
        
        return query

2. Update Your Model

PYTHONCopied
from django.db import models

class FinancialData(models.Model):
    timestamp = models.DateTimeField()
    open = models.FloatField()
    high = models.FloatField()
    low = models.FloatField()
    close = models.FloatField()
    
    objects = models.Manager()  # Default manager
    timescale = FinancialDataManager()  # Custom manager
    
    class Meta:
        managed = False  # No migrations will be created for this model.
        db_table = 'financial_data'

3. Usage Example

PYTHONCopied
# Get hourly OHLC data for the last week
from datetime import datetime, timedelta

end_time = datetime.now()
start_time = end_time - timedelta(days=7)

hourly_data = FinancialData.timescale.get_ohlc(
    interval='1 hour',
    start_time=start_time,
    end_time=end_time
)

# Print the results
for data in hourly_data:
    print(f"Time: {data['bucket']}, Open: {data['open_price']}, High: {data['high_price']}, "
          f"Low: {data['low_price']}, Close: {data['close_price']}")

Notes:

1. This approach uses TimescaleDB's time_bucket, first, and last functions through Django's RawSQL.
2. Make sure you have the TimescaleDB extension installed and activated in your PostgreSQL database.
3. The first and last functions are TimescaleDB-specific aggregates that get the first/last value ordered by the second parameter.
4. You may need to adjust the SQL syntax depending on your specific TimescaleDB version.
5. Be careful with user input for the interval parameter to avoid SQL injection.

This implementation gives you the flexibility of TimescaleDB's time-series functions while still working within Django's ORM framework.