CData Python Connector for eBay

Build 21.0.7930

Aggregate Functions

Certain aggregate functions can also be used within SQLAlchemy by using the func module. First, you will need to import it:

from sqlalchemy.sql import func

Once imported, the following aggregate functions are available:

COUNT

This example counts the number of records in a set of groups using the session object's query() method.

rs = session.query(func.count(ItemListing.ItemId).label("CustomCount"), ItemListing.HitCount).group_by(ItemListing.HitCount)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("HitCount: ", instance.HitCount)
	print("---------")

Alternatively, you can execute COUNT using the session object's execute() method.

rs = session.execute(ItemListing_table.select().with_only_columns([func.count(ItemListing_table.c.ItemId).label("CustomCount"), ItemListing_table.c.HitCount])group_by(ItemListing_table.c.HitCount))
for instance in rs:

SUM

This example calculates the cumulative amount of a numeric column in a set of groups.

rs = session.query(func.sum(ItemListing.MinimumBestOfferPrice).label("CustomSum"), ItemListing.HitCount).group_by(ItemListing.HitCount)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("HitCount: ", instance.HitCount)
	print("---------")

Alternatively, you can invoke SUM using the session object's execute() method.

rs = session.execute(ItemListing_table.select().with_only_columns([func.sum(ItemListing_table.c.MinimumBestOfferPrice).label("CustomSum"), ItemListing_table.c.HitCount]).group_by(ItemListing_table.c.HitCount))
for instance in rs:

AVG

This example calculates the average amount of a numeric column in a set of groups using the session object's query() method.

rs = session.query(func.avg(ItemListing.MinimumBestOfferPrice).label("CustomAvg"), ItemListing.HitCount).group_by(ItemListing.HitCount)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("HitCount: ", instance.HitCount)
	print("---------")

Alternatively, you can invoke AVG using the session object's execute() method.

rs = session.execute(ItemListing_table.select().with_only_columns([func.avg(ItemListing_table.c.MinimumBestOfferPrice).label("CustomAvg"), ItemListing_table.c.HitCount]).group_by(ItemListing_table.c.HitCount))
for instance in rs:

MAX and MIN

This example finds the maximum value and minimum value of a numeric column in a set of groups.

rs = session.query(func.max(ItemListing.MinimumBestOfferPrice).label("CustomMax"), func.min(ItemListing.MinimumBestOfferPrice).label("CustomMin"), ItemListing.HitCount).group_by(ItemListing.HitCount)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("HitCount: ", instance.HitCount)
	print("---------")

Alternatively, you can invoke MAX and MIN using the session object's execute() method.

rs = session.execute(ItemListing_table.select().with_only_columns([func.max(ItemListing_table.c.MinimumBestOfferPrice).label("CustomMax"), func.min(ItemListing_table.c.MinimumBestOfferPrice).label("CustomMin"), ItemListing_table.c.HitCount]).group_by(ItemListing_table.c.HitCount))
for instance in rs:

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Build 21.0.7930