Certain aggregate functions can also be used within SQLAlchemy by using the func module.

To import this module, execute:

from sqlalchemy.sql import func

Once func is imported, the following aggregate functions are available:

COUNT

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

rs = session.query(func.count("CData"."SYSTEM".Customers.Id).label("CustomCount"), "CData"."SYSTEM".Customers.CompanyName).group_by("CData"."SYSTEM".Customers.CompanyName)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("CompanyName: ", instance.CompanyName)
	print("---------")

You can also execute COUNT using the session object's execute() method:

rs = session.execute("CData"."SYSTEM".Customers_table.select().with_only_columns([func.count("CData"."SYSTEM".Customers_table.c.Id).label("CustomCount"), "CData"."SYSTEM".Customers_table.c.CompanyName])group_by("CData"."SYSTEM".Customers_table.c.CompanyName))
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("CData"."SYSTEM".Customers.AnnualRevenue).label("CustomSum"), "CData"."SYSTEM".Customers.CompanyName).group_by("CData"."SYSTEM".Customers.CompanyName)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("CompanyName: ", instance.CompanyName)
	print("---------")

You can also invoke SUM using the session object's execute() method.

rs = session.execute("CData"."SYSTEM".Customers_table.select().with_only_columns([func.sum("CData"."SYSTEM".Customers_table.c.AnnualRevenue).label("CustomSum"), "CData"."SYSTEM".Customers_table.c.CompanyName]).group_by("CData"."SYSTEM".Customers_table.c.CompanyName))
for instance in rs:

AVG

This example uses the session object's query() method to calculate the average amount of a numeric column in a set of groups:

rs = session.query(func.avg("CData"."SYSTEM".Customers.AnnualRevenue).label("CustomAvg"), "CData"."SYSTEM".Customers.CompanyName).group_by("CData"."SYSTEM".Customers.CompanyName)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("CompanyName: ", instance.CompanyName)
	print("---------")

You can also use the session object's execute() method to invoke AVG:

rs = session.execute("CData"."SYSTEM".Customers_table.select().with_only_columns([func.avg("CData"."SYSTEM".Customers_table.c.AnnualRevenue).label("CustomAvg"), "CData"."SYSTEM".Customers_table.c.CompanyName]).group_by("CData"."SYSTEM".Customers_table.c.CompanyName))
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("CData"."SYSTEM".Customers.AnnualRevenue).label("CustomMax"), func.min("CData"."SYSTEM".Customers.AnnualRevenue).label("CustomMin"), "CData"."SYSTEM".Customers.CompanyName).group_by("CData"."SYSTEM".Customers.CompanyName)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("CompanyName: ", instance.CompanyName)
	print("---------")

You can also use the session object's execute() method to invoke MAX and MIN:

rs = session.execute("CData"."SYSTEM".Customers_table.select().with_only_columns([func.max("CData"."SYSTEM".Customers_table.c.AnnualRevenue).label("CustomMax"), func.min("CData"."SYSTEM".Customers_table.c.AnnualRevenue).label("CustomMin"), "CData"."SYSTEM".Customers_table.c.CompanyName]).group_by("CData"."SYSTEM".Customers_table.c.CompanyName))
for instance in rs: