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(Schemas.Id).label("CustomCount"), Schemas.Type).group_by(Schemas.Type)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("Type: ", instance.Type)
	print("---------")

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

rs = session.execute(Schemas_table.select().with_only_columns([func.count(Schemas_table.c.Id).label("CustomCount"), Schemas_table.c.Type])group_by(Schemas_table.c.Type))
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(Schemas.AnnualRevenue).label("CustomSum"), Schemas.Type).group_by(Schemas.Type)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("Type: ", instance.Type)
	print("---------")

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

rs = session.execute(Schemas_table.select().with_only_columns([func.sum(Schemas_table.c.AnnualRevenue).label("CustomSum"), Schemas_table.c.Type]).group_by(Schemas_table.c.Type))
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(Schemas.AnnualRevenue).label("CustomAvg"), Schemas.Type).group_by(Schemas.Type)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("Type: ", instance.Type)
	print("---------")

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

rs = session.execute(Schemas_table.select().with_only_columns([func.avg(Schemas_table.c.AnnualRevenue).label("CustomAvg"), Schemas_table.c.Type]).group_by(Schemas_table.c.Type))
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(Schemas.AnnualRevenue).label("CustomMax"), func.min(Schemas.AnnualRevenue).label("CustomMin"), Schemas.Type).group_by(Schemas.Type)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("Type: ", instance.Type)
	print("---------")

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

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