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(GoalHeadings.GoalHeadingId).label("CustomCount"), GoalHeadings.GoalHeadingId).group_by(GoalHeadings.GoalHeadingId)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("GoalHeadingId: ", instance.GoalHeadingId)
	print("---------")

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

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

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

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

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

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

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

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