CData Python Connector for Odoo

Build 24.0.8963

Aggregate Functions

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(res_users.id).label("CustomCount"), res_users.name).group_by(res_users.name)
for instance in rs:
	print("Count: ", instance.CustomCount)
	print("name: ", instance.name)
	print("---------")

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

rs = session.execute(res_users_table.select().with_only_columns([func.count(res_users_table.c.id).label("CustomCount"), res_users_table.c.name])group_by(res_users_table.c.name))
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(res_users.meeting_count).label("CustomSum"), res_users.name).group_by(res_users.name)
for instance in rs:
	print("Sum: ", instance.CustomSum)
	print("name: ", instance.name)
	print("---------")

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

rs = session.execute(res_users_table.select().with_only_columns([func.sum(res_users_table.c.meeting_count).label("CustomSum"), res_users_table.c.name]).group_by(res_users_table.c.name))
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(res_users.meeting_count).label("CustomAvg"), res_users.name).group_by(res_users.name)
for instance in rs:
	print("Avg: ", instance.CustomAvg)
	print("name: ", instance.name)
	print("---------")

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

rs = session.execute(res_users_table.select().with_only_columns([func.avg(res_users_table.c.meeting_count).label("CustomAvg"), res_users_table.c.name]).group_by(res_users_table.c.name))
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(res_users.meeting_count).label("CustomMax"), func.min(res_users.meeting_count).label("CustomMin"), res_users.name).group_by(res_users.name)
for instance in rs:
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("name: ", instance.name)
	print("---------")

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

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

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Build 24.0.8963