CData Python Connector for BigCommerce

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

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

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

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

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

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

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

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

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

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Build 21.0.7930