CData Python Connector for OData

Build 20.0.7587

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.

for instance in session.query(func.count(Lead.Id).label("CustomCount"), Lead.Id).group_by(Lead.Id):
	print("Count: ", instance.CustomCount)
	print("Id: ", instance.Id)
	print("---------")

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

for instance in session.execute(Lead_table.select().with_only_columns([func.count(Lead_table.c.Id).label("CustomCount"), Lead_table.c.Id])group_by(Lead_table.c.Id)):

SUM

This example calculates the cumulative amount of a numeric column in a set of groups.

for instance in session.query(func.sum(Lead.AnnualRevenue).label("CustomSum"), Lead.Id).group_by(Lead.Id):
	print("Sum: ", instance.CustomSum)
	print("Id: ", instance.Id)
	print("---------")

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

for instance in session.execute(Lead_table.select().with_only_columns([func.sum(Lead_table.c.AnnualRevenue).label("CustomSum"), Lead_table.c.Id])group_by(Lead_table.c.Id)):

AVG

This example calculates the average amount of a numeric column in a set of groups using the session object's query() method.

for instance in session.query(func.avg(Lead.AnnualRevenue).label("CustomAvg"), Lead.Id).group_by(Lead.Id):
	print("Avg: ", instance.CustomAvg)
	print("Id: ", instance.Id)
	print("---------")

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

for instance in session.execute(Lead_table.select().with_only_columns([func.avg(Lead_table.c.AnnualRevenue).label("CustomAvg"), Lead_table.c.Id])group_by(Lead_table.c.Id)):

MAX and MIN

This example finds the maximum value and minimum value of a numeric column in a set of groups.

for instance in session.query(func.max(Lead.AnnualRevenue).label("CustomMax"), func.min(Lead.AnnualRevenue).label("CustomMin"), Lead.Id).group_by(Lead.Id):
	print("Max: ", instance.CustomMax)
	print("Min: ", instance.CustomMin)
	print("Id: ", instance.Id)
	print("---------")

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

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

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Build 20.0.7587