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(Lead.Id).label("CustomCount"), Lead.Id).group_by(Lead.Id) for instance in rs: print("Count: ", instance.CustomCount) print("Id: ", instance.Id) print("---------")
You can also execute COUNT using the session object's execute() method:
rs = 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)) 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(Lead.AnnualRevenue).label("CustomSum"), Lead.Id).group_by(Lead.Id) for instance in rs: print("Sum: ", instance.CustomSum) print("Id: ", instance.Id) print("---------")
You can also invoke SUM using the session object's execute() method.
rs = 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)) 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(Lead.AnnualRevenue).label("CustomAvg"), Lead.Id).group_by(Lead.Id) for instance in rs: print("Avg: ", instance.CustomAvg) print("Id: ", instance.Id) print("---------")
You can also use the session object's execute() method to invoke AVG:
rs = 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)) 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(Lead.AnnualRevenue).label("CustomMax"), func.min(Lead.AnnualRevenue).label("CustomMin"), Lead.Id).group_by(Lead.Id) for instance in rs: print("Max: ", instance.CustomMax) print("Min: ", instance.CustomMin) print("Id: ", instance.Id) print("---------")
You can also use the session object's execute() method to invoke MAX and MIN:
rs = 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)) for instance in rs: