8.50. SQLAlchemy Func Numeric

• array_agg - Support for the ARRAY_AGG function

• count - The ANSI COUNT aggregate function. With no arguments, emits COUNT *

• cube - Implement the CUBE grouping operation

• cume_dist - Implement the cume_dist hypothetical-set aggregate function

• dense_rank - Implement the dense_rank hypothetical-set aggregate function

• max - The SQL MAX() aggregate function

• min - The SQL MIN() aggregate function

• mode - Implement the mode ordered-set aggregate function

• percent_rank - Implement the percent_rank hypothetical-set aggregate function

• percentile_cont - Implement the percentile_cont ordered-set aggregate function

• percentile_disc - Implement the percentile_disc ordered-set aggregate function

• random - The RANDOM() SQL function

• rank - Implement the rank hypothetical-set aggregate function

• sum - The SQL SUM() aggregate function

8.50.1. About

Table 8.19. SQL and Generic Functions

Object	Name Description
array_agg	Support for the ARRAY_AGG function
count	The ANSI COUNT aggregate function. With no arguments, emits COUNT *
cube	Implement the CUBE grouping operation
cume_dist	Implement the cume_dist hypothetical-set aggregate function
dense_rank	Implement the dense_rank hypothetical-set aggregate function
max	The SQL MAX() aggregate function
min	The SQL MIN() aggregate function
mode	Implement the mode ordered-set aggregate function
percent_rank	Implement the percent_rank hypothetical-set aggregate function
percentile_cont	Implement the percentile_cont ordered-set aggregate function
percentile_disc	Implement the percentile_disc ordered-set aggregate function
random	The RANDOM() SQL function
rank	Implement the rank hypothetical-set aggregate function
sum	The SQL SUM() aggregate function

8.50.2. Count

• https://docs.sqlalchemy.org/en/stable/core/functions.html#sqlalchemy.sql.functions.count

>>> from sqlalchemy import func
>>> from sqlalchemy import distinct

Count User records, without sing a subquery:

>>> session.query(func.count(User.id))  

Return count of user 'id' grouped by 'name':

>>> session.query(func.count(User.id)).\
...         group_by(User.name)  

Count distinct 'name' values:

>>> session.query(func.count(distinct(User.name)))