SQLAlchemy: several counts in one query

Question

I am having hard time optimizing my SQLAlchemy queries. My SQL knowledge is very basic, and I just can't get the stuff I need from the SQLAlchemy docs.

Suppose the following very basic one-to-many relationship:

class Parent(Base):
    __tablename__ = "parents"
    id = Column(Integer, primary_key = True)
    children = relationship("Child", backref = "parent")

class Child(Base):
    __tablename__ = "children"
    id = Column(Integer, primary_key = True)
    parent_id = Column(Integer, ForeignKey("parents.id"))
    naughty = Column(Boolean)

How could I:

• Query tuples of (Parent, count_of_naughty_children, count_of_all_children) for each parent?

After decent time spent googling, I found how to query those values separately:

# The following returns tuples of (Parent, count_of_all_children):
session.query(Parent, func.count(Child.id)).outerjoin(Child, Parent.children).\
    group_by(Parent.id)
# The following returns tuples of (Parent, count_of_naughty_children):
al = aliased(Children, session.query(Children).filter_by(naughty = True).\
    subquery())
session.query(Parent, func.count(al.id)).outerjoin(al, Parent.children).\
    group_by(Parent.id)

I tried to combine them in different ways, but didn't manage to get what I want.

• Query all parents which have more than 80% naughty children? Edit: naughty could be NULL.

I guess this query is going to be based on the previous one, filtering by naughty/all ratio.

Any help is appreciated.

EDIT : Thanks to Antti Haapala's help, I found solution to the second question:

avg = func.avg(func.coalesce(Child.naughty, 0)) # coalesce() treats NULLs as 0
# avg = func.avg(Child.naughty) - if you want to ignore NULLs
session.query(Parent).join(Child, Parent.children).group_by(Parent).\
    having(avg > 0.8)

It finds average if children's naughty variable, treating False and NULLs as 0, and True as 1. Tested with MySQL backend, but should work on others, too.

Bottoms

Answer 1

the count() sql aggretate function is pretty simple; it gives you the total number of non-null values in each group. With that in mind, we can adjust your query to give you the proper result.

print (Query([
    Parent,
    func.count(Child.id),
    func.count(case(
        [((Child.naughty == True), Child.id)], else_=literal_column("NULL"))).label("naughty")])

    .join(Parent.children).group_by(Parent)
    )

Which produces the following sql:

SELECT 
 parents.id AS parents_id, 
 count(children.id) AS count_1, 
 count(CASE WHEN (children.naughty = 1) 
       THEN children.id 
       ELSE NULL END) AS naughty 
FROM parents 
JOIN children ON parents.id = children.parent_id 
GROUP BY parents.id

Pinworm

Answer 2

If your query is only to get the parents who have > 80 % children naughty, you can on most databases cast the naughty to integer, then take average of it; then having this average greater than 0.8.

Thus you get something like

from sqlalchemy.sql.expression import cast

naughtyp = func.avg(cast(Child.naughty, Integer))
session.query(Parent, func.count(Child.id), naughtyp).join(Child)\
    .group_by(Parent.id).having(naughtyp > 0.8).all()

Nabonidus

Thanks a lot, that did the trick. But I didn't mention that in my real model "naughty" could be null - sorry, my fault. Null values are getting ignored by avg, so this solution isn't exactly what I want. – Bottoms

func.coalesce() helped me to fix this ^^ – Bottoms