SQLAlchemy ORM - Working with Joins



Now that we have two tables, we will see how to create queries on both tables at the same time. To construct a simple implicit join between Customer and Invoice, we can use Query.filter() to equate their related columns together. Below, we load the Customer and Invoice entities at once using this method −

from sqlalchemy.orm import sessionmaker
Session = sessionmaker(bind = engine)
session = Session()

for c, i in session.query(Customer, Invoice).filter(Customer.id == Invoice.custid).all():
   print ("ID: {} Name: {} Invoice No: {} Amount: {}".format(c.id,c.name, i.invno, i.amount))

The SQL expression emitted by SQLAlchemy is as follows −

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email, invoices.id 
AS invoices_id, invoices.custid 
AS invoices_custid, invoices.invno 
AS invoices_invno, invoices.amount 
AS invoices_amount
FROM customers, invoices
WHERE customers.id = invoices.custid

And the result of the above lines of code is as follows −

ID: 2 Name: Gopal Krishna Invoice No: 10 Amount: 15000
ID: 2 Name: Gopal Krishna Invoice No: 14 Amount: 3850
ID: 3 Name: Govind Pant Invoice No: 3 Amount: 10000
ID: 3 Name: Govind Pant Invoice No: 4 Amount: 5000
ID: 4 Name: Govind Kala Invoice No: 7 Amount: 12000
ID: 4 Name: Govind Kala Invoice No: 8 Amount: 8500
ID: 5 Name: Abdul Rahman Invoice No: 9 Amount: 15000
ID: 5 Name: Abdul Rahman Invoice No: 11 Amount: 6000

The actual SQL JOIN syntax is easily achieved using the Query.join() method as follows −

session.query(Customer).join(Invoice).filter(Invoice.amount == 8500).all()

The SQL expression for join will be displayed on the console −

SELECT customers.id 
AS customers_id, customers.name 
AS customers_name, customers.address 
AS customers_address, customers.email 
AS customers_email
FROM customers JOIN invoices ON customers.id = invoices.custid
WHERE invoices.amount = ?

We can iterate through the result using for loop −

result = session.query(Customer).join(Invoice).filter(Invoice.amount == 8500)
for row in result:
   for inv in row.invoices:
      print (row.id, row.name, inv.invno, inv.amount)

With 8500 as the bind parameter, following output is displayed −

4 Govind Kala 8 8500  

Query.join() knows how to join between these tables because there‚Äôs only one foreign key between them. If there were no foreign keys, or more foreign keys, Query.join() works better when one of the following forms are used −

query.join(Invoice, id == Address.custid) explicit condition
query.join(Customer.invoices) specify relationship from left to right
query.join(Invoice, Customer.invoices) same, with explicit target
query.join('invoices') same, using a string

Similarly outerjoin() function is available to achieve left outer join.

query.outerjoin(Customer.invoices)

The subquery() method produces a SQL expression representing SELECT statement embedded within an alias.

from sqlalchemy.sql import func

stmt = session.query(
   Invoice.custid, func.count('*').label('invoice_count')
).group_by(Invoice.custid).subquery()

The stmt object will contain a SQL statement as below −

SELECT invoices.custid, count(:count_1) AS invoice_count FROM invoices GROUP BY invoices.custid

Once we have our statement, it behaves like a Table construct. The columns on the statement are accessible through an attribute called c as shown in the below code −

for u, count in session.query(Customer, stmt.c.invoice_count).outerjoin(stmt, Customer.id == stmt.c.custid).order_by(Customer.id):
   print(u.name, count)

The above for loop displays name-wise count of invoices as follows −

Arjun Pandit None
Gopal Krishna 2
Govind Pant 2
Govind Kala 2
Abdul Rahman 2
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