I'm using SQLAlchemy to programmatically query a table with a composite foreign key. e.g.:
CREATE TABLE example (
id INT NOT NULL,
date TIMESTAMP NOT NULL,
data VARCHAR(128)
PRIMARY KEY (id, date)
)
I'd like to take a list of values and get rows back e.g.:
interesting_data = (
(1, '2016-5-1'),
(1, '2016-6-1'),
(2, '2016-6-1'),
(3, '2016-5-1'),
(3, '2016-6-1'),
)
select(
[example.c.id, example.c.date, example.c.data],
).where(example.primary_key.in_(interesting_data)
If each column was independent I could do
interesting_ids = [1,2,3]
interesting_dates = ['2016-5-1', '2016-6-1']
select(
[example.c.id, example.c.date, example.c.data],
).where(
example.c.id.in_(interesting_ids)
).where(
example.c.date.in_(interesting_dates)
)
But that clearly fails to bring only the unique matching (id, date) tuples. I suspect there is a way to specify the compound primary key to query, but I can't find any documentation after a search.
Assuming your model class is called Example
with (id, date) is the composite primary key:
You can query either with:
import sqlalchemy
...
Example.query.get((id, date))
or
import sqlalchemy
from sqlalchemy.orm import sessionmaker
...
engine = sqlalchemy.create_engine('postgresql://user:pass@localhost/db_name')
session = sessionmaker(bind=engine)()
session.query(Example).get((id, date))
Use a list comprehension in your where clause:
from sqlalchemy import and_, or_, select
stmt = select(
[example.c.id, example.c.date, example.c.data]
).where(or_(and_(example.c.id==data[0], example.c.date==data[1])
for data in interesting_data))
However, a separate issue I noticed is that you're comparing a date column to string data type. The interesting_data
list should be
import datetime as dt
interesting_data = (
(1, dt.date(2016,5,1)),
(1, dt.date(2016,6,1)),
(2, dt.date(2016,6,1)),
(3, dt.date(2016,6,1)),
(3, dt.date(2016,6,1)),
)
Also, note that it is possible to create a basic statement, and then add clauses to it incrementally, leading to (hopefully) better legibility and code reuse.
So, it would be possible to write the above as
base_stmt = select([example.c.id, example.c.date, example.c.data])
wheres = or_(and_(example.c.id==data[0], example.c.date==data[1])
for data in interesting_data))
stmt = base_stmt.where(wheres)
This generates the following sql (new-lines & spaces added by me):
SELECT example.id, example.date, example.data
FROM example
WHERE
example.id = :id_1 AND example.date = :date_1
OR example.id = :id_2 AND example.date = :date_2
OR example.id = :id_3 AND example.date = :date_3
OR example.id = :id_4 AND example.date = :date_4
OR example.id = :id_5 AND example.date = :date_5
note: if you have a lot of rows to filter like this, it may be more efficient to create a temporary table, insert rows into this temporary table from interesting_data
, and then inner join to this table, rather than add the where clause as shown above.
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