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To select data from a table via SQLAlchemy, you need to build a representation of that table within SQLAlchemy. If Jupyter Notebook's response speed is any indication, that representation isn't filled in (with data from your existing database) until the query is executed. You need Table to build a table.
all() method. The Query object, when asked to return full entities, will deduplicate entries based on primary key, meaning if the same primary key value would appear in the results more than once, only one object of that primary key would be present.
All SELECT statements generated by SQLAlchemy ORM are constructed by Query object. It provides a generative interface, hence successive calls return a new Query object, a copy of the former with additional criteria and options associated with it.
You'll need to use a literal_column, which looks a bit like this:
sqlalchemy.orm.Query(Item, sqlalchemy.sql.expression.literal_column("0"))
Beware that the text argument is inserted into the query without any transformation; this may expose you to a SQL Injection vulnerability if you accept values for the text parameter from outside your application. If that's something you need, you'll want to use bindparam, which is about as easy to use; but you will have to invent a name:
sqlalchemy.orm.Query(Item, sqlalchemy.sql.expression.bindparam("zero", 0))
As mentioned in the comments of the accepted answer there's a "shorthand" for bindparam() that alleviates the need to come up with a name for the literal bindparam, literal():
Return a literal clause, bound to a bind parameter.
So one does not have to write
session.query(Item, bindparam("zero", 0).label("subscribed"))
but just
session.query(Item, literal(0).label("subscribed"))
without having to worry about quoting etc., if passing strings or such.
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