I'm trying to implement dynamic filtering using SQLAlchemy ORM.
I was looking through StackOverflow and found very similar question:SQLALchemy dynamic filter_by
It's useful for me, but not enough.
So, here is some example of code, I'm trying to write:
# engine - MySQL engine
session_maker = sessionmaker(bind=engine)
session = session_maker()
# my custom model
model = User
def get_query(session, filters):
if type(filters) == tuple:
query = session.query(model).filter(*filters)
elif type(filters) == dict:
query = session.query(model).filter(**filters)
return query
then I'm trying to reuse it with something very similar:
filters = (User.name == 'Johny')
get_query(s, filters) # it works just fine
filters = {'name': 'Johny'}
get_query(s, filters)
After the second run, there are some issues:
TypeError: filter() got an unexpected keyword argument 'name'
When I'm trying to change my filters to:
filters = {User.name: 'Johny'}
it returns:
TypeError: filter() keywords must be strings
But it works fine for manual querying:
s.query(User).filter(User.name == 'Johny')
What is wrong with my filters?
BTW, it looks like it works fine for case:
filters = {'name':'Johny'}
s.query(User).filter_by(**filters)
But following the recommendations from mentioned post I'm trying to use just filter.
If it's just one possible to use filter_by instead of filter, is there any differences between these two methods?
Your problem is that filter_by takes keyword arguments, but filter takes expressions. So expanding a dict for filter_by **mydict will work. With filter, you normally pass it one argument, which happens to be an expression. So when you expand your **filters dict to filter, you pass filter a bunch of keyword arguments that it doesn't understand.
If you want to build up a set of filters from a dict of stored filter args, you can use the generative nature of the query to keep applying filters. For example:
# assuming a model class, User, with attributes, name_last, name_first
my_filters = {'name_last':'Duncan', 'name_first':'Iain'}
query = session.query(User)
for attr,value in my_filters.iteritems():
query = query.filter( getattr(User,attr)==value )
# now we can run the query
results = query.all()
The great thing about the above pattern is you can use it across multiple joined columns, you can construct 'ands' and 'ors' with and_ and or_, you can do <= or date comparisons, whatever. It's much more flexible than using filter_by with keywords. The only caveat is that for joins you have to be a bit careful you don't accidentally try to join a table twice, and you might have to specify the join condition for complex filtering. I use this in some very complex filtering over a pretty involved domain model and it works like a charm, I just keep a dict going of entities_joined to keep track of the joins.