Hi to all.
I try to use the code in this way (query LIKE with OR operator)
res = session.query(MAPPER).filter(or_(MAPPER.field.contains('Value1'),
MAPPER.field.contains('Value2'), MAPPER.field.contains('Value3'),MAPPER
.field.contains('Value4')))
With a small dataset, I found the records I want, but with a larger dataset
sqlalchemy return me an error:
more than 255 arguments.
To bypass this problem in the past I used the operator in_ in this way:
id_list = [1, 2, 3]
session.query(CLASS).filter(CLASS.field.in_(id_list)).all()
I've guessed that was possible to make something like this:
value_to_find = [CLASS.field.contains('value1'),
CLASS.field.contains('value2')]
session.query(CLASS).filter(CLASS.field.in_(value_to_find)).all()
This script runs without error, but didn't return me any result.
Because is a OR type query, it's a good idea make single research for each
value and storing the id of every record in a list?
Smothing like this:
res_list = []
for value in value_list:
res = session.query(MAPPER).filter(MAPPER.field.contains(value))
for r in res:
res_list.append(res.id_record)
Or there is a more pythonic way?
Thanks a lot
Luca
On Fri, Sep 27, 2013 at 5:43 PM, Ofir Herzas <herz...@gmail.com> wrote:
> Hi Luca,
> Keep in mind that contains will not map to 'like'. Hence if you want your
> query to have a 'like' clause, you'll have to use the 'like' method (the
> end result of 'contains' will be the same though as 'like' beginning and
> ending with a percent sign).
> On Sep 27, 2013 5:06 PM, "pyArchInit ArcheoImagineers" <
> pyarchi...@gmail.com> wrote:
>
>> Thanks a lot...sorry for my prevous post that I delete beacause I didn't
>> undestand I must to use this ~
>>
>> def test_not_like(self):
>> Session = sessionmaker(bind=self.engine, autoflush=True,
>> autocommit=True)
>> session = Session()
>> res = session.query(MAPPER).filter(and_(~MAPPER.field.contains('Value1'),
>> ~US.field.contains('Value2'),
>> ~US.field.contains('Value3'),~US.field.contains('Value4')))
>>
>> return res
>>
>> This appear to run properly now I test with my little dataset and I'll
>> try to understand is what I must to find.
>>
>> Thank you very much and sorry for the unnecessary my old replies.
>> Bye
>> Luca
>>
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