From 7daa9e1d6a0bddf46cbd47115b5f5a4ef56ce478 Mon Sep 17 00:00:00 2001 From: Mike Bayer Date: Sun, 24 Sep 2006 20:51:53 +0000 Subject: [PATCH] spelling fix --- doc/build/content/adv_datamapping.txt | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/doc/build/content/adv_datamapping.txt b/doc/build/content/adv_datamapping.txt index 6ce0dd6dd2..f1afd5c6ee 100644 --- a/doc/build/content/adv_datamapping.txt +++ b/doc/build/content/adv_datamapping.txt @@ -153,7 +153,7 @@ When creating relations on a mapper, most examples so far have illustrated the m mapper(Address, addresses_table) mapper(User, users_table, properties={ - 'boston_addreses' : relation(Address, primaryjoin= + 'boston_addresses' : relation(Address, primaryjoin= and_(users_table.c.user_id==Address.c.user_id, Addresses.c.city=='Boston')) }) @@ -179,7 +179,7 @@ The previous example leads in to the idea of joining against the same table mult {python} mapper(User, users_table, properties={ - 'boston_addreses' : relation(Address, primaryjoin= + 'boston_addresses' : relation(Address, primaryjoin= and_(users_table.c.user_id==Address.c.user_id, Addresses.c.city=='Boston')), 'newyork_addresses' : relation(Address, primaryjoin= @@ -349,7 +349,7 @@ An example of a mapper with a lazy load relationship, upgraded to an eager load # a 'lazy' relationship mapper(User, users_table, properties = { - 'addreses':relation(mapper(Address, addresses_table), lazy=True) + 'addresses':relation(mapper(Address, addresses_table), lazy=True) }) # copy the mapper and convert 'addresses' to be eager -- 2.47.2