10/18/2023 0 Comments Sqlight insert if doesnt already exist![]() ![]() So I can see why someone might think they need to know the pseudokey, but they are incorrect. Seems to me that there is no need to EVER deal with the pseudokeys. (select house_id from houses where address = new.address) Select (select name_id from names where name = new.name), Insert or ignore into houses (address) select new.address where new.address is not null Insert or ignore into names (name) values (new.name) ![]() Select raise(ABORT, 'Name cannot be NULL') where new.name is null Where (peasants.name_id is null or peasants.name_id = names.name_id)Īnd (peasants.house_id is null or peasants.house_id = houses.house_id) Ĭreate trigger ins_person instead of insert into persons create table namesĪddress text not null collate nocase unique It is actually not needed for anything at all. ![]() It also does not really matter what some excrement-head thinks "after the fact" - they can either accept the answer "I don't know" (which by the way is an incorrect answer - the correct answer would be "that information was not recorded").Īnd going back to the post to which you replied, it only appears to the uneducated that there is a need to know the pseudokey for the row. If you are trying to insert/update a player whose ID already exists, the SQLite engine will delete that row and insert the. In other words, you don't have foreign key, or if you have them, your SQLite engine is configured so that there no are integrity exceptions. Playing with pseudokeys will not be helpful in this regard. Option 1: You can afford deleting the row. Unless the inserted record contains a timestamp of when it was inserted, there is no way to tell when the record was inserted. Filter out those rows from df0 and df2, whose corresponding combinedcolumn does not. combinedcolumn, and save this into a list combinedcolumnlist. Well, that is a design flaw (failure to store needed information) and has nothing whatsoever to do with the question asked. There are two ways: if the data from database is not big, read the data from database into the dataframe, and combine the two columns (Col1 and Col2) to create a new column, i.e. ![]()
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