Python performance: search large list vs sqlite -


Let me have a database table that has three columns: id , field1

and field 2 . There can be anywhere between 100 and 100,000 rows in this table. I have a dragon script that includes 10-1000 new lines in this table. However, if the new field1 already exists in the table, then it should not be UPDATE , INSERT .

Which of the following approaches is more efficient?

  1. Select SELECT field 1 ( field 1 is unique) from the table and store it in that list. Then, for each new row, use list.count () , to determine whether INSERT or UPDATE
  2. For each line, run two questions First, from the SELECT number (*) to the table WHERE field 1 = "foo" then either INSERT or < Code> UPDATE .

In other words, is it more efficient to execute the n + 1 questions and get the list, or the sequence to find and search 2n questions?

Assume that there is a unique hurdle on field 1, you can do simple access:

  Enter or change the table values ​​(...)  

The following syntax is also supported (similar semantics):

Edit: I realize that I really want to answer your question. I'm not giving up, I'm just providing an alternative solution that should be fast. / P>


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