Profiling has shown that there are many calls to sqlite3.execute and
fetchone which takes a signicant amount of time. A simple way of
reducing these is to swap the 2-stage init of table row data into a
unified add.
Applying this to add_set and add_country yielded these results:
Before changes
```
281784 7.054 0.000 7.054 0.000 {method 'execute' of 'sqlite3.Cursor' objects}
127443 1.114 0.000 1.114 0.000 {method 'fetchone' of 'sqlite3.Cursor' objects}
```
After changes
```
281714 7.492 0.000 7.492 0.000 {method 'execute' of 'sqlite3.Cursor' objects}
127373 1.217 0.000 1.217 0.000 {method 'fetchone' of 'sqlite3.Cursor' objects}
```
Note: The total time of fetchone has actually increased. I am hoping
this was an abnormality on my machine and the actual reduction in the
number of calls will permantly reduce this total time.
* Added profiling info
* Resort to the expensive database lookup only if the person exists in the
database.
* Prevent any access to the people database unless a person must be added.
* Bulk operations where possible.
* Prepare for a new install and the table not existing.
implementation dependant although with CPython elements are
unintentionally skipped during iteration.
Basic CPython example:
>>> A = [1,2,3,4,5,6]
>>> for a in A:
... A.remove(a)
>>> A
[2, 4, 6]
