- It seems that when we changed the name of the job.status column that we didn't update the code to use job.job_status.
- Therefore none of the jobs since then have had the job status updated.
- Now that this is fix we can show the job status when there is an error like "sending exceeds limits"
- This could happen if a job is scheduled to run at the top of the hour, so at the time of the job creation the limit was not exceed, but at the time of processing the job the limit is exceed.
Notifications with a `billable_units` count of `0` wont have any effect
on the result, but including them in the query will slow down the
grouping and summing of the results because it’ll have to loop over more
rows.
April 1st is in British summer time, ie 1hr ahead of UTC. The database
stores everything in UTC, so for accurate comparisions we need to make
sure that `get_financial_year()` returns a UTC, datetime-aware
timestamp that is 1hr ahead of midnight.
This also means that when we group notifications by month, the months
need to be in BST. So the line between one year and another is actually
01:00 on April 1st, _not_ 00:00 on April 1st.
There’s no way we’ve found to do this in SQLAlchemy or raw Postgres,
especially because we don’t store the timestamps with a timezone in the
database.
So the grouping and summing of the notifications has to be done in
Python.
`/services/ef7a665d-11a4-425a-a180-a67ca00b69d7/billable-units?year=2016`
Pretty much just passes through to the DAO layer. Validates that year
is:
- present (there’s no need for unbounded queries on this endpoint)
- an integer
In order to invoice people we need to know how many text message
fragments they’ve sent per month.
This should be per (government) financial year, ie April 1st to April
1st because we’ll only ever show a page for one year (because the
250,000 allowance is topped up at the start of every financial year).
This commit only does the DAO bit, not the REST bit.
Refactored send_notifications method so that it is more readible.
Refectored the test_send_notificaitons so that it uses parametrized test to avoid duplication.
this means normal celery workers WON'T process this queue. Requires a dedicated celery worker to do this.
- note development and test configs add it in so DEV and TEST builds require no change.
