We already filter the usage-by-month query by financial year. When we
show the total usage for a service, we should be able to filter this
by financial year.
Then, when the two lots of data are put side by side, it all adds up.
This meant that the research mode task would never work.
Also the way we mark data as "temporary-failure" with firetext is with first a pending status callback then a declined callback.
This PR changes the research mode task to account for that situation.
Right now we strip HTML from templates at the point of saving them. This
also converts stuff like ampersands to their entity form (eg &) and
this is what we save in the database.
This is a bad idea when you’re sending a text message or a letter, in
which an HTML entity makes no sense. But we still need to encode HTML in
the body of HTML emails.
The right place to do this is when rendering the templates. The code to
do this is now in utils. So this commit:
- pull in this new utils code
- removes the old
- adds some integration tests to make sure that everything is working
as expected (more thorough unit tests are happening in utils)
We are using the notify queue in this iteration because that queue is a low volume queue with it's own dedicated workers. This just saves us from building a new queue at this point, and a new queue may not be necessary.
- Added the `simulate` notification logic to version 2. We have 3 email addresses and phone numbers that are used
to simulate a successful post to /notifications. This was missed out of the version 2 endpoint.
- Added a test to template_dao to check for the default value of normal for new templates
- in v2 get_notifications, casted the path param to a uuid, if not uuid abort(404)
We’ve seen quite a few developers encounter the `Invalid token: expired`
error message when they’re getting started using the Notify API. When
this happens they either raise a support ticket or ask for help on
Slack.
In every case this has been because the clock on their
machine/environment/container isn’t accurate. The error message doesn’t
help them figure this out.
This commit adds extra detail to the error message so they can fix the
problem without having to come to us for help.
If the template is marked as priority the notification will be sent using the `notify` queue.
The `notify` queue is a low volume queue, messages here will not be queue behind a large job and should be delivered with in a more consistent time frame.
- Added templates.process_type and templates_history.process_type column.
- Added a template_process_type table to handle the enum for templates.process_type, initial values are normal and priority
https://www.pivotaltracker.com/story/show/135429147
while it's nice to use the decorator to signify fixtures with side
effects, it has unfortunate problems of completely overriding any
fixtures you've declared in the funcargs - so isn't really suitable
for our usecase where we often have other fixtures we rely on to
return values to us.
So for consistency, let's remove this and stick to using funcargs
to define our fixtures
when you invoke the fixture `sample_user`, it does two things: it
creates the user in the database, but also returns the user, a useful
object that you may want to manipulate or reference in your test.
however, when you invoke the fixture `notify_db_session`, it doesn't
do anything - rather, it *promises* to clear up the database tables
at the end of the test run.
because we have no need of the notify_db_session object in our tests
(indeed, for a long time this fixture just returned `None`), using
`pytest.mark.usefixtures('notify_db_session')` brings attention to the
fact that this is a side-effect fixture rather than a data setup
fixture. Functionally it is identical to passing as a parameter
note that all of these tests have to be checked to ensure that they
still call through to notify_db_session (notify_db not required) to
tear down the database after the test runs - since it's no longer
required to pass it in to the function just to invoke the sample_user
function
this create_user function can be imported for use in creating specific
users in your tests, for example
```
from tests.app.db import create_user
def test_create_user_persists_to_database(notify_db_session):
user = create_user()
assert User.query.count() == 1
```
this has the benefit of not requiring you to pass the notify_db and
notify_db_session fixtures around, and separating custom object
creation from the fixture dependency trees to aid clarity
I started with sample_user since it has no downstream dependencies, but
the intention is to push this out to all db fixtures eventually. This
is a total conversion, but can be rolled out in a non-breaking manner
by keeping arguments in the fixture, and passing them through to the
new db function - then tests can be updated to use the create_* instead
of sample_* functions as and when you want to
