Tasks will fail if we leave the kwarg in, so I think it's quite
important that we test this works. We don't cover this in any other
test because we call the task functions directly, so the request_id
kwarg doesn't get injected beforehand.
This requires upgrading freezegun, as time.monotonic wasn't frozen
by v1.0. Note that we need to explicitly specify the base class for
the task in the test, the reason for which is quite subtle:
- Normally, by using the 'notify_api' fixture, the base class is set
to NotifyTask automatically by running app.create_app [1].
- However, when run alongside other tests, the imports of files with
other celery tasks cause the base class to be instantiated and cached
as the default Celery one. This means none of our tests actually use
our custom superclass when testing tasks.
Because we can't run 'apply_async' directly (since this would require
an actual Celery broker), we need to manually push/pop the request
Context that's normally done as part of sending a task.
Note also that we use a UUID as the name for a task, since these are
global. We want to avoid the task polluting other tests in future,
as well as make it clear the task is being reused.
[1]: dea5828d0e/app/__init__.py (L113)
Previously we used a '@statsd' decorator to time and count Celery
tasks [1]. Using a decorator isn't ideal since we need to remember
to add it to every task we define. In addition, it's not possible
to use data like the task name and queue.
In order to avoid breaking existing stats, this duplicates them as
new StatsD metrics until we have sufficient data to update dashboards
using the old ones. Using the CeleryTask superclass to send metrics
avoids a future maintenance overhead, and means we can include more
useful data in the StatsD metric. Note that the new metrics will sit
in StatsD until we add a mapping for them [2].
StatsD automatically produces a 'count' stat for timing metrics, so
we don't need to increment a separate counter for successful tasks.
[1]: dea5828d0e/app/celery/tasks.py (L65)
[2]: https://github.com/alphagov/notifications-aws/blob/master/paas/statsd/statsd-mapping.yml
This is mainly so we can use it in the new metrics we send to StatsD
in the following commits, but it should also be useful in the logs.
I've taken the opportunity to make the log format consistent between
success / failure, and with our Template Preview app [1].
[1]: f456433a5a/app/celery/celery.py (L19)
it's important to keep tabs on when these things leave our system.
Sending a zendesk ticket that triggers a P1 is probably our simplest way
of notifying the team when this happens (it's what we do with out of
hours emergencies on the admin app too). We don't have any direct
pagerduty integrations from the api app, but we already have the zendesk
client hooked up.
After broadcasts go live, we may want to change this to a P2 (but even
then, there's arguments for keeping it P1 to start with I think).
Don't cause a P1 if it goes out on staging as that might be MNOs testing.
Now that https://github.com/alphagov/notifications-api/pull/3184 has
been deployed for a while, the `send_delivery_status_to_service` task will
always have `template_id` and `template_version` being passed in. This
means we don't need to check if those fields are there.
April 1 2021.
In this PR there is a command to set annual_billing for all active
services with the the new defaults.
The new method `set_default_free_allowance_for_service` will also be
called in a PR to follow that will set a services free allowance to the
default if the organisation for the service is changed.
for the service.
The letters rates for cronw and non crown are the same. It would be nice
to remove the need for crown but for now this is a quick fix.
This is mostly useful for letters.
For templated letters sent via interface, whether one-offs
or CSV uploads, we do not give our users a way to set client reference.
Still, they often have a placeholder with reference that we could use
to set client_reference field.
Why is this helpful?
When letter is returned, or when we experience some printing issues,
often it is difficult to identify letters after the retention period.
This change will make it easier for some users to identify letters.
It will have more impact if we inform our users of this in template
editing guidance.
This adds the `template_id` and `template_version` fields to the data
sent to services from the `send_delivery_status_to_service` task.
We need to account for the task not being passed these fields at first
since there might be tasks retrying which don't have that data. Once all
tasks have been called with the new fields we can then update the code
to assume they are always there.
Since we only send delivery status callbacks for SMS and emails, I've
removed the tests where we call that task with letters.
Names of services and orgs were confusing, and variable setting
was done in a way that made it easy to introduce errors.
Now hopefully it is more readable and more error-proof.
This is not required by DVLA and since [1] we no longer care about
the end of letter filenames when collating them, so removing it is
safe to do. Note that the name of the ZIP files of collated letters
is based on a hash of the filenames, which needed updating in tests.
Before merging this we need to do a test run in Staging, so DVLA can
check that a mixture of the old / new filenames won't cause issues.
[1]: https://github.com/alphagov/notifications-api/pull/3172
We have a scheduled task that was checking for jobs still in progress.
We saw a case where a scheduled job was stuck in a `pending` status as a
result of an app shutting down. This changes the `check_job_status` task
so that it also checks for scheduled jobs which are still pending after
30 minutes.
Previously we did some unnecessary work:
- Collate task. This had one S3 request to get a summary of the object,
which was then used in another request to get the full object. We only
need the size of the object, which is included in the summary [1].
- Archive task. This had one S3 request to get a summary of the object,
which was then used to make another request to delete it. We still need
both requests, but we can remove the S3.Object in the middle.
[1]: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#objectsummary
Previously we made a call to S3 to list objects for a letter, even
though we already had the precise key of the single object to hand.
This removes the one usage of "get_s3_bucket_objects" and uses the
filename directly in the call to remove the object.
Previously, the function would just return a presumed filename. Now that
it actually checks s3, if the file doesn't exist it'll raise an
exception. By default that's a StopIteration at the end of the bucket
iterator, which isn't ideal as this will get supressed if the function
is called within a generator loop further up or anything.
There are a couple of places where we expect the file may not exist, so
we define a custom exception to rescue specifically here. I did consider
subclassing boto's ClientError, but this wasn't straightforward as the
constructor expects to know the operation that failed, which for me is a
signal that it's not an appropriate (re-)use of the class.
Previously we generated the filename we expected a letter PDF to be
stored at in S3, and used that to retrieve it. However, the generated
filename can change over the course of a notification's lifetime e.g.
if the service changes from crown ('.C.') to non-crown ('.N.').
The prefix of the filename is stable: it's based on properties of the
notification - reference and creation - that don't change. This commit
changes the way we interact with letter PDFs in S3:
- Uploading uses the original method to generate the full file name.
The method is renamed to 'generate_' to distinguish it from the new one.
- Downloading uses a new 'find_' method to get the filename using just
its prefix, which makes it agnostic to changes in the filename suffix.
Making this change helps to decouple our code from the requirements DVLA
have on the filenames. While it means more traffic to S3, we rely on S3
in any case to download the files. From experience, we know S3 is highly
reliable and performant, so don't anticipate any issues.
In the tests we favour using moto to mock S3, so that the behaviour is
realistic. There are a couple of places where we just mock the method,
since what it returns isn't important for the test.
Note that, since the new method requires a notification object, we need
to change a query in one place, the columns of which were only selected
to appease the original method to generate a filename.
