I prefer to avoid `assert_not_called`, because if I make a typo like
this, the tests will still pass:
```
app.invite_api_client.create_invite.asset_not_called()
```
It’s harder to have a false positive with the statement written this
way:
```
assert app.invite_api_client.create_invite.called is False
```
We don’t want to muddy them up with the normal CSV uploads.
I’ve tried to reuse the existing S3 code where possible because it’s
well tested.
Buckets have already been created.
Now persisting the address to the "to" field of the Notification, after the notification has been validated.
If the letter is pending validation, then "Checking..." will appear as the identifier for the letter.
If the letter has passed validation, then the first line of the address (now persisted in the "to" field) will be displayed, with the client reference underneath.
If the letter has failed validation the "Provided as PDF" will show be displayed, which is now the initial value of the "to" field.
The recipient of the letter now displays at the bottom of the page when
previewing a valid letter. The template preview `/precompiled/sanitise`
endpoint returns the address, but we format it to display on a single
line with commas between each line. We also need to convert the
recipient address to ASCII so that it can be stored as S3 metadata.
We had been storing whether or not a file was valid in the S3 metadata,
but using the query string of the URL to store the original filename
and the page count. This meant that if you tried to view the preview
letter page without the query string you would see a `500`. It was
possible for this to happen if you were signed out of Notify while on
the preview page - you would be redirected back to the preview page but
without the query string, causing an error.
This sanitises uploaded letters and stores the sanitised result in S3
with if it passes validation or the original PDF in S3 if validation
fails. A metadata value of 'status' is set to either 'valid' or
'invalid'.
This has a form with 3 fields - the file upload field, logo name, and an
optional logo domain. Logos need to be uploaded in `.svg` format and we
then convert this to `.png` format and upload both file types to S3 as
well as saving the letter branding details in the database.
Some of the tests were calling methods that didn't exist on MagicMock
objects, which meant that they were always passing. For example, tests
using the format of MagicMock.called_once_with(...) were always passing
since a MagicMock does not have the method `called_once_with`. Changing
this to `assert_called_once_with` ensures that the tests fail if they're
called with the wrong arguments.
Separated s3_client.py into 3 files - for logos, CSV files and the MOU.
This helps to keep things clearer now that we need to add lots more logo
functions for letters.
