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Previously, when running the `collate_letter_pdfs_for_day` task, we
would only send letters that were created between 5:30pm yesterday and
5:30 today.
Now we send letters that were created before 5:30pm today and that are
still waiting to be sent. This will help us automatically attempt to
send letters that may have fallen through the gaps and not been sent the
previous day when they should have been.
Previously we solved the problem of letters that had fallen the gap by
having to run the task with a date parameter for example
`collate_letter_pdfs_for_day('2020-02-18'). We no longer need this date
parameter as we will always look back across previous days too for
letters that still need sending.
Note, we have to change from using the pagination `list_objects_v2` to
instead getting each individual notification from s3. We reduce load by
using `HEAD` rather than `GET` but this will still greatly increase the
number of API calls. We acknowledge there will be a small cost to this,
say 50p for 5000 letters and think this is tolerable. Boto3 also handles
retries itself so if when making one of the many HEAD requests, there is
a networking blip then it should be retried automatically for us.
GOV.UK Notify API
Contains:
- the public-facing REST API for GOV.UK Notify, which teams can integrate with using our clients
- an internal-only REST API built using Flask to manage services, users, templates, etc (this is what the admin app talks to)
- asynchronous workers built using Celery to put things on queues and read them off to be processed, sent to providers, updated, etc
Setting Up
Python version
At the moment we run Python 3.6 in production. You will run into problems if you try to use Python 3.5 or older, or Python 3.7 or newer.
AWS credentials
To run the API you will need appropriate AWS credentials. You should receive these from whoever administrates your AWS account. Make sure you've got both an access key id and a secret access key.
Your aws credentials should be stored in a folder located at ~/.aws. Follow Amazon's instructions for storing them correctly.
Virtualenv
mkvirtualenv -p /usr/local/bin/python3 notifications-api
environment.sh
Creating the environment.sh file. Replace [unique-to-environment] with your something unique to the environment. Your AWS credentials should be set up for notify-tools (the development/CI AWS account).
Create a local environment.sh file containing the following:
echo "
export NOTIFY_ENVIRONMENT='development'
export MMG_API_KEY='MMG_API_KEY'
export FIRETEXT_API_KEY='FIRETEXT_ACTUAL_KEY'
export NOTIFICATION_QUEUE_PREFIX='YOUR_OWN_PREFIX'
export FLASK_APP=application.py
export FLASK_DEBUG=1
export WERKZEUG_DEBUG_PIN=off
"> environment.sh
NOTES:
- Replace the placeholder key and prefix values as appropriate
- The SECRET_KEY and DANGEROUS_SALT should match those in the notifications-admin app.
- The unique prefix for the queue names prevents clashing with others' queues in shared amazon environment and enables filtering by queue name in the SQS interface.
Postgres
Install Postgres.app. You will need admin on your machine to do this.
Choose the version with Additional Releases - you want 9.6. Once you run the app, open the sidebar, remove the default v11 server and create and initialise a v9.6 server.
Redis
To switch redis on you'll need to install it locally. On a OSX we've used brew for this. To use redis caching you need to switch it on by changing the config for development:
REDIS_ENABLED = True
To run the application
First, run scripts/bootstrap.sh to install dependencies and create the databases.
You need to run the api application and a local celery instance.
There are two run scripts for running all the necessary parts.
scripts/run_app.sh
scripts/run_celery.sh
Optionally you can also run this script to run the scheduled tasks:
scripts/run_celery_beat.sh
To test the application
First, ensure that scripts/bootstrap.sh has been run, as it creates the test database.
Then simply run
make test
That will run flake8 for code analysis and our unit test suite. If you wish to run our functional tests, instructions can be found in the notifications-functional-tests repository.
To update application dependencies
requirements.txt file is generated from the requirements-app.txt in order to pin
versions of all nested dependencies. If requirements-app.txt has been changed (or
we want to update the unpinned nested dependencies) requirements.txt should be
regenerated with
make freeze-requirements
requirements.txt should be committed alongside requirements-app.txt changes.
To run one off tasks
Tasks are run through the flask command - run flask --help for more information. There are two sections we need to
care about: flask db contains alembic migration commands, and flask command contains all of our custom commands. For
example, to purge all dynamically generated functional test data, do the following:
Locally
flask command purge_functional_test_data -u <functional tests user name prefix>
On the server
cf run-task notify-api "flask command purge_functional_test_data -u <functional tests user name prefix>"
All commands and command options have a --help command if you need more information.
To create a new worker app
You need to:
- Create new entries for your app in
manifest.yml.j2andscripts/paas_app_wrapper.sh(example) - Update the jenkins deployment job in the notifications-aws repo (example)
- Add the new worker's log group to the list of logs groups we get alerts about and we ship them to kibana (example)
- Optionally add it to the autoscaler (example)
Important:
Before pushing the deployment change on jenkins, read below about the first time deployment.
First time deployment of your new worker
Our deployment flow requires that the app is present in order to proceed with the deployment.
This means that the first deployment of your app must happen manually.
To do this:
- Ensure your code is backwards compatible
- From the root of this repo run
CF_APP=<APP_NAME> make <cf-space> cf-push
Once this is done, you can push your deployment changes to jenkins to have your app deployed on every deployment.