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We can make the tests run slightly faster by parallelizing them across multiple CPU cores: - from some casual testing locally, 2 cores gives the optimum speedup - Travis container-based builds have 2 CPU cores available[1] - the net gain is about 20%, or 2 seconds - unfortunately we can’t do this on the API because each test is still using the same instance of the database 1. https://docs.travis-ci.com/user/ci-environment/#Virtualization-environments
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notifications-admin
GOV.UK Notify admin application.
Features of this application
- Register and manage users
- Create and manage services
- Send batch emails and SMS by uploading a CSV
- Show history of notifications
First-time setup
Languages needed
- Python 3
- Node 5.0.0 or greater
brew install node
NPM is Node's package management tool. n is a tool for managing
different versions of Node. The following installs n and uses the latest
version of Node.
npm install -g n
n latest
npm rebuild node-sass
The app runs within a virtual environment. To install virtualenv, run
[sudo] pip install virtualenv
Make a virtual environment for this app:
mkvirtualenv -p /usr/local/bin/python3 notifications-admin
Install dependencies and build the frontend assets:
./scripts/bootstrap.sh
Rebuilding the frontend assets
If you want the front end assets to re-compile on changes, leave this running in a separate terminal from the app
npm run watch
Create a local environment.sh file containing the following:
echo "
export NOTIFY_ADMIN_ENVIRONMENT='config.Development'
export ADMIN_CLIENT_SECRET='dev-notify-secret-key'
export ADMIN_CLIENT_USER_NAME='dev-notify-admin'
export API_HOST_NAME='http://localhost:6011'
export DANGEROUS_SALT='dev-notify-salt'
export SECRET_KEY='dev-notify-secret-key'
export DESKPRO_API_HOST=""
export DESKPRO_API_KEY=""
export DESKPRO_PERSON_EMAIL=""
export DESKPRO_DEPT_ID=""
export DESKPRO_ASSIGNED_AGENT_TEAM_ID=""
"> environment.sh
Running the application
workon notifications-admin
./scripts/run_app.sh
Then visit localhost:6012
Description
Languages
Python
69.3%
HTML
16.6%
JavaScript
11.1%
SCSS
0.9%
Nunjucks
0.7%
Other
1.4%