Install Docker for your system. Make sure that you've installed both docker and docker-compose packages, preferably using Homebrew:
brew install docker
brew install docker-compose
On MacOS install container runtimes, eg. Colima:
brew install colima
Make sure Colima is started every time you want to use Docker images:
colima start
To get eq-questionnaire-runner running the following command will build and run the containers
RUNNER_ENV_FILE=.development.env docker compose up -d
To launch a survey, navigate to http://localhost:8000/
When the containers are running you are able to access the application as normal, and code changes will be reflected in the running application. However, any new dependencies that are added would require a re-build.
To rebuild the eq-questionnaire-runner container, the following command can be used.
RUNNER_ENV_FILE=.development.env docker compose build
If you need to rebuild the container from scratch to re-load any dependencies then you can run the following
RUNNER_ENV_FILE=.development.env docker compose build --no-cache
git clone git@github.com:ONSdigital/eq-questionnaire-runner.git
In order to run locally you'll need Node.js, snappy, pyenv, jq and wkhtmltopdf installed
brew install snappy npm pyenv jq wkhtmltopdf
Create .application-version
for local development
This file is automatically created and populated with the git revision id during CI for anything other than development,
but the file is absent when the repo is first cloned and is required for running the app locally. Setting the contents
to local
removes the implication that any particular revision is used when run locally.
echo "local" > .application-version
It is preferable to use the version of Python locally that matches that
used on deployment. This project has a .python_version
file for this
purpose.
It is recommended to install the pyenv
Python version management tool to easily switch between Python versions.
To install pyenv
use this command:
curl https://pyenv.run | bash
After the installation it should tell you to execute a command to add pyenv
to path. It should look something like this:
export PYENV_ROOT="$HOME/.pyenv"
command -v pyenv >/dev/null || export PATH="$PYENV_ROOT/bin:$PATH"
eval "$(pyenv init -)"
Python versions can be changed with the pyenv local
or pyenv global
commands suffixed with the desired version (e.g. 3.12.6). Different versions of Python can be installed first with the pyenv install
command. Refer to the pyenv project Readme here. To avoid confusion, check the current Python version at any given time using python --version
or python3 --version
.
Inside the project directory install python version, upgrade pip:
pyenv install
pip install --upgrade pip setuptools
Install poetry, poetry dotenv plugin and install dependencies:
curl -sSL https://install.python-poetry.org | python3 - --version 1.8.4
poetry self add poetry-plugin-dotenv
poetry install
We use poetry-plugin-up to update dependencies in the pyproject.toml
file:
poetry self add poetry-plugin-up
To update the design system templates run:
make load-design-system-templates
To download the latest schemas from the Questionnaire Registry:
make load-schemas
Run the server inside the virtual env created by Poetry with:
make run
Runner requires five supporting services - a questionnaire launcher, a storage backend, a cache, the supplementary data service and the collection instrument registry.
To run the app locally, but the supporting services in Docker, make sure you have Docker and Colima installed from this step, then run:
make dev-compose-up
Note that on Linux you will need to use:
make dev-compose-up-linux
docker run -e SURVEY_RUNNER_SCHEMA_URL=http://host.docker.internal:5000 -e SDS_API_BASE_URL=http://host.docker.internal:5003 -e CIR_API_BASE_URL=http://host.docker.internal:5004 -it -p 8000:8000 onsdigital/eq-questionnaire-launcher:latest
docker run -it -p 5003:5003 onsdigital/eq-runner-mock-sds:latest
docker run -it -p 5004:5004 onsdigital/eq-runner-mock-cir:latest
docker run -it -p 6060:8000 onsdigital/eq-docker-dynamodb:latest
or
docker run -it -p 8432:8432 knarz/datastore-emulator:latest
docker run -it -p 6379:6379 redis:4
To use EQ_STORAGE_BACKEND
as datastore
or EQ_SUBMISSION_BACKEND
as gcs
directly on GCP and not a docker image, you need to set the GCP project using the following command:
gcloud config set project <gcp_project_id>
Or set the GOOGLE_CLOUD_PROJECT
environment variable to your gcp project id.
There is a dev-convenience script that auto generates the lines of code for a user journey. See README for more information and how to run the script.
The frontend tests use NodeJS to run. To handle different versions of NodeJS it is recommended to install Node Version Manager
(nvm
). It is similar to pyenv but for Node versions.
To install nvm
use the command below (make sure to replace "v0.39.5" with the current latest version in releases:
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash
You will need to have the correct node version installed to run the tests. To do this, use the following commands:
nvm install
nvm use
Fetch npm dependencies:
npm install
Available commands:
Command | Task |
---|---|
make test-functional |
Runs the functional tests through Webdriver (requires app running on localhost:5000 and generated pages). |
make generate-pages |
Generates the functional test pages. |
make lint-js |
Lints the JS, reporting errors/warnings. |
make format-js |
Format the json schemas. |
The tests are written using WebdriverIO, Chai, and Mocha
The functional tests use a set of selectors that are generated from each of the test schemas. These make it quick to add new functional tests.
To run the functional tests first runner needs to be spin up with:
RUNNER_ENV_FILE=.functional-tests.env make run
This will set the correct environment variables for running the functional tests.
Then you can run either:
make test-functional
or
make test-functional-headless
This will delete the tests/functional/generated_pages
directory and regenerate all the files in it from the schemas.
To generate the pages manually you can run the generate_pages
scripts with the schema directory. Run it from the tests/functional
directory as follows:
./generate_pages.py ../../schemas/test/en/ ./generated_pages -r "../../base_pages"
To generate a spec file with the imports included, you can pass the schema name as an argument without the file extension, e.g. SCHEMA=test_address
:
make generate-spec SCHEMA=<schema-name>
If you have already built the generated pages, then the functional tests can be executed with:
make test-functional
This can be limited to a single spec where argument needed is the remainder of the path after ./tests/functional/spec/
(which is included in the command):
make test-functional-spec SPEC=<spec>
To run a single test, add .only
into the name of any describe
or it
function:
describe.only('Skip Conditions', function() {...}
or
it.only('Given this is a test', function() {...}
Test suites are configured in the wdio.conf.js
file.
An individual test suite can be run using the suite names as the argument to this command. The suites that can be used with command below are:
- timeout_modal_expired
- timeout_modal_extended
- timeout_modal_extended_new_window
- features
- general
- components
make test-functional-suite SUITE=<suite>
To run the tests against a remote deployment you will need to specify the environment variable of EQ_FUNCTIONAL_TEST_ENV eg:
EQ_FUNCTIONAL_TEST_ENV=https://staging-new-surveys.dev.eq.ons.digital/ npm run test_functional
For deploying with Concourse see the CI README.
Deployment with gcloud
To deploy this application with gcloud, you must be logged in using gcloud auth login
and gcloud auth application-default login
.
When deploying with gcloud the environment variables specified in Deploying the app must be set.
Then call the following command with environment variables set:
./ci/deploy_app.sh
Before deploying the app to GCP you need to create the application credentials. Run the following command to provision the credentials:
PROJECT_ID=PROJECT_ID EQ_KEYS_FILE=PATH_TO_KEYS_FILE EQ_SECRETS_FILE=PATH_TO_SECRETS_FILE ./ci/deploy_credentials.sh
For example:
PROJECT_ID=eq-test EQ_KEYS_FILE=dev-keys.yml EQ_SECRETS_FILE=dev-secrets.yml ./ci/deploy_credentials.sh
The following environment variables must be set when deploying the app.
Variable Name | Description |
---|---|
PROJECT_ID | The ID of the GCP target project |
DOCKER_REGISTRY | The FQDN of the target Docker registry |
IMAGE_TAG |
The following environment variables are optional:
Variable Name | Default | Description |
---|---|---|
REGION | europe-west2 | The region that will be used for your Cloud Run service |
CONCURRENCY | 80 | The maximum number of requests that can be processed simultaneously by a given container instance |
MIN_INSTANCES | 1 | The minimum number of container instances that can be used for your Cloud Run service |
MAX_INSTANCES | 1 | The maximum number of container instances that can be used for your Cloud Run service |
CPU | 4 | The number of CPUs to allocate for each Cloud Run container instance |
MEMORY | 4G | The amount of memory to allocate for each Cloud Run container instance |
GOOGLE_TAG_ID | The Google Tag ID - Specifies the GTM account | |
WEB_SERVER_TYPE | gunicorn-threads | Web server type used to run the application. This also determines the worker class which can be async/threaded |
WEB_SERVER_WORKERS | 7 | The number of worker processes |
WEB_SERVER_THREADS | 10 | The number of worker threads per worker |
WEB_SERVER_UWSGI_ASYNC_CORES | 10 | The number of cores to initialise when using "uwsgi-async" web server worker type |
DATASTORE_USE_GRPC | False | Determines whether to use gRPC for Datastore. gRPC is currently only supported for threaded web servers |
To deploy the app, run the following command:
./ci/deploy_app.sh
We use flask-babel to do internationalisation. To extract messages from source and create the messages.pot file, in the project root run the following command.
make translation-templates
make translation-templates
is a command that uses pybabel to extract static messages.
This will extract messages and place them in the .pot files ready for translation.
These .pot files will then need to be translated. The translation process is documented in Confluence here
Once we have the translated .po files they can be added to the source code and used by the application
The following env variables can be used
Variable Name | Default | Description |
---|---|---|
EQ_SESSION_TIMEOUT_SECONDS | 2700 (45 mins) | The duration of the flask session |
EQ_PROFILING | False | Enables or disables profiling (True/False) Default False/Disabled |
EQ_GOOGLE_TAG_ID | The Google Tag Manger ID - Specifies the GTM account | |
EQ_ENABLE_HTML_MINIFY | True | Enable minification of html |
EQ_ENABLE_SECURE_SESSION_COOKIE | True | Set secure session cookies |
EQ_MAX_HTTP_POST_CONTENT_LENGTH | 65536 | The maximum http post content length that the system wil accept |
EQ_MINIMIZE_ASSETS | True | Should JS and CSS be minimized |
MAX_CONTENT_LENGTH | 65536 | max request payload size in bytes |
EQ_APPLICATION_VERSION_PATH | .application-version | the location of a file containing the application version number |
EQ_ENABLE_LIVE_RELOAD | False | Enable livereload of browser when scripts, styles or templates are updated |
EQ_SECRETS_FILE | secrets.yml | The location of the secrets file |
EQ_KEYS_FILE | keys.yml | The location of the keys file |
EQ_SUBMISSION_BACKEND | Which submission backend to use ( gcs, rabbitmq, log ) | |
EQ_GCS_SUBMISSION_BUCKET_ID | The bucket name in GCP to store the submissions in | |
EQ_GCS_FEEDBACK_BUCKET_ID | The bucket name in GCP to store the feedback in | |
EQ_RABBITMQ_HOST | ||
EQ_RABBITMQ_HOST_SECONDARY | ||
EQ_RABBITMQ_PORT | 5672 | |
EQ_RABBITMQ_QUEUE_NAME | submit_q | The name of the submission queue |
EQ_SERVER_SIDE_STORAGE_USER_ID_ITERATIONS | 10000 | |
EQ_STORAGE_BACKEND | datastore | |
EQ_DYNAMODB_ENDPOINT | ||
EQ_REDIS_HOST | Hostname of Redis instance used for ephemeral storage | |
EQ_REDIS_PORT | Port number of Redis instance used for ephemeral storage | |
EQ_DYNAMODB_MAX_RETRIES | 5 | |
EQ_DYNAMODB_MAX_POOL_CONNECTIONS | 30 | |
EQ_QUESTIONNAIRE_STATE_TABLE_NAME | ||
EQ_SESSION_TABLE_NAME | ||
EQ_USED_JTI_CLAIM_TABLE_NAME | ||
WEB_SERVER_TYPE | Web server type used to run the application. This also determines the worker class which can be async/threaded | |
WEB_SERVER_WORKERS | The number of worker processes | |
WEB_SERVER_THREADS | The number of worker threads per worker | |
WEB_SERVER_UWSGI_ASYNC_CORES | The number of cores to initialise when using "uwsgi-async" web server worker type | |
DATASTORE_USE_GRPC | False | Determines whether to use gRPC for Datastore. gRPC is currently only supported for threaded web servers |
ACCOUNT_SERVICE_BASE_URL | https://surveys.ons.gov.uk |
The base URL of the account service used to launch the survey |
ONS_URL | https://www.ons.gov.uk |
The URL of the ONS website where static content is sourced, e.g. accessibility info |
SDS_API_BASE_URL | The base URL of the SDS API used for fetching supplementary data | |
CIR_API_BASE_URL | The base URL of the CIR API used for fetching collection instruments | |
OIDC_TOKEN_BACKEND | gcp | The backend to use when fetching the Open ID Connect token |
OIDC_TOKEN_LEEWAY_IN_SECONDS | 300 | The leeway to use when validating OIDC tokens |
SDS_OAUTH2_CLIENT_ID | The OAuth2 Client ID used when setting up IAP on the SDS | |
CIR_OAUTH2_CLIENT_ID | The OAuth2 Client ID used when setting up IAP on the CIR |
The following env variables can be used when running tests
EQ_FUNCTIONAL_TEST_ENV - the pre-configured environment [local, docker, preprod] or the url of the environment that should be targeted
Integration with the survey runner requires the use of a signed JWT using public and private key pair (see https://jwt.io, https://tools.ietf.org/html/rfc7519, https://tools.ietf.org/html/rfc7515).
Once signed the JWT must be encrypted using JWE (see https://tools.ietf.org/html/rfc7516).
The JWT payload must contain the following claims:
- exp - expiration time
- iat - issued at time
The header of the JWT must include the following:
- alg - the signing algorithm (must be RS256)
- type - the token type (must be JWT)
- kid - key identification (must be EDCRRM)
The JOSE header of the final JWE must include:
- alg - the key encryption algorithm (must be RSA-OAEP)
- enc - the key encryption encoding (must be A256GCM)
To access the application you must provide a valid JWT. To do this browse to the /session url and append a token parameter. This parameter must be set to a valid JWE encrypted JWT token. Only encrypted tokens are allowed.
There is a python script for generating tokens for use in development, to run:
python token_generator.py
Refer to our profiling document.
To add a new dependency, use:
poetry add [package-name]
This will add the required packages to your pyproject.toml and install them
To update a dependency, use:
poetry update [package-name]
This will resolve the required dependencies of the project and write the exact versions into poetry.lock
Using the poetry up plugin we can update dependencies and bump their versions in the pyproject.toml file
To update dependencies to the latest compatible version with respect to their version constraints specified in the pyproject.toml file:
poetry up
To update dependencies to their latest compatible version:
poetry up --latest
NB: both the pyproject.toml and poetry.lock files are required in source control to accurately pin dependencies.
To add a new dependency, use npm install [dev dependency] --save-dev
or npm install [dependency]
then use npm install
to install all the packages locally.
On Design System Repo
Checkout branch with new changes on
You will need to install the Design System dependencies. If you haven't installed Yarn, install it with npm i -g yarn
. To install the dependencies run yarn
in the terminal. If you haven't
you will also need to install gulp.
Then in the terminal run:
yarn cdn-bundle
cd build
browser-sync start --cwd -s --http --port 5678
You should now see output indicating that files are being served from localhost:5678
. So main.css for example will now be served on http://localhost:5678//css/main.css
Now switch to the eQ Questionnaire Runner Repo
In a separate terminal window/tab: Checkout the runner branch you want to test on
Edit your .development.env with following:
CDN_URL=http://localhost:5678
CDN_ASSETS_PATH=
Edit the Makefile to remove load-design-system-templates
from the build command. Should now look like this:
build: load-schemas translate
Run make load-design-system-templates
in the terminal to make sure you have the Design System templates loaded
Then edit the first line in the templates/layout/_template.njk
file to remove the version number. Should now look like this:
{% set release_version = '' %}
Then spin up launcher and runner with make dev-compose-up
and make run
Now when navigating to localhost:8000 and launching a schema, this will now be using the local cdn with the changes from the Design System branch