/2018-PyDash.io

A Flask Web-service for visualising Flask-Monitoring-Dashboards

Primary LanguagePython

PyDash.io

PyDash on Travis

A Flask Web-service for visualising Flask-Monitoring-Dashboards

You can view a live deployment of this repository at pydash.io

Master branch

Use this branch for weekly deadlines

Development branch

Push to this branch as soon as you've implemented a feature.

Installing Dependencies

This app manages its language-version dependencies using the ASDF Version Manager.

More information on how to install this can be found in ./docs/setting-up-virtual-env-using-asdf.md

Running in Development

Side-Note: Seeding the database

Before running your application for the first time (and possibly after a lot of changes have occurred in the development version), you will want to re-seed your application, using:

./build_and_run.sh databasebg seed

Running the application as a whole

In this case, running ./build_and_run.sh is enough. This will install front-end dependencies, build the front-end react application, install back-end dependencies, and then start the back-end (which serves the react app and the API) including the database.

The application can be closed using Ctrl+C.

In the event that the database does not properly close, use killall runzeo.

Running only the Flask Back-End+Database

./build_and_run.sh databasebg backend

Building the React.js Front-End

./build_and_run.sh build

Running the React.js Front-End separately for a quick feedback-loop

Ensure that the Flask back-end+database is running using above steps.

In one shell: ./build_and_run.sh databasebg server

In another:

./build_and_run.sh frontend

Testing

Tests are written using pytest, with a couple of plugins:

  • pytest-xdist is used to spread test running over all available CPU cores.
  • pytest-random-order is used to randomize the order tests are run in, to prevent unwanted coupling between tests.
  • pytest-cov is used to show code-line coverage of a test run.
  • pytest-bdd is used to write feature (integration) tests using the Gherkin specification language.
  • pytest-splinter is used to run the feature (integration) tests using an automated browser.
  • pytest-flask and pytest-localserver are used to server the Flask-app during testing to the automated browser.

Running all tests

Tests as a whole can be run by:

./build_and_run.sh test

To do this manually:

  1. move into the pydash folder
  2. Setup your virtual environment using ./start_pipenv.sh.
  3. Run pytest.

Do note that for the integration tests, you will need the chromedriver binary (that can be found in your OS distribution's package manager).

You might also need to install development dependencies. This is done by running cd pydash && pipenv install --dev && cd ..

Running only back-end unit tests

Follow the manual steps as above, but instead of pytest, run pytest -k "not features"

Running only feature tests

Follow the manual steps as above, but instead of pytest, run pytest -k "features"

Running tests iteratively during development

Follow the manual steps as above, but instead of pytest, run pytest -f