Scene coding challenge

A technical interview challenge for python developers.

This live-coding challenge is as much about demonstrating the process as it is about the end-result.

Getting started

You will need:

• git
• python (^3.11)
• poetry (pipx install poetry is easiest)

You should be able to clone this repository, and setup a virtual environment using poetry:

poetry install
poetry shell

Copy the example environment file:

cp .env.example .env

Running the Django server

From a shell within the poetry virtual environment:

python manage.py runserver

You can access the documentation at: http://localhost:8000/docs/

The basic api Django app does not use authentication. You can try out the existing /api/home/{uprn} endpoint with UPRN: 906205784. This will return a HomeDetailsResponse object with details of the property.

For the challenge we're not actually using a database, so the APIs will only fetch hard-coded data. No other UPRNs will work with this endpoint.

Challenge

1. Add a simple "UI" prototype for a chart, comparing monthly energy usage before and after a set of home improvements.

   • Use the tools you think get you the best results the quickest.
     • This could be a single-page-application framework, or just HTML with a Django view using CDN assets.
     • If you do not have a preferred JavaScript charting library, try ChartJS.
   • You can choose whatever chart style you feel is most appropriate.
   • You don't need to consider aesthetics, just make the chart understandable.
   • You do not need to consider security, access controls, or other usual best-practices for this challenge. Treat it as an internal prototyping exercise.

2. You should add an endpoint to the python_challenge.api.views to supply the data for the chart.

   • We have provided a utility function python_challenge.utils.get_results which fetches a RetrofitPlannerResponsePublic object.
     • This object contains all the data you will need (and more, see the notes below about what data to use).
     • You can use the UUID 1e0e7511-9e40-4b13-8c52-4f9c26c41c55 which has baseline and improved simulation results for UPRN 906205784.
   • You should format the data into whatever structure your chart requires, in python.

RetrofitPlannerResponsePublic

The RetrofitPlannerResponsePublic has a lot of data, but for this challenge the two fields you need are:

• $.baseline_energy_profile.monthly_energy_total
• $.improvement_plan.energy_profile.monthly_energy_total

These are both dict[MonthNumber, EnergyConsumptionSummary], and have an energy sub-field with the total household energy consumption for the month, in kWh.

The chart needs to compare these two data series. You should choose how best to display the data.

Notes

python_challenge/types/

Do not change or add any code to python_challenge/types/. This is a collection of type definitions copied over from one of our packages. Treat it as an external dependency.

Linting

We have included several python linter tools we use: black, isort, ruff, pyright. These are configured to be run with pre-commit and will be run before each commit and push.

Please install and check the pre-commit hooks with:

pre-commit install
pre-commit run --all-files

• We have a 100% test-coverage policy, so please add a unit test to python_challenge/api/tests/ for the new endpoint.
  • Currently, test-coverage is not 100% because we have provided some fixtures for you to use in your test, see python_challenge/api/tests/conftest.py
  • For the UI prototype you do not need to write equivalent unit tests, however if you do add the UI as a Django view please add a test to check that the view responds with a HTTPStatus.OK