Unicheck.ai Technical Interview Demo – Django REST Edition

Welcome! This repository is an automatically generated demo interview produced by unicheck.ai.

It demonstrates how the platform turns a job description into a realistic, production-like technical assignment.

Powered by an agent‑based architecture – every stage, from vacancy parsing to the candidate's solution scoring, is performed by specialised LLM agents.

As a result, each candidate receives a unique, production-grade project as a test task, and hiring managers receive a multi-angle, evidence-based assessment.

How the system works

1. Post your vacancy – paste the job description. That’s all we need to start.
2. Skill map generation – unicheck.ai analyses the job description and extracts the exact knowledge, tools, and seniority your role requires.
3. Interview assembly – for each candidate, we spin up a fresh GitHub repo with unique tasks tailored specifically for a given position. The interview tasks include genuine bugs, anti‑patterns, optimisation needs, or missing features.
4. Invite the candidate – a private repo is provisioned for the candidate (GitHub username is enough).
5. Candidate action – they open the GitHub Codespaces, fulfill the requirements of the task, and open a Pull Request.
6. Automated review – analysis agents inspect the code, tests, and commit history alongside static analysis and style checks; a detailed report is produced.
7. Adjust & repeat – hiring teams can edit requirements or regenerate tasks at any point.

Each interview repo is unique, medium-sized production-like service, so solutions cannot be reused between candidates.

All tooling is fully configured and ready to launch, so candidates can start coding immediately in a ready-to-work environment.

Role demonstrated:

Middle Python / Django Developer

Interview description for the candidate: Django Interview

Welcome to the live‑coding stage of our hiring process. You will work on a compact yet production‑style Django REST project. Issues reported by product, marketing, and finance have been turned into auto-tests.

Your goal is to address those issues and keep all tests green.

What's included

• A ready‑to‑run Django application.
• Pre‑configured infrastructure (PostgreSQL, Redis, Docker, devcontainer).
• A comprehensive test suite. All tests should stay green.

Business stories to address

See the task list

Getting started

• Select the prepared git branch candidate
• Go Code -> Codespaces -> Create codespace on candidate:

• You will find a ready-made, fully operational dedicated workspace to solve the interview. Take any action to solve the problem, keep the project working, and make sure that all the tests are passing.

Requirements

• Commit each task separately.
• When all interview tests are done, open one Pull Request with your solution.
• All tests must be successfully passed. For tests/interview/, the removal of the decorator @pytest.mark.xfail is mandatory.
• Your solution will be evaluated externally. In addition to test results, the following aspects will be considered:
  • code quality and style
  • architectural and implementation decisions
  • adherence to industry best practices
  • the amount of time invested in completing the task
• Creative solutions are welcome if they meet quality standards.

⏱ Time‑box

The task is designed to be solved not more than 1 hour. Focus on clear, incremental fixes.

Helpful commands

Use the terminal to run:

• make interview to run interview tests to check your solutions.
• make test to run common project tests to ensure that common features are still working.
• make lint to run linters and formatters.
• see more useful commands in the Makefile.

Good luck and enjoy!

About Project

A back-end service that lets travelers discover nearby points of interest, build day-by-day itineraries and reserve limited time-slot attractions — all through a RESTful JSON API. Local tour operators manage their attractions’ availability while end-users assemble personal schedules and place bookings that respect capacity and timing rules. The system stores geo-spatial data for proximity search, supports multilingual content, and guarantees seats by applying row-level locks inside transactional booking flows.

see more details

Tech Stack

• Python: 3.11
• Django: 4
• API: Django REST Framework
• Database: PostgreSQL 15
• Caching: Redis 7
• Testing: Pytest, Pytest-Django
• Architecture: Service Pattern, Resource-Based API
• Dependency Management: requirements.txt

Project Structure Overview

> tree -a -I .git|.github|.gitignore|.devcontainer|.dockerignore|.vscode|.idea|__pycache__|.mypy_cache|alembic|.pytest_cache|__init__.py|.venv|node_modules|dist|build --gitignore
.
├── .env.example
├── app
│   ├── admin.py
│   ├── api
│   │   ├── exceptions.py
│   │   ├── pagination.py
│   │   ├── permissions.py
│   │   ├── serializers.py
│   │   ├── urls.py
│   │   └── views.py
│   ├── apps.py
│   ├── migrations
│   │   └── 0001_initial.py
│   ├── models.py
│   └── services.py
├── config
│   ├── asgi.py
│   ├── settings.py
│   ├── urls.py
│   └── wsgi.py
├── docker-compose.yml
├── Dockerfile
├── docs
│   ├── codespaces_example.png
│   └── README.md
├── Makefile
├── manage.py
├── pyproject.toml
├── README.md
├── requirements.txt
└── tests
    ├── api
    │   ├── test_api_basic.py
    │   ├── test_api_itinerary_stats.py
    │   ├── test_api_poi_geo.py
    │   ├── test_api_schedule.py
    │   ├── test_auth_permissions.py
    │   └── test_heapth.py
    ├── conftest.py
    ├── models
    ├── test_core_models.py
    └── test_services.py

8 directories, 35 files

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Contact: info@unicheck.ai