Welcome

This project explores my approach and solution for a requested technical screen.

Solution #1 - TypeScript

Solution #2 - Python

The Challenge

I've included the requirements from the challenge for reference.

Objective

Imagine you work in a robotic automation factory, and your objective is to write a function for one of its robotic arms that will dispatch the packages to the correct stack according to their volume and mass.

Rules

Sort the packages using the following criteria:

• A package is bulky if its volume (Width x Height x Length) is greater than or equal to 1,000,000 cm³ or when one of its dimensions is greater or equal to 150 cm.
• A package is heavy when its mass is greater or equal to 20 kg.

You must dispatch the packages in the following stacks:

• STANDARD: standard packages (those that are not bulky or heavy) can be handled normally.
• SPECIAL: packages that are either heavy or bulky can't be handled automatically.
• REJECTED: packages that are both heavy and bulky are rejected.

Implementation

Implement the function sort(width, height, length, mass) (units are centimeters for the dimensions and kilogram for the mass). This function must return a string: the name of the stack where the package should go.

My solution

For this particular example, I wanted to demonstrate how I would solve this challenge - creating two solutions to demonstrate my style and approach with TypeScript and Python. 🤓

TL;DR

If you already have Node.js, npm, and Python installed on your system, you can run the following scripts to see my solutions in action 🤓

# Pull the trigger and run both TypeScript and Python solutions
% npm start

# TypeScript solution
% npm run typescript:solution

# Python solution
% npm run python:solution

TypeScript

To run the TypeScript solution from the project root:

# TypeScript solution
% npm run typescript:solution

# Navigate to the directory
% cd solutions/typescript

# Install dependencies
% npm install

# Run scripts as desired 🤓

## EXAMPLE: Run tests
% npm test

## EXAMPLE: Run tests and generate a code coverage report
% npm run test:coverage

## EXAMPLE: Run tests with verbose output
% npm run test:verbose

## EXAMPLE: Run tests with verbose output and generate a code coverage report
% npm run test:verbose:coverage

## EXAMPLE: Run code in development
% npm start

## EXAMPLE: Build project
% npm run build

## EXAMPLE: Run production code after building the project
% npm run start:prod

Python

To run the Python solution from the project root:

# Python solution
% npm run python:solution

# Navigate to the directory
% cd solutions/python

# Initialize the Python virtual environment
% python3 -m venv .venv

# Activate the Python virtual environment
# On Windows, use `.venv\Scripts\activate`
% source .venv/bin/activate

# Install the packages from requirements.txt
(.venv) % pip install -r requirements.txt

# To run the code:
(.venv) % python3 src/main.py

# To run tests:
(.venv) % pytest

# To run tests and automatically view the HTML coverage report on macOS:
(.venv) % pytest --cov=. --cov-report=html && open htmlcov/index.html

# To run tests with verbose output:
(.venv) % pytest -v

# To run tests with verbose output and automatically view the HTML coverage report on macOS:
(.venv) % pytest -v --cov=. --cov-report=html && open htmlcov/index.html

# To run a single unit test
(.venv) % pytest tests/lib/test_sort.py

# Deactivate your virtual environment
(.venv) % deactivate