rdparedes / dema-ai-code-challenge Goto Github PK

For tech stack of this solution, I took the freedom to choose a few libraries and frameworks that I haven't used before but I wanted to try out, such as FastAPI, Tortoise ORM and Aerich.

Regarding the exercise's scope, I decided to focus on architecting all the pieces and implementing the core features, but I left aside automated testing, custom error handling and other details that would be necessary for a production-ready solution.

• List inventory, including pagination and filtering by name, category and subcategory
• Update inventory - update a product's name, quantity, category and/or subcategory
• GraphQL API

• The GraphQL API returns products, but does not have GraphQL native pagination or filtering. The GraphQL API is implemented using Strawberry, which is a very simple and lightweight library, and it is very easy to integrate with FastAPI.
• Bulk update support for Update Inventory
• Sorting support for List Inventory

• Python 3.7+ (tested with Python 3.11.6)

This project was created using poetry:

pip install poetry

# Install the dependencies
poetry install

# Start a virtual environment to run the server
poetry shell

Run the server

uvicorn app.main:app --root-path app/ --reload

python scripts/import_data.py -d

The database already contains all the necessary data, changes can be done with Aerich

# To create a new migration
aerich migrate

# To upgrade the database
aerich upgrade

Start the server:

strawberry server app.graphql:schema

The graphql playground will be available at http://localhost:8000/graphql

# Get all products
curl -X GET "http://localhost:8000/products?page_size=15"
curl -X GET "http://localhost:8000/products?page_size=15&category=clothing"
curl -X GET "http://localhost:8000/products?page_size=15&sub_category=blouse"

# Update a product
curl -X PUT -H 'Content-Type: application/json' -d '{"name": "foobar"}' "http://localhost:8000/products/prod1548%23prod104001000080"