Challenge

This challenge is divided between the main task and additional stretch goals. All of those stretch goals are optional, but we would love to see them implemented. It is expected that you should be able to finish the challenge in about 1.5 hours. If you feel you are not able to implement everything on time, please, try instead describing how you would solve the points you didn't finish.

And also, please do not hesitate to ask any questions. Good luck!

gistapi

Gistapi is a simple HTTP API server implemented in Flask for searching a user's public Github Gists. The existing code already implements most of the Flask boilerplate for you. The main functionality is left for you to implement. The goal is to implement an endpoint that searches a user's Gists with a regular expression. For example, I'd like to know all Gists for user justdionysus that contain the pattern import requests. The code in gistapi.py contains some comments to help you find your way.

To complete the challenge, you'll have to write some HTTP queries from Gistapi to the Github API to pull down each Gist for the target user. Please don't use a github API client (i.e. using a basic HTTP library like requests or aiohttp or urllib3 is fine but not PyGithub or similar).

Stretch goals

Implement a few tests (using a testing framework of your choice)
In all places where it makes sense, implement data validation, error handling, pagination
Migrate from requirements.txt to pyproject.toml (e.g. using poetry)
Implement a simple Dockerfile
Implement handling of huge gists
Set up the necessary tools to ensure code quality (feel free to pick up a set of tools you personally prefer)
Document how to start the application, how to build the docker image, how to run tests, and (optionally) how to run code quality checkers
Prepare a TODO.md file describing possible further improvements to the archtiecture:
- Can we use a database? What for? SQL or NoSQL?
- How can we protect the api from abusing it?
- How can we deploy the application in a cloud environment?
- How can we be sure the application is alive and works as expected when deployed into a cloud environment?
- Any other topics you may find interesting and/or important to cover

Documentation

Setting up development environment

Clone the repository:

git clone git@github.com/vkolev/backend-coding-challenge

Make sure you have poetry installed so running the following command will generate virtual environment for the project automatically (providing the flag --with dev will ensure that the development dependencies are installed)

poetry intall --with dev

Running Tests

To run the tests:

poetry run -v pytest

Or using the Makefile:

make test

Code Quality

For code quality we use black and pylint

Black - to ensure consistent formatting
pylint - to check for linting errors (we run it with --max-line-length=120 since 80 characters is too small for modern monitors)

poetry run black gitstapi
poetry run pylint gistapi --max-line-length=120

Or using make:

make checks

Runing the application

Running the application with Flask Build-in server

poetry run python run.py

Running the application with docker

docker-compose up --build