sesam-io / backend-challenge

A small programming challenge for applicants for backend positions in Sesam.

Sesam Backend Challenge

A small programming challenge for applicants for backend positions in Sesam.

Overview

This task is designed to test some general skills that are important for a backend/fullstack developer without being too time-consuming. Some of the things you encounter while working on this task: Git, GitHub, a JSON REST API, Python, Flask, Docker.

This challenge involves building a small API server and corresponding command-line client, both in Python, that allow uploading and processing JSON files, such as those included in the repo.

Setup

Fork this repository to your own GitHub account as a private repository (don't create pull requests to https://github.com/sesam-io/backend-challenge directly). Add @branislavjenco, @BaardBouvet and @grove as collaborators (you can do this when you are finished or right at the start).

Task

For this task we'll be building a very simple Python 3-based REST API server and command-line client.

API Server

The API server should have a single root endpoint, /datasets/, that allows list and CRUD operations over a dataset object via the following API / HTTP verbs:

• GET /datasets/ - list the ids of the uploaded datasets and their corresponding file sizes
• POST /datasets/ - creates a dataset. This endpoint takes a JSON file as input, and stores it somewhere/how on the server. A reference to this created object is returned by the endpoint, for instance an id or url.
• GET /datasets/<id>/ - return the particular dataset
• DELETE /datasets/<id>/ - delete the dataset object
• GET /datasets/<id>/excel/ - export the dataset as an excel file

Client Library

The client app should be a fully standalone command-line python application. The app should provide command-line arguments that correspond and support each of the API actions above - how you structure the command line arguments and what you call them is left up to you.

Technologies

You may use any Python libraries and technologies of your choice, but we would like you to use Flask for serving the requests. We would also like you to build a Docker image for the API server and run it as a Docker container. It's up to you to use other Python development and packaging tools, like virtualenv and setuptools.

Notes

• do not hesitate to ask us any questions
• don't worry if you can't finish all aspects of the task - make notes on where you got stuck and why
• it's all about conveying to us what your process was when tackling the challenge