Welcome to CoEval AMR’s resource library!

Co-Eval AMR is a research network that evaluates existing frameworks and approaches for the evaluation of AMR surveillance and proposes guidance for their use taking an integrated perspective.

Check out the Usage section for further information, including how to Installation the project.

Note

This project is under active development.

Contents

Usage

Installation

To use Lumache, first install it using pip:

(.venv) $ pip install lumache

Creating recipes

To retrieve a list of random ingredients, you can use the lumache.get_random_ingredients() function:

The kind parameter should be either "meat", "fish", or "veggies". Otherwise, lumache.get_random_ingredients() will raise an exception.

For example:

>>> import lumache
>>> lumache.get_random_ingredients()
['shells', 'gorgonzola', 'parsley']

API