Metadata-Version: 2.1
Name: mercs
Version: 0.0.20
Summary: MERCS: Multi-Directional Ensembles of Regression and Classification treeS
Home-page: https://github.com/eliavw
Author: Elia vw
Author-email: elia.vw@gmail.com
License: mit
Project-URL: Documentation, https://github.com/eliavw
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: networkx
Requires-Dist: scikit-learn
Requires-Dist: dask
Requires-Dist: toolz
Requires-Dist: tornado
Requires-Dist: pydot
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'

# mercs

Add a short description here!

## Description

A longer description of your project goes here...

## Installation

In order to set up the necessary environment:

1. create an environment `mercs` with the help of [conda],
   ```
   conda env create -f environment.yaml
   ```
2. activate the new environment with
   ```
   conda activate mercs
   ```
3. install `mercs` with:
   ```
   python setup.py install # or `develop`
   ```

Then take a look into the `scripts` and `notebooks` folders.

## Dependency Management & Reproducibility

1. Always keep your abstract (unpinned) dependencies updated in `environment.yaml` and eventually
   in `setup.cfg` if you want to ship and install your package via `pip` later on.

2. Create concrete dependencies as `environment.lock.yaml` for the exact reproduction of your
   environment with:
   ```
   conda env export -n mercs -f environment.lock.yaml
   ```

   _N.b.: For multi-OS development, consider using `--no-builds` during the export._

3. Update your current environment with respect to a new `environment.lock.yaml` using:
   ```
   conda env update -f environment.lock.yaml --prune
   ```


