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Iris Species v0.0.1

Overview

Iris Species classification engine from Kaggle

Requirements

REPLACE: Add here the list of requirements. For example:

  • Python 2.7
  • Numpy 1.11.0 or higher

Installation

_REPLACE: Add here the best way to install this engine

Development

Getting started

First, create a new virtualenv

mkvirtualenv marvin_iris_species_engine_env

Now install the development dependencies

make marvin

You are now ready to code.

Adding new dependencies

It`s very important. All development dependencies should be added to setup.py.

Running tests

This project uses py.test as test runner and Tox to manage virtualenvs.

To run all tests use the following command

marvin test

To run specific test

marvin test tests/test_file.py::TestClass::test_method

Writting documentation

The project documentation is written using Jupyter notebooks. You can start the notebook server from the command line by running the following command

marvin notebook

Use notebooks to demonstrate how to use the lib features. It can also be useful to show some use cases.

Bumping version

marvin pkg-bumpversion [patch|minor|major]
git add . && git commit -m "Bump version"

Tagging version

marvin pkg-createtag
git push origin master --follow-tags

Logging

The default log level is set to WARNING. You can change the log level at runtime setting another value to one of the following environment variable: MARVIN_IRIS_SPECIES_ENGINE_LOG_LEVEL or LOG_LEVEL. The available values are CRITICAL, ERROR, WARNING, INFO and DEBUG.

Be careful using LOG_LEVEL, it may affect another lib.