Installation¶

SimpleML currently runs best on Python 2.7.x and 3.5+; other versions may work but are not explicitly supported.

You can install SimpleML via several different methods. The simplest is via pip:

pip install simpleml

While the above is the simplest method, the recommended approach is to create a virtual environment via conda, before installation. Assuming you have conda installed, you can then open a new terminal session and create a new virtual environment:

conda create -n simpleml python
source activate simpleml

Once the virtual environment has been created and activated, SimpleML can be installed via pip install simpleml as noted above. Alternatively, if you have the project source, you can install SimpleML using the distutils method:

cd path-to-source
python setup.py install

If you have Git installed and prefer to install the latest bleeding-edge version rather than a stable release, use the following command:

pip install -e "git+https://github.com/eyadgaran/simpleml.git@master#egg=simpleml"

Optional packages¶

SimpleML comes configured with a few optional dependencies. The base installation will work without any issues if they are not installed, but extended functionality will not be available.

The general command is pip install simpleml[extras] (substituting “extras” with the group of dependencies)

These are the current supported extras:

'postgres': ["psycopg2"]
'deep-learning': ["keras", "tensorflow"]
'hdf5': ["hickle"]
'cloud': ["onedrivesdk", "apache-libcloud", "pycrypto"]

Additionally, a convenience extra titled all is defined to install the full list of optional dependencies.

Dependencies¶

When SimpleML is installed, the following dependent Python packages should be automatically installed. These are necessary dependencies and SimpleML will not function properly without them.

sqlalchemy, to manage database communication
sqlalchemy_mixins, for database active record functionality
alembic, for database schema management
pandas, for data processing
numpy, for numerical foundations
cloudpickle, for code pickling
future, for Python 2 and 3 compatibility
configparser, for config management
simplejson, extended support for json handling
scikit-learn, base machine learning support and metric computation

Upgrading¶

If you installed SimpleML via pip and wish to upgrade to the latest stable release, you can do so by adding --upgrade:

pip install --upgrade simpleml

If you installed via distutils or the bleeding-edge method, simply perform the same step to install the most recent version.