Intel MacOS

Note: This guide is suitable for Mac machines with Intel processors. For newer Macs with M1 processors, see M1 MacOS.

Python installation

The first thing you need to do is to set up python 3.8. If you haven't done this, this can be done in several ways via Terminal or your preferred client:

Using Anaconda:

# Using conda...conda create -n bitfount python=3.8 bottleneck

or using Homebrew: First, install Homebrew :

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"

As recommended by Homebrew, the following environment variables should also be set:

export PATH="/usr/local/opt/python/libexec/bin:$PATH"

Now, we can install Python 3.8 or 3.9:

$ brew install python3.8

Also, make sure that pip is installed. (You can check this by running pip help). If not, use the below command to install:

python3 -m ensurepip --upgrade

Along with python, you also need to install libomp. Note that version 12.0.0 of libomp on Homebrew is incompatible with LightGBM on MacOS. We recommend running the following brew commands for getting the required version:

curl https://raw.githubusercontent.com/Homebrew/homebrew-core/fb8323f2b170bd4ae97e1bac9bf3e2983af3fdb0/Formula/libomp.rb -o libomp.rbbrew unlink libompbrew install libomp.rb

Bitfount Installation via CLI

If you’d prefer to install Bitfount via CLI, ensure the python and libomp dependencies are installed and install bitfount using the relevant package manager.

We recommend that you install bitfount in a virtual environment. You should first install virtualenv as follows:

pip install virtualenv

And then create and activate a virtual environment:

python -m venv <path_to_virtual_environment>source <path_to_virtual_environment>/bin/activate

Either in the virtual environment or on your local machine you can then proceed to install bitfount.

pip install bitfount

This might take a few moments, so do not worry if it does — grab a coffee or tea while you wait!

If you are planning on using the bitfount package with Jupyter Notebooks we recommend you install the splinter package bitfount[tutorials] which will make sure you are running compatible jupyter dependencies.

pip install "bitfount[tutorials]"

Next Steps

Once you’ve installed Bitfount, whichever party that will provide the data for analysis must connect the data to a Pod. See For Data Custodians for detailed instructions.

If data is already connected to a Pod for analysis and you wish to train models on or query it, see For Data Scientists.