Below we assume you have the default Python environment already configured on your computer and you intend to install mgcpy inside of it. If you want to create and work with Python virtual environments, please follow instructions on venv and virtual environments.

First, make sure you have the latest version of pip (the Python package manager) installed. If you do not, refer to the Pip documentation and install pip first.

Install the released version

Install the current release of mgcpy with pip:

$ pip install mgcpy

To upgrade to a newer release use the --upgrade flag:

$ pip install --upgrade mgcpy

If you do not have permission to install software systemwide, you can install into your user directory using the --user flag:

$ pip install --user mgcpy

Alternatively, you can manually download mgcpy from GitHub or PyPI. To install one of these versions, unpack it and run the following from the top-level source directory using the Terminal:

$ pip install .

Install from Github

To install from Github, run the following from the top-level source directory using the Terminal:

$ git clone
$ cd mgcpy
$ python3 install
  • sudo, if required
  • python3 build_ext --inplace  # for cython, if you want to test in-place, first execute this

Setting up the development environment

  • To build image and run from scratch:
    • Install [docker](
    • Build the docker image, docker build -t mgcpy:latest .
      • This takes 10-15 mins to build
    • Launch the container to go into mgcpy’s dev env, docker run -it --rm --name mgcpy-env mgcpy:latest
  • Pull image from Dockerhub and run:
    • docker pull tpsatish95/mgcpy:latest or docker pull tpsatish95/mgcpy:development
    • docker run -it --rm -p 8888:8888 --name mgcpy-env tpsatish95/mgcpy:latest
  • To run demo notebooks (from within Docker):
    • cd demos
    • jupyter notebook --ip --no-browser --allow-root
    • Then copy the url it generates, it looks something like this: http://(0de284ecf0cd or
    • Edit this: (0de284ecf0cd or to:, in the above link and open it in your browser
    • Then open mgc.ipynb
  • To mount/load local files into docker container:
    • Do docker run -it --rm -v <local_dir_path>:/root/workspace/ -p 8888:8888 --name mgcpy-env tpsatish95/mgcpy:latest, replace <local_dir_path> with your local dir path.
    • Do cd ../workspace when you are inside the container to view the mounted files. The mgcpy package code will be in /root/code directory.

Python package dependencies

mgcpy requires the following packages:

  • numpy
  • scikit-learn
  • scipy
  • Cython
  • pandas
  • h5py
  • seaborn

Hardware requirements

mgcpy package requires only a standard computer with enough RAM to support the in-memory operations.

OS Requirements

This package is supported for macOS and partly on Linux.


mgcpy uses the Python pytest testing package. If you don’t already have that package installed, follow the directions on the pytest homepage.