Installation

Installation with conda is recommended.

conda environment files for Python 3.7, 3.8 and 3.9 are available in the repository. To use models under the inference.tf module (e.g. DragonNet), additional dependency of tensorflow is required. For detailed instructions, see below.

Install using conda

Install conda

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh -b
source miniconda3/bin/activate
conda init
source ~/.bashrc

Install from conda-forge

Directly install from the conda-forge channel using conda.

conda install -c conda-forge causalml

Install from the conda virtual environment

This will create a new conda virtual environment named causalml-[tf-]py3x, where x is in [7, 8, 9]. e.g. causalml-py37 or causalml-tf-py38. If you want to change the name of the environment, update the relevant YAML file in envs/.

git clone https://github.com/uber/causalml.git
cd causalml/envs/
conda env create -f environment-py38.yml    # for the virtual environment with Python 3.8 and CausalML
conda activate causalml-py38

Install causalml with tensorflow

git clone https://github.com/uber/causalml.git
cd causalml/envs/
conda env create -f environment-tf-py38.yml # for the virtual environment with Python 3.8 and CausalML
conda activate causalml-tf-py38
pip install -U numpy                        # this step is necessary to fix [#338](https://github.com/uber/causalml/issues/338)

Install from PyPI

pip install causalml

Install causalml with tensorflow from PyPI

pip install causalml[tf]
pip install -U numpy                            # this step is necessary to fix [#338](https://github.com/uber/causalml/issues/338)

Install from source

Create a clean conda environment.

conda create -n causalml-py38 -y python=3.8
conda activate causalml-py38
conda install -c conda-forge cxx-compiler
conda install python-graphviz
conda install -c conda-forge xorg-libxrender

Then:

git clone https://github.com/uber/causalml.git
cd causalml
pip install .
python setup.py build_ext --inplace

with tensorflow:

pip install .[tf]

---

Windows

See content in https://github.com/uber/causalml/issues/678

Running Tests

Make sure pytest is installed before attempting to run tests.

Run all tests with:

pytest -vs tests/ --cov causalml/

Add --runtf to run optional tensorflow tests which will be skipped by default.

You can also run tests via make:

make test