causal-test-again 0.1.67

A Scalable Causal Inference Library

Experimentation Library

We are thrilled you decided to contribute to Doordash Experiment Library!

Doordash Experimentation Library Dev Environment setup

Python

The easiest way to install the python version for this project is to use pyenv. Follow these steps:

• brew install pyenv
• Add pyenv initializer to shell startup script ~/.bash_profile: echo 'eval "$(pyenv init -)"' >> ~/.bash_profile
• pyenv install 3.8.10
• pyenv shell 3.8.10

To confirm that you have the right python version, simply run python in your terminal. This codebase should work with any Python ~3.8 version

Package dependencies

To install package depenencies, follow these steps:

• make install-deps. This command will do the following:
  • It wil create a virtual environment in the root of the project.
  • It will install poetry, which is being used for dependency management and package development
  • Poetry will install all the dependencies from poetry.lock file
  • It will install pre-commit hooks that are used for linting and formatting.
• Set up artifactory config by running poetry config http-basic.artifactory username password with your artifactory username and password
• If you want to update your dependencies, you can run poetry update.

Other make commands

• make shell: will start a bash terminal inside the container based of Dockerfile found in the project directory. This can be useful for running code in a more isolated environment that mimicks the CI/CD system.
• make local-build: this will build the sdist and the wheel for the library and put them in dist directory.
• make unittest: this will run tests locally

To perform development in a container using VsCode, please follow this guide.

License

This library is released under the Apache 2.0 license. See LICENSE for details.