Supporting Resources

Great Expectations requires a Python compute environment and access to data, either locally or through a database or distributed cluster. In addition, developing with Great Expectations relies heavily on tools in the Python engineering ecosystem: pip, virtual environments, and Jupyter Notebooks. We also assume some level of familiarity with Git and version control.

See the links below for good, practical tutorials for these tools.

pip

• https://pip.pypa.io/en/stable/
• https://www.datacamp.com/community/tutorials/pip-python-package-manager

Virtual Environments

• https://virtualenv.pypa.io/en/latest/
• https://python-guide-cn.readthedocs.io/en/latest/dev/virtualenvs.html
• https://www.dabapps.com/blog/introduction-to-pip-and-virtualenv-python/

Jupyter Notebooks and Jupyter Lab

• https://jupyter.org/
• https://jupyterlab.readthedocs.io/en/stable/
• https://towardsdatascience.com/jupyter-lab-evolution-of-the-jupyter-notebook-5297cacde6b

Git

• https://git-scm.com/
• https://www.atlassian.com/git/tutorials