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.
pipโ
- https://pip.pypa.io/en/stable/
- https://www.datacamp.com/community/tutorials/pip-python-package-manager
Virtual Environmentsโ
- 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 Labโ
- https://jupyter.org/
- https://jupyterlab.readthedocs.io/en/stable/
- https://towardsdatascience.com/jupyter-lab-evolution-of-the-jupyter-notebook-5297cacde6b