Links

Support for Installation

Error in pip's Dependency Resolver

This error indicates that there are conflicting requirements in the Python libraries you are trying to install. You are likely to encounter this if you already have libraries installed in your environment.
To prevent conflicts, we recommend using a virtual environment (such as virtualenv). Ensure that you have the correct Requirements and try the installation again in a fresh Python environment dedicated to the SDV.
Are you using a Google Colab notebook? Sometimes Google Colab comes with different default libraries than the ones that SDV requires. Generally, you can ignore the printed errors.
In the top menu bar, click Runtime and then Restart session. After this, you can continue running the rest of your code.

ModuleNotFoundError or AttributeError

These errors may indicate a problem with installation or usage. To debug this, start by verifying that you have the latest SDV version.
import sdv
print(sdv.__version__)
When a version number prints, it should be the latest one found in our Release Notes.
Installation problems: If this code produces an error or if the version is old, then the newest SDV is not properly installed. Ensure that you have the correct Requirements and try the installation again in a fresh Python environment.
Usage problems: If everything looks ok, then ensure that you are using the correct API and spelling. Starting from version 1.0.0, some modules now use different names. Browse this website to see the latest API.

Other Issues?

For other problems, please visit our GitHub. You can browse existing issues and raise a new one if you cannot find a solution.
Copyright (c) 2023, DataCebo, Inc.