@Scout What is the best approach to using Selenium in Dagster?

The documentation does not provide a specific guide or best practices for using Selenium with Dagster. However, Dagster is a flexible orchestration tool that can run arbitrary Python code, so you can use Selenium within Dagster assets or jobs just as you would in a regular Python script. To integrate Selenium into a Dagster pipeline, you would typically define an asset or a job that includes the Selenium code to perform web automation tasks. Here's a general approach you might take, based on how you would use Python code in Dagster: 1. Install Selenium and the necessary web drivers for your chosen browser. 2. Define a Dagster asset or job that encapsulates your Selenium logic. 3. Use Dagster's resource system to manage browser instances and other configurations if needed. 4. Ensure that any data produced by Selenium is handled appropriately, either by storing it as an asset or passing it to other parts of your pipeline. Remember that running Selenium requires a browser and a web driver, so you'll need to ensure that your execution environment (local machine, Docker container, Kubernetes pod, etc.) has the necessary dependencies installed. For more detailed guidance on how to structure your code within Dagster, you can refer to the documentation on software-defined assets, jobs, and resources. If you encounter specific issues or need more tailored advice, you might consider searching for community discussions or opening a discussion on the Dagster GitHub repository to seek input from other users who may have experience with Selenium and Dagster.