From easy integrations, plotting inspiration, and technical details about our query engine, there’s something for everyone in the latest round of Deephaven documentation. Keep reading for the highlights, and as always check out our YouTube channel for new content weekly.
In this release, we’ve added another quick start guide for Python users who want to install Deephaven with pip. Pip is the package manager for Python and is the easiest way to install Python packages, including Deephaven.
Integrations
Our Jupyter integration gives you all the benefits of Deephaven’s streaming tables and plots in the notebooks you love. Follow the new how-to guide to get set up.
DQL
The Deephaven Query Langugage allows users to write powerful queries to filter and modify tables of data. We’ve added documentation to help up-level your queries, such as how to programmatically generate query strings in Python and overviews of parallelizing queries and locking.
In the Deephaven blog, we’ve been chronicling crypto use cases and how to use AI to predict prices and manage investments. Our series is now complete, with the following additions:
Other articles related to stocks and trading include how to build your own automated market maker using Deephaven and Interactive Brokers, and how to use a scatter plot overlay to create real-time chart markers.
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