Graphistry 2.31.7

Posted by Graphistry Staff on August 28, 2020

2.31 is out! Graphistry Hub cloud users have already been enjoying the fixes and speedups, on-prem users can download  one of our Docker tarballs, and the aligned release is making its way through AWS + Azure cloud marketplaces for one-click launches in your team’s private cloud account. Graphistry 2.31.7 adds a lot for working with […]

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Graphistry 2.30.26: Graph gallery, edge weighting, a faster release schedule, and more

Posted by Graphistry Staff on July 12, 2020

Figure: Clustering animation when neighbor edges weigh more than non-neighbors   Graphistry v2.30.26 is a fast and worthwhile follow on to our big v2.29 introduction of the 2.0 API for quickly uploading big graphs (Apache Arrow + RAPIDS!) and the 2.30.11 launch of Graphistry Hub for free open visual investigations on managed Graphistry GPU instances. […]

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Graphistry 2.30.11: Graphistry Hub, PyGraphistry 2.0 API, & RAPIDS 0.14

Posted by Graphistry Staff on June 19, 2020

Release 2.30.11 is a fast and worthwhile follow on the big 2.29 release. If you didn’t get Graphistry 2.29 with our new Graphistry 2.0 API — 100X faster & bigger uploads! — now is your chance with 2.30. The latest release also introduces Graphistry Hub, RAPIDS 0.14, open registration mode, and more. As a reminder, […]

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Graphistry 2.29.5: Upload 100X+ more, RAPIDS 0.13, LearnRAPIDS.com, and more!

Posted by Graphistry Staff on May 28, 2020

Updated: 6.24.2020 to reflect PyGraphistry now supporting the 2.0 Upload API The Graphistry team has been quite busy with v2.29. While we’ve been quiet on the tool side as we’ve been directing attention to our volunteer efforts like ProjectDomino.org for medical anti-misinformation, and as you’ll see, a lot has been happening! As usual, get the […]

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Graphistry 2.23.4: HyperNetX, data bridge, fuzzy matching, and APIs

Posted by Graphistry Staff on August 16, 2019

Enterprise users will be happy to hear about the data bridge, while  fuzzy matching and new URL parameters should make life better for scripters.  This release also provides an example of working with PNNL’s new HyperNetX Python package.

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