Review of First Bokeh Fundraiser
Tags: Python, Data Visualization, Data Science, Open Source, Bokeh

July of this year was the first time that Bokeh has had a time-bound, focused fund drive, and we were impressed by the show of support: we exceeded our initial funding goal by 20%! While our code contributors have always been essential to maintaining and growing the scope and applications of the Bokeh project, the support of our users in other ways is also fundamental in driving Bokeh’s future success.

The Bokeh project has grown significantly in the last year, and some of that has meant incurring some operational costs. The funds raised will go directly to hosting costs for our documentation, demo sites, and the CDN for BokehJS, all platforms for helping our users research and discover ways to create beautiful data representations.

We received support from individuals, several who have shared some amazing visualizations using our libraries; check out the ongoing “30 Days of Bokeh” challenges on Twitter! The success of our fundraiser is a direct result of our community of data scientists, data engineers, and data communicators of all types showing their support. Thank you!

We also started a corporate sponsorship program, in which companies can support the ongoing development of Bokeh with tiered donation levels:

Bronze: $500 per year

Silver: $1,000 per year

Gold: $2,500 per year

Companies interested in becoming a Bokeh sponsor can email info@bokeh.org to start the conversation.

Here is our inaugural list of wonderful, much-appreciated corporate sponsors for 2019:

The mission of NumFOCUS is to promote open practices in research, data, and scientific computing by serving as a fiscal sponsor for open source projects and organizing community-driven educational programs.

With more than 15 million users, Anaconda is the world’s most popular data science platform and the foundation of modern machine learning. Anaconda Enterprise delivers data science and machine learning at speed and scale, unleashing the full potential of their customers’ data science and machine learning initiatives.

The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.

Quansight will help you get started with Artificial Intelligence, Machine Learning, Deep Learning, and Data management using Python or R as well as the toolboxes they link to including NumPy, Pandas, scikit-learn, Jupyter, Tensorflow, PyTorch, MXNet, Caffe, CNTK, Chainer, and more. Quansight extracts data from transactions, images, videos, weblogs, audio, and more. Access to their community and tools (which produced projects such as NumPy, SciPy, PyData, Numba, Conda, JupyterLab, Dask, Bokeh, XND, and many others) are now available directly to your business or project.

REX was created in 2015 to bring residential real estate into line with today’s expectations by using AI and big data to push past the outmoded practices of traditional real estate brokers to provide a superior outcome for both buyers and sellers at one-third the cost. Rex uses data modeling and machine learning to match sellers and buyers of homes as accurately and speedily as possible on Zillow, Google, Facebook and more.

Become a Contributor!

We learned a lot about how to run a fundraiser with this first event, and we look forward to future successes. If you’d like to become a sustaining supporter of the Bokeh project, the donation form is still accessible! Other ways to contribute to the project include:

Code contributions. If you know of a way in which Bokeh’s feature set could be improved, go for it!

Sharing your examples of Bokeh at work. We’re so proud of all the plots we see on social media and in our gallery!

Take part in the discussions on the Bokeh Discourse site . It’s a great format for getting support for your Bokeh questions, and helping others with your knowledge.

Thanks again for your support, Bokeh community- happy plotting!