PyData Global 2021: A Recap

makepath had the opportunity to attend and present at PyData Global 2021, a completely virtual conference. 

PyData Global gathers Python enthusiasts, developers of data analysis tools, and leaders within the PyData community to discuss the latest innovations in data management, analytics, and visualization.

A big thank you to the PyData Global planning committee!

PyData is part of NumFocus, a non-profit charity organization that sponsors open source research projects. 

Below is a recap of makepath’s participation in PyData Global 2021.

makepath Presentations

Spatial Analytics Using Dask and Numba 

Brendan Collins

makepath Co-Founder and Principal

Brendan started off with a high-level overview of Xarray-Spatial, an open source raster-based spatial analytics library that uses Numba to speed up algorithms and Dask for scalability across different cores and machines. 

“The aim of Xarray-Spatial is to provide analysis functions on top of rasters without dependencies on GDAL or GEOS.”

Brendan explained two fundamental types of data you’ll find in the geospatial world: 

1. Raster: grids of pixels that represent continuous phenomena.
2. Vector: points, lines, and polygons that represent discrete phenomena.  

Moving on to what makes Xarray-Spatial so valuable, Brendan highlighted the power of Datashader, a general-purpose rasterization pipeline. Datashader allows users to integrate vector data into raster-based analysis. It also makes operations like rasterization of polygons at the same resolutions as satellite imagery possible, which enables analysis between sources. 

Brendan and the makepath team recently looked into what parts of Xarray-Spatial would benefit the most from better GPU support and performance, to leverage the trailblazing work going on at NVIDIA.

Four tools stood out:

1. Terrain Generation
2. Viewshed
3. Hillshade
4. Hillshade with real shadows

Focusing on CuPy and CUDA on top of Xarray-Spatial has led to great results. 

What’s New in Bokeh 2.4 (Timestamp: 1:09:31)

Timo Metzger

Technical Writer and Bokeh Core Contributor 

Timo introduced the latest features in the Bokeh 2.4 release. 

Bokeh is an open source library that creates interactive JavaScript-powered visualizations for web browsers. No JavaScript coding is necessary for the user, since it is all defined in python.

Bokeh consists of two libraries: Python and BokehJS. 

What’s New in Bokeh 2.4? Here are Timo’s highlights:

• LaTeX for axis labels, ticks, and div widgets
• Better documentation for contributors 
• Improved SVG exports
• Improved Bokeh server performance and flexibility
• Added geopandas/xyzservices raster basemaps for map plots
• Wheel Packages on PyPI

What’s Next for Bokeh 3.0?

• Improved compatibility with existing web frameworks (Angular, Vue, etc.)
• Improved accessibility (for output Bokeh generates)
• Improved WebGL output (new ways to bring output into the browser)

Timo and the Bokeh team want you to contribute to Bokeh 3.0! You can contribute to open source projects even if you do not know how to code. To learn how to get started, visit bokeh.org/community.

Bokeh PyData Global Sprint

The PyData Global Sprint that took place on the last day of the conference helped attendees interested in Bokeh set up their development environments and start on their first issues.

The sprint covered a range of issues, but the main focus was updating Bokeh’s library of examples — a great way to explore what’s possible with Bokeh as your visualization tool. 

Four maintainers of Bokeh ran the sprint: three were makepath team members funded by a grant from the Chan Zuckerberg Initiative. 

Connect with the Open Source Community

makepath is actively involved in leveraging and creating Open Source GIS tools, which would not be possible without support from the Open Source Community!

If you want to learn more about Xarray-Spatial for raster analysis, Bokeh for visualizations, or anything else about Open Source projects, connect with us at makepath at contact@makepath.com.