Recently, an increasing number of large scale astronomy projects have been opting to develop their software in a more open and community focused way. Often this has involved using Python in some capacity to enable rapid progress toward building effective data analysis packages.
In this talk I will introduce SunPy, a community-lead project to provide the core tools needed by solar physicists to obtain, access and analyse solar physics-specific data sources. I also describe how the Data Center team of the Daniel K. Inouye Solar Telescope (DKIST), which will be the largest solar telescope in the world when built, is incorporating Python, and SunPy in particular, into their operational, petascale data processing infrastructure as well as the primary language supporting a community-centered data analysis package for DKIST data. Finally, I will talk about the adoption of Python in the historically IDL-dominated field of solar physics and discuss the importance of building communities around both programming projects and data from large scale instruments.