We are in 2019 and the PyData ecosystem seems extremely healthy. Python is growing in popularity and the PyData ecosystem is increasingly becoming the de-facto standard for many areas of data science, replacing expensive proprietary software like Matlab, SAS or SPSS. And a project like pandas was already responsible for 1% of StackOverflow traffic from developed countries in 2017, and it has seen its number of users doubled year-to-date.

For new users of the PyData ecosystem, and new members of the community, it may look like the path has been easy, and it is just the product of the normal evolution of software and technology. But is this true? How is the PyData ecosystem different from others such as Business Intelligence or ERPs, where open source projects are very small players? Can we be confident that the future of scientific software will be open, free and Pythonic?

This talk will describe the journey of a community that manages to work as a team, in a complex, challenging and sometimes tough environment. And that is writing one of the most fascinating chapters in the history of technology.