A retrospective and prospective of Python's adoption in the data-driven industries and how it has and should influence its ecosystem and communities. Thanks to its versatility, Python's usage and adoption has changed a lot over the last decade to go beyond the very act of software programming. From Developers to SysOps, closely followed by Scientists and Data analysts, Python has spread to become a common tongue for a wide range of people. We will start by looking at how this increased adoption impacted Python ecosystem and is still shaping it today. While this talk is not walk through all the Python technologies around data, some of them will be outlined so you will hear words like Numpy, Pandas or Jupyter. Then we will try to project ourselves in the future and by highlighting the pitfalls Python has to overcome to keep up with its pace and mature in its ability to scale! Draft of the agenda The rise and collusion of science and engineering and their influence on Python From DevOps to DataOps, the shape and breakthroughs of Python's ecosystem Prospect of challenges and pitfalls in the massive data era