My Take-Aways after Attending PyCon.DE 2018 in Karlsruhe

25 November 2018

PyCon De 2018

On October 24th until 26th 2018, I attended my second german Python Conference (PyCon.DE) in Karlsruhe. During the three days venue, I've met many interesting persons and attending interesting talks. In this article, I would like to write down the list and the take- away messages from the conference, so that in future I can recap it again.

List of the Talks and Workshop

These are the list of the talks and workshops that I attended during the three days:

  1. Digital Cultural Techniques by Peter Weibel
  2. Introduction and practical experience about Quantum Computing using the Python libraries from IBM and Google by Dr. Andreas Riegg
  3. Developing ecommerce platform with Django Oscar by Alexander Gaevsky
  4. Scalable Scientific Computing using Dask by Uwe L. Korn
  5. Active Learning - Building Semi-supervised Classifiers when Labeled Data is not Available by Dr. Hendrik Niemeyer
  6. Script, Library, or Executable: You can have it all! by Luke Lee
  7. Testing in Python - The Big Picture by Niklas Meinzer
  8. About going Open-Source by Tim
  9. Looking backward, looking forward by Wes McKinney
  10. Understanding Neural Networks by Playing Games by Sidharth Ramachandran
  11. Satellite Image Segmentation Photovoltaic Potential Estimation by Johannes Oos
  12. Interactive Visualization of Traffic Data using Bokeh by Dr. Patrik Hlobil
  13. Python on the blockchain: Triumphs and tribulations in a crypto startup by Daniel and Lorb
  14. Observe all your applications by Christoph Heer
  15. Microservices from the trenches: how we delivery fancy sofas across Europe by Christian Barra
  16. scikit-image by Emmanuelle Gouillart
  17. Concurrency in Python - concepts, frameworks and best practices by Stegan Schwarzer
  18. Enabling the chip technologies of tomorrow by Tim Hoffmann
  19. Cython to speed up your Python code by Stefan Behnel
  20. Lightning Talks

The other talks can be watched in each talks by clicking the title in the PyCon.DE schedule.

My take aways

Digital Cultural Techniques

  • The first talks from Peter Weibel gave me very interesting topics about evolution and philosophy of the digital world. He described and showed some overview of the publication of the famous scientific research such as from Gottfried Wilhelm Leibniz, Isaac Newton, Joseph-Luise de Lagrange, George Boole, Alan Turing, Claude Elwood Shannon, Axel Thue, Heinrich Hertz.

  • He talked about the reversibility of the current digital age, that things and data are reversible.

    In the analog world the relation between things and symbols has been irreversible. In the digital world, the relation between words, images, sound and data, even between things and data, is reversible. ~ Peter Weibel.

Introduction and practical experience about Quantum Computing using the Python libraries from IBM and Google

  • Short interesting overview about qubits (quantum bits) and how a quantum computer calculates an operation compared to the classical computer.
  • Overview of the components of a current quantum computer which is very fragile and still challenging due to the temperature.

Scalable Scientific Computing using Dask

If in future I need to process a big data, the take away is that Dask is somehow better than Spark.

Script, Library, or Executable: You can have it all!

Very nice talks that gives some tipps how to build and publish Python scripts, packages, libraries, GUI application and executables.

Looking backward, looking forward

  • The creator of the open-source panda package
  • Knowing his motivation and the challenges of working in a big open source project
  • Scenarios of funding of an open-source software

Interactive Visualization of Traffic Data using Bokeh

Very nice tutorial to use Bokeh for visualization.

Cython to speed up your Python code

  • Speed up Python Code in CPython.
  • Tutorial how to convert Python for loop to C-based for loop.
  • Tutorial how to call C memory allocation using malloc and free in Python.
from libc.stdlib cimport malloc, free

cdef int* c_mem = <int*>malloc(20*sizeof(int))
if not c_mem:
    raise MemoryError()
free(c_mem)
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