What are the network messaging options? How do they compare? And which should I use?

MQTT is being used by AWS but how does this compare to the newly emerging gRPC; how does the tried and tested Avro compare to Protocol Buffers or even using the familiar JSON with HTTP and Websockets? Enjoy the presentation by Mike Leonard (he is from Australia, isn't he?)
https://www.youtube.com/watch?v=UfPhXhCjMpw

Prepare for Python 3.8. The release schedule is here (the releases are not going to happen soon though):
https://www.python.org/dev/peps/pep-0569/

I'm sure all of us use pdb pretty often. Just to remind you - here are some hints on how to use pdb effectively:
https://www.codementor.io/stevek/advanced-python-debugging-with-pdb-g56gvmpfa

Have you ever asked yourself if you needed Python metaprogramming in some particular situation? If you did, you didn't need it. You only go with metaprogramming when you are 101% sure you need it. And this presentation is therefore for you. Enjoy Mike Leonard and your weekend:
https://www.youtube.com/watch?v=l8u8VENJhpM

You guys know that there are some major improwements in python 3.7. Here is a little description of the performance speed up:
https://hackernoon.com/5-speed-improvements-in-python-3-7-1b39d1581d86

No. Magic. In. Regular expressions. Absolutely.
https://rcoh.me/posts/no-magic-regular-expressions/

Here is a list of 500 algorithms. Most of them are not written in Python but anyway this is a useful and mighty collection.
https://techiedelight.quora.com/500-Data-Structures-and-Algorithms-practice-problems-and-their-solutions

A little note on copying things in Python, of course with some examples:
https://www.programiz.com/python-programming/shallow-deep-copy

Today I want to introduce to you a wonderful tool, which some of you may already be familiar with - mitmproxy, a great man-in-the-middle proxy which you can setup in a few minutes. It's a joy to use it for the software development purposes, but you may go further%) Please, check it out:
https://mitmproxy.org/

The demystification of range and why it is not an iterator: http://treyhunner.com/2018/02/python-range-is-not-an-iterator/

A little tutorial about reactive programming in Python (based on RxPy library but anyway it is useful):
https://auth0.com/blog/reactive-programming-in-python/

You should try the Google's ML course. It's free and available now.
https://thenextweb.com/artificial-intelligence/2018/03/05/you-can-take-googles-machine-learning-crash-course-for-free-now/

At last here is a logo of Europython 2018! Check the blog post for more details:
https://blog.europython.eu/post/171656128512/europython-2018-our-conference-logo

By the way, Guido van Rossum is one of the three 2018 Fellow Award honorees of the Computer History Museum (CHM) - for the creation and evolution of the Python programming language, and for leadership of its community. The CHM Fellow Awards is the Museum’s prestigious program, which has recognized such esteemed honorees as Frances Allen, Sir Tim Berners-Lee, Ed Catmull, Vint Cerf, Morris Chang, Lynn Conway, Doug Engelbart, Bjarne Stroustrup, Ken Olsen and Steve Wozniak. CHM is the world’s leading institution exploring the history of computing and its transformational impact on society. It's located in Mountain View, CA.

A few words about GIL:
https://realpython.com/blog/python/python-gil/

A little story about regular expressions and how guys used it for data investigation https://www.dataquest.io/blog/regular-expressions-data-scientists/

A descriptive benchmark of memory efficiency for parallel IO operations with different syncronous and asyncronous frameworks.
https://code.kiwi.com/memory-efficiency-of-parallel-io-operations-in-python-6e7d6c51905d

Here is a new draft of Think Complexity book:
http://greenteapress.com/wp/think-complexity-2e/

So true
https://medium.com/@webseanhickey/the-evolution-of-a-software-engineer-db854689243

When I hear that Machine Learning is an emerging tech field it freaks me out.

Logistic regression — 1958
Hidden Markov Model — 1960
Stochastic gradient descent — 1960
Support Vector Machine — 1963
k-nearest neighbors — 1967
Artificial Neural Networks — 1975
Expectation Maximization — 1977
Decision tree — 1986
Q-learning — 1989
Random forest — 1995

The logic seems to be: "if I didn't care about something important my whole life, but I care now, then it has to be emerging".