A simple introduction to Asyncio

This is a simple explanation of the asyncio module and new supporting language features in Python 3.5. Even though the new keywords async and await are new language constructs, they are mostly* useless without an event loop, and that is supplied in the standard library as asyncio. Also, you need awaitable functions, which are only supplied by asyncio (or in the growing set of async libraries, like asyncssh, quamash etc.).

Note: My previous post uses these without the asyncio event loop. But you should not normally do that.

A little example of how Asyncio works

This is a simple example to show how Asyncio works without using Asyncio itself, instead using a basic and poorly written event loop. This is only meant to give a flavor of what Asyncio does behind the curtains. I'm avoiding most details of the library design, like callbacks, just to keep this simple. Since this is written as an illustration, rather than real code, I'm going to dispense with trying to keep it 2.7 compatible.

Feynman Diagrams in Tikz

There is a package for making Feynman diagrams in LaTeX. Unfortunately, it is old and dvi latex only. If you are using pdflatex or lualatex, as you should be, it does not work. Even in regular LaTeX, it's a bit of a pain. Why is there not a new package for pdflatex? Turns out, you don't need one. Due to the powerful drawing library Tikz, you can create any diagram easily, and can customize it completely. For example:

Including CRY cosmic ray generator in CMake

I realized that CRY did not have a CMake based install option, so including it in a GEANT4 cmake project might not be obvious. This is how you would do it in your CMakeLists.txt:

GTest Submodule

Note: There is a better way to do this described here.

If you've ever tried apt-get or brew to try to install gtest, you arer probably familiar with the fact that gtest is not "recommend" for global install on your system. As an alternitive, the recommendation is that you make it part of your project. The process for making gtest part of your project, however, is not well documented, at least for modern git projects. What follows is the procedure I used to do so.

Slots in Python

Slots seem to be poorly documented. What they do is simple, but whether they are used is tricky. This is a little mini-post on slots.

Basics of Metaclasses

This is a quick tutorial over the basics of what metaclasses do.

The Metaclass¶

Metaclasses, while seemingly a complex topic, really just do something very simple. They control what happens when you have code that turns into a class object. The normal place they are executed is right after the class statement. Let's see that in action by using print as our metaclass.

Note: this post uses Python 3 metaclass notation. Python 2 uses assignment to a special __metaclass__ attribute to set the metaclass. Also, Python 2 requires explicit, 2 argument super() calls.

In [13]:

class WillNotBeAClass(object, metaclass=print):
    x=1

WillNotBeAClass (<class 'object'>,) {'x': 1, '__module__': '__main__', '__qualname__': 'WillNotBeAClass'}

Here, we have replaced the metaclass (type) with print, just to investigate how it works. This is quite useless, of course, but does show that the metaclass gets called with three arguments when a class is created. The first is the name of the class to be created, the second is a tuple of base classes, and the third is a dictionary that has the namespace of the body of a class, with a few extra special values added.