Python

For particle physicists, ROOT is one of the most important toolkits around. It is a huge suite of tools that predates the C++ standard library, and has almost anything a particle physicist could want. It has driven developments in other areas too. ROOT’s current C++ interpreter, CLING, is the most powerful C++ interpreter available and is used by the Xeus project for Jupyter. The Python work has helped PyPy, with CPPYY also coming from ROOT. However, due to the size, complexity, and age of some parts of ROOT, it can be a bit challenging to install; and it is even more challenging when you want it to talk to Python. I would like to point to the brand-new Conda-Forge ROOT package for Linux and macOS, and point out a few other options for macOS installs. Note for Windows users: Due to the fact that ROOT expects the type long to match the system pointer size, 64-bit Windows cannot be supported for quite some time. While you can use it in 32 bit form, this is generally impossible to connect to Python, which usually will be a 64-bit build.

These are some illustrations and videos that I have made over the years.

Let’s compare several ways of making Histograms. I’m going to assume you would like to end up with a nice OO histogram interface, so all the 2D methods will fill a Physt histogram. We will be using a 2 x 1,000,000 element array and filling a 2D histogram, or 10,000,000 elements in a 1D histogram. Binnings are regular.

1D 10,000,000 item histogram

2D 1,000,000 item histogram

Let’s try a non-trivial example of a binding: Minuit2 (6.14.0 standalone edition).

This was originally given as a PyHEP 2018 talk. It is designed to be interactive, and can be run in SWAN if you have a CERN account. If you want to run it manually, just download the repository: github.com/henryiii/pybindings_cc. It is easy to run in Anaconda.

About ten years ago, Guido Van Rossum, the Python author and Benevolent Dictator for Life (BDFL), along with the Python community, decided to make several concurrent backward incompatible changes to Python 2.5 and release a new version, Python 3.0.

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 mostly¹ 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.).

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.