Articles about programming

1. How convenient is multithreading compared to multiprocessing?

   There are basically two ways in which one can make use of a modern CPU with multiple cores for computationally intensive work.

   1. Using multiple threads within one program (multithreading).
   2. Using multiple (single-threaded) programs that communicate (multiprocessing).

   In the first case, all data is implicitly shared. In the second case, data must be explicitly shared or communicated.

   The first option is often said to be more convenient. I would like to make the case that this usually makes the task more difficult, because of the need to manage all shared data.

2. Including binary data in Python scripts

   Sometimes I need to use some binary data (e.g. a bitmap image) in a Python script. In a package, you can store this data portable in a data subdirectory of a modules using the package_data argument of setuptools.setup. This won’t work in a standalone script. You can of course make your script into a package, but here I want to show an alternative solution.

3. ImageMagick: convert vs Wand

   The ImageMagick suite has been in my software toolbox for years. It is my go-to tool for manipulating bitmap images. Over the years I have written several front-ends for specific tasks for in Python.

   In general, I have used the subprocess module to launch convert or mogrify from Python.

   With the release of Wand 0.5.0 which supports ImageMagick 7, I decided to try that by porting one of my scripts (foto4lb) to it. This turned out to be slower than using convert directly.

   But now it is 2021. Py-wand is at 0.6.7 and it is time to try again.

4. Using sqlite3 for time management

   After some initial experiments with sqlite as a replacement for a json data file format (which I did not pursue in the end), I have now started using sqlite in earnest. And I must say that I quite like it.

5. Database scheme for resin recipes

   This document explores how an SQLite database could be used to store data for the resin-calculator. Normally, the recipes are a dictionary keyed to the name of the resin. The value of each recipe is a list of (component, parts-by-weight) tuples. Since a database only contains tables, where each row has the same form, how do we store such infomation in a database?

6. Doing calculations with Python

   As an engineer I do a lot of calculations. These can be done with pen and paper and a calculator, in an IPython notebook or in a throwaway spreadsheet. All of these methods have shortcomings, though.

   Pen and paper is hard to share and (in my case) hard for others to read. In IPython you can assign the results of calculations to a variable, but you have to perform a separate action to display them. And spreadsheets in general show you the results but not the calculations.

   So I wrote a simple function in Python to help me with that. Using this function I can print both simple assignments and relatively complex calculations. And it shows both the calculation and the result.

7. Improving my Python coding

   With leading white space governing the indentation level and so the grouping of statements, Python code already looks relatively clean.

   Yet there are additional tools that will help you improve your code.

8. Structures in Python

   Sometimes I miss the C’s plain old struct in Python.

   Of course Python has dictionaries, but I prefer to write a.b over a['b'].

   Here are several ways of doing something akin to a struct in Python.

9. State machines in Python

   State machines can be relatively easy defined as a data structure.

10. Using gnuplot from Python

    According to my revision control systems (rcs in those days), I’ve been using gnuplot to make graphs since at least 2002. And I’ve got it set up via a custom gnuplotrc to match the style of the TeX documents I often use the graphs in.

    At work we have an Instron 3369 machine for material testing. Recently, I wanted to visualize some tensile test data in ways that I couldn’t get into the test report.