Is there existing code to log-with-bells-on for runtime algorithm diagnostics?

Rob Clewley rob.clewley at
Tue Apr 21 21:02:02 CEST 2015


I'm in need of a system for logging the step-wise results and
diagnostic metadata about a python function implementation of an
algorithm that I'm developing. The specific algorithm is not of great
consequence except that it's for scientific computing and may produce
large (e.g., '00s or maybe '000s, but not "big data" scale) amounts of
intermediate numerical data that can be complex to understand when
debugging its progress.

In fact, I'm trying to build a general purpose tool for exploring the
inner workings of numerical algorithms for teaching and learning
purposes, e.g. for graduate student training or for figuring out
parameter choices in difficult applications.

I want to be able to insert commands inside of the loops that log
certain variable states, completed stages of the algorithm (assume
it's hierarchical), text warnings, and possibly even 'pointers' to
graphical output objects of some of the intermediate data (e.g.
matplotlib object handles for lines, points). Then I can trace the
work done afterwards or step through the process in an IDE debugger
and make interactive calls to access recent steps, plot certain
relationships in the current state, etc. The basic logger's "levels"
of output don't really apply here. I at least want categories, if not
hierarchical sub-categories.

I don't think the built-in logger is sophisticated enough for this,
being a flat record of freeform text AFAIU, but the API looks

I'm considering an in-memory sqlite DB to store structured records at
any logged step, and an accompanying dictionary to store references to
any python object metadata, keyed by a unique ID in the DB log. Then
I'd write an API for it that resembles the logger's.

It's not super hard for me to write my own thing here, but I'm
wondering if anyone has come across any existing solutions in this
vein, or has any advice before I go further in designing a solution? I
can't really believe that no-one has attempted this before, but it's
been really hard to find any existing work through online search.


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