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Hi,

Thanks. It looks really interesting :)

On Mon, Apr 22, 2019 at 11:51:49AM -0500, Ben Nemec wrote:
> 
> 
> On 4/22/19 8:32 AM, Artom Lifshitz wrote:
> > tl;dr Instead of debugging with LOG.debug and/or print() statements
> > all over the place, use the pysnooper decorator [1].
> > 
> > I came across this on Hacker News this morning - if you're like me and
> > are too lazy to invest in learning a real debugger, and instead do it
> > with LOG.debug/print()s all over the place, pysnooper might be useful
> > to you. This line from the README feels particularly relevant to me ;)
> 
> I'm going to mildly object to the characterization of print and log
> debugging as "lazy". I've spent plenty of time in debuggers over the years
> and in many cases I just prefer a simple print over stepping through a huge
> number of lines of code. Both debugging techniques have their place and
> nobody should feel bad because they chose one over the other.
> 

Exactly. Imagine debugging e.g. some race condition issue. Using simple prints
may be much better in such case to find out what is going on wrong there :)

> > 
> > > What makes PySnooper stand out from all other code intelligence tools?
> > > You can use it in your sh***y, sprawling enterprise codebase without having
> > > to do any setup.
> > 
> > I tried it out with a random Nova unit test by decorating the function
> > being tested, and it gave me the expected analysis of how the function
> > executed.
> > 
> > Just sharing this, I hope it might be useful to someone :)
> 
> I've starred it. It looks a bit like bash's xtrace on steroids, which is
> something I use quite a lot when debugging bash scripts.
> 
> > 
> > [1] https://github.com/cool-RR/pysnooper
> > 
> 

-- 
Slawek Kaplonski
Senior software engineer
Red Hat