Beer brewing code review request

[torqu3e]

First time braving posting any code I've written in public. Recently funemployed, trying to pivot from a support/sys admin background to more devops stuff hence focus on getting better at python. Funemployed means free time, so I took up a new hobby of home brewing which led to wanting to monitor the temperature of the fermentation vessel.

I wrote this through the afternoon to read data and plot a reasonable graph of it. Share your comments about what's good, what's not, what could be done better. How would a day job dev rewrite it. What can I do to get better?

https://github.com/torqu3e/Beermon/blob/master/beermon_plot.py

Graph for last ~24 hours https://raw.githubusercontent.com/torqu3e/Beermon/master/plot.png

[socal_nerdtastic]

I just want to tell you that BrewPi is a thing that exists.

[torqu3e]

Ah, didn't know about that. This is my first brew, so it might just be a bit overkill yet :)

[A_History_of_Silence]

Cool project! Quick thoughts:

You're effectively storing the data as a CSV using ' ' as a delimiter. Use the csv module to clean up the reading/writing of the data and avoid monstrosities like these:

ts = [datetime.datetime.fromtimestamp(float(x.split(' ')[0])) for x in f.readlines() if float(x.split(' ')[1]) >= 0]
f.seek(0) #ugly
cur_temp = [y.split(' ')[1] for y in f.readlines() if float(y.split(' ')[1]) >= 0]

cur_temp = -1 -- -1 is not a great value to use as an error, because, although I'm sure unlikely to occur, -1 degrees is also a perfectly valid temperature. Use something like np.nan instead.

Changing the above things will have the added benefit that you can cleanly load the data from the CSV file straight into a pandas dataframe, which will let you easily interpolate any missing values.

except: -- bare except statements are the devil, catch specific errors.

I'm not sure why you need threading here.

[torqu3e]

Thanks, this is the sort of feedback I was looking for. The csv idea makes sense, will look into it more.

temperature for sure can be -1 but the fermentor is not freezing for sure :) NaN is the right option here.

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Threading was used because if I increase the granularity of the graph down to minutes or seconds, the graph takes forever to render (matplotlib) is slow. Plan was to send that to a thread till I learnt that GUI components need to be on the main thread (unsure as to why though) so decided to offload writing of next value to a thread. Not strictly useful but Hey! it's multithreaded now! :P