Self-updating graphs over time with Python and matplotlib -

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i'm not familiar matplotlib in python. want achieve plot data on time using text file receives new data every period.

the text file format following:

data,time

1,2015-07-05 11:20:00

what have far:

import matplotlib.pyplot plt import matplotlib.dates md import dateutil  pulldata = open('sampletext.txt', 'r').read() dataarray = pulldata.split('\n')  datestrings = [] plt_data = []  eachline in dataarray:     if len(eachline)>1:         y,x = eachline.split(',')         plt_data.append(int(y))         datestrings.append(x)  dates = [dateutil.parser.parse(s) s in datestrings]  plt.subplots_adjust(bottom=0.2) plt.xticks( rotation=25 )  ax=plt.gca() ax.set_xticks(dates)  xfmt = md.dateformatter('%m-%d %h:%m') ax.xaxis.set_major_formatter(xfmt) plt.plot(dates,plt_data, "o-") plt.show()

this pretty through different tutorials/previous questions.

as may see, code works plotting data on time, don't understand how can adapt in way graph update new data.

supposing text file being written to, , appended new data.

you can use inotify alerts when file modified , 'hang' function event update graph.

have @ this page, there several examples on how use pyinotify capture events. minimal example provided, shows 'structure' of program:

import pyinotify  # instantiate new watchmanager (will used store watches). wm = pyinotify.watchmanager()  # associate watchmanager notifier (will used report , # process events). notifier = pyinotify.notifier(wm)  # add new watch on /tmp all_events. wm.add_watch('/tmp', pyinotify.all_events)  # loop forever , handle events. notifier.loop()

most importantly, pyinotify.all_events can changed listen events you're interested in (such file modifications, or creation if file not exist yet)


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