I'm trying to build a small website, using django, that stores network
performance data. The user will be able to use filters to retrieve the
exact data he/she wants and then have the option to graph that data. I'm
using django-pandas to convert filtered queryset to a dataframe and from
there to create a plot. Everything works fine the first time the plot
function is called. When the plot function is called a second time, the
python web server just hangs (started from python2.7.exe manage.py
runserver).
Here is the django view function:
def FilteredPerformanceChartsView(request):
f = PerfvRtrOnlyFilter(request.GET, queryset=PerfvRtrOnly.objects.all())
df = read_frame(f.qs, fieldnames=['runDate', 'deviceName', 'aggrPPS',
'jdmVersion'])
#################################################################
# Let's pass the Pandas DataFrame off to a seperate function for
# further processing and to generate a chart.
# This should return an image (png or jpeg)
#################################################################
chart = pandas_generate_chart(f.qs)
return render(request,
'performance_charts.html',
context={'filter': f,
'chart': chart,
'dataFrame': df,
},
)
The function *pandas_generate_chart* is where the problem is. After
performing a lot of troubleshooting, what appears to trigger the hang is
calling df.plot a second time. In other words, when the user hits the
button to generate a different chart. Until that second request to generate
a chart is submitted, the website still works perfect. You will also notice
that plt.close() is commented out below. If I uncomment that out, the
webserver will hang the first time this function is called. (Note, it will
display the chart). I've been looking into the pyplot interactive vs
non-interactive modes to see if that was the cause of the problem. From the
troubleshooting I've done, it is running in non-interactive mode.
def pandas_generate_chart(filtered_queryset):
df = read_frame(filtered_queryset, fieldnames=['jdmVersion', 'hardware',
'deviceName', 'aggrPPS'])
df = df.set_index('jdmVersion')
# Plot
myplot = df.plot(kind='barh', figsize=(12,7), grid=True)
myplot.set_ylabel('JDM Version')
format="png"
sio_file = StringIO()
plt.savefig(sio_file, format=format)
image = base64.b64encode(sio_file.getvalue())# plt.close()
sio_file.close()
return image
Thank you for your help...
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