def pie_chart(request):
suites = TestSuite.objects.raw('select *, max(date_run) '
'from reporter_testsuite group by '
'suite_name')
plot_values = {'total': 0, 'passed': 0, 'skipped': 0, 'failed': 0}
for suite in suites:
plot_values['total'] += suite.num_tests
plot_values['passed'] += suite.num_passed
plot_values['skipped'] += suite.num_skipped
plot_values['failed'] += suite.num_failed
labels = 'Passed', 'Skipped', 'Failed'
sizes = [
plot_values['passed'], plot_values['skipped'], plot_values['failed']
]
colors = ['#086788', '#FDF0D5', '#EB5E55']
explode = (0, 0.1, 0)
fig = pyplot.figure(0)
# Plot
fig.add_subplot = pyplot.pie(sizes,
explode=explode,
labels=labels,
colors=colors,
autopct='%1.1f%%',
shadow=False,
startangle=140)
fig.add_axes = pyplot.axis('equal')
figCanvas = FigureCanvas(fig)
response = HttpResponse(content_type='image/png')
figCanvas.print_png(response)
return response
axs[0, 0].xaxis.set_major_locator(fmt_month)
axs[0, 0].xaxis.set_major_formatter(date_form)
fig.suptitle('Thailand COVID data up to ' + last_updated +
'\n Data from https://github.com/djay/covidthailand')
if plot_save == True:
fig.savefig('full_figure.png')
if plot_upload == True:
canvas = FigureCanvas(fig) # renders figure onto canvas
imdata = io.BytesIO(
) # prepares in-memory binary stream buffer (think of this as a txt file but purely in memory)
canvas.print_png(
imdata
) # writes canvas object as a png file to the buffer. You can also use print_jpg, alternatively
s3.Object('covidviz', 'full_figure.png').put(Body=imdata.getvalue(),
ContentType='image/png')
s3.ObjectAcl('covidviz', 'full_figure.png').put(ACL='public-read')
# narrow plot for mobile screen
fig, axs = plt.subplots(6, 1, figsize=(6, 9.5), sharex=True)
axs[0].bar(df['Date'], df['Cases'], 1, label='cases')
axs[0].set_title(f'Daily New Cases: {latest_new_confirmed:,d}')
axs[0].set(ylabel="")
axs[0].yaxis.set_major_formatter(ticker.EngFormatter())
axs[1].bar(df['Date'], df['Tested'], 1, label='tested')
