def project_usage(request, project_id, machine_category_id):
machine_category = get_object_or_404(MachineCategory, pk=machine_category_id)
project = get_object_or_404(Project, pid=project_id)
if not project.can_view(request.user) and not getattr(settings, 'USAGE_IS_PUBLIC', False):
return HttpResponseForbidden('<h1>Access Denied</h1>')
result = progress(request)
if result is not None:
return result
start, end = get_date_range(request)
result = gen_cache_for_machine_category(request, start, end, machine_category)
if result is not None:
return result
result = gen_cache_for_project(request, start, end, project, machine_category)
if result is not None:
return result
usage_list = []
total, total_jobs = 0, 0
# Custom SQL as need to get users that were removed from project too
rows = CPUJob.objects.filter(
project=project,
machine__category=machine_category,
date__range=(start, end)
).values('account').annotate().order_by('account')
for row in rows:
u = Account.objects.get(id=row['account']).person
time, jobs = usage.get_person_usage(u, project, start, end, machine_category)
if time:
total += time
total_jobs += jobs
if jobs > 0:
usage_list.append({'person': u, 'usage': time, 'jobs': jobs})
for u in usage_list:
if total == 0:
u['percent'] = 0
else:
u['percent'] = (u['usage'] / total) * 100
usage_list = dictsortreversed(usage_list, 'usage')
count = 0
for i in usage_list:
i['colour'] = graphs.get_colour(count)
count += 1
graph = graphs.get_project_trend_graph_url(project, start, end, machine_category)
return render_to_response('usage/project_usage.html', locals(), context_instance=RequestContext(request))
def _gen_project_trend_graph(project,
start,
end,
machine_category,
force_overwrite=False):
"""Generates a bar graph for a project
Keyword arguments:
project -- Project
start -- start date
end -- end date
machine_category -- MachineCategory object
"""
filename = graphs.get_project_trend_graph_filename(project,
start, end, machine_category)
csv_filename = os.path.join(settings.GRAPH_ROOT, filename + '.csv')
png_filename = os.path.join(settings.GRAPH_ROOT, filename + '.png')
_check_directory_exists(csv_filename)
_check_directory_exists(png_filename)
if not settings.GRAPH_DEBUG or force_overwrite:
if os.path.exists(csv_filename):
if os.path.exists(png_filename):
return
rows = CPUJob.objects.filter(
project=project,
machine__category=machine_category,
date__range=(start, end)
).values('account', 'account__username', 'date').annotate(Sum('cpu_usage')).order_by('account', 'date')
t_start = start
t_end = end
start_str = start.strftime('%Y-%m-%d')
end_str = end.strftime('%Y-%m-%d')
fig, ax = plt.subplots(figsize=(6, 4))
ax.set_xlim(start, end + datetime.timedelta(days=1))
ax.set_title('%s %s - %s' % (project.pid, start_str, end_str))
ax.set_ylabel("CPU Time (hours)")
ax.set_xlabel("Date")
locator = mdates.AutoDateLocator()
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))
ax.xaxis.set_minor_locator(mdates.DayLocator())
data = {}
x_data = {}
y_data = {}
with open(csv_filename, 'wb') as csv_file:
csv_writer = csv.writer(csv_file)
for row in rows.iterator():
csv_writer.writerow([
row['account__username'],
row['date'], row['cpu_usage__sum']/3600.00
])
account = row['account']
date = row['date']
if account not in data:
data[account] = {}
x_data[account] = []
y_data[account] = []
data[account][date] = row['cpu_usage__sum']
for account, dates in data.iteritems():
start = t_start
end = t_end
while start <= end:
total = 0
if start in dates:
total = dates[start]
x_data[account].append(start)
y_data[account].append(total / 3600.00)
start = start + datetime.timedelta(days=1)
del data
totals = []
start = t_start
end = t_end
while start <= end:
totals.append(0)
start = start + datetime.timedelta(days=1)
count = 0
for account in x_data.keys():
ax.bar(
x_data[account], y_data[account],
bottom=totals,
color=graphs.get_colour(count),
edgecolor=graphs.get_colour(count),
align='edge')
count = count + 1
i = 0
start = t_start
end = t_end
while start <= end:
totals[i] += y_data[account][i]
i = i + 1
start = start + datetime.timedelta(days=1)
del x_data
del y_data
del totals
fig.autofmt_xdate()
plt.tight_layout()
plt.savefig(png_filename)
plt.close()
