def usage_index(request):
result = progress(request)
if result is not None:
return result
start, end = get_date_range(request)
result = gen_machine_category_cache(request, start, end)
if result is not None:
return render_to_response(
'usage/progress.html',
{'task_id': result.task_id},
context_instance=RequestContext(request))
mc_list = []
for machine_category in MachineCategory.objects.all():
mc_list.append({
'obj': machine_category,
'graph': graphs.get_machine_graph_url(
start, end, machine_category),
})
return render_to_response(
'usage/mc_list.html', locals(),
context_instance=RequestContext(request))
def usage_index(request):
start, end = get_date_range(request)
mc_list = []
for machine_category in MachineCategory.objects.all():
m_list = []
for machine in machine_category.machine_set.all():
time, jobs = machine.get_usage(start, end)
if time is None:
time = 0
m_list.append({'obj': machine, 'usage': time, 'jobs': jobs})
mc_list.append({
'obj': machine_category,
'machines': m_list,
'graph': get_machine_graph_url(start, end, machine_category),
})
del m_list
return render_to_response('usage/mc_list.html', locals(), context_instance=RequestContext(request))
def index(request, machine_category_id):
if not getattr(settings, 'USAGE_IS_PUBLIC', False):
return HttpResponseForbidden('<h1>Access Denied</h1>')
machine_category = get_object_or_404(MachineCategory, pk=machine_category_id)
mc_list = MachineCategory.objects.exclude(id__exact=machine_category_id)
show_zeros = True
institute_list = Institute.active.all()
total, total_jobs = 0, 0
i_list = []
m_list = []
start, end = get_date_range(request)
available_time, avg_cpus = get_available_time(start, end, machine_category)
for m in machine_category.machine_set.all():
time, jobs = m.get_usage(start, end)
if time is None:
time = 0
m_list.append({'machine': m, 'usage': time, 'jobs': jobs})
for iq in machine_category.institutequota_set.all():
i = iq.institute
time, jobs = i.get_usage(start, end, machine_category)
if time is None:
time = 0
total = total + time
total_jobs = total_jobs + jobs
try:
quota = InstituteQuota.objects.get(institute=i, machine_category=machine_category)
display_quota = quota.quota
except InstituteQuota.DoesNotExist:
display_quota = None
else:
data_row = {'institute': i, 'usage': time, 'jobs': jobs, 'quota': display_quota}
if available_time != 0:
data_row['percent'] = Decimal(time) / Decimal(available_time) * 100
else:
data_row['percent'] = 0
if data_row['quota'] is not None:
if data_row['quota'] != 0:
data_row['p_used'] = (data_row['percent'] / data_row['quota']) * 100
else:
data_row['p_used'] = 0
data_row['diff'] = data_row['percent'] - data_row['quota']
if data_row['diff'] <= 0:
data_row['class'] = 'green'
else:
data_row['class'] = 'red'
else:
data_row['class'] = 'green'
i_list.append(data_row)
# Unused Entry
unused = {'usage': available_time - total, 'quota': 0}
try:
unused['percent'] = (unused['usage'] / available_time) * 100
except ZeroDivisionError:
unused['percent'] = 0
unused['diff'] = unused['percent'] - unused['quota'] / 100
if unused['diff'] <= 0:
unused['class'] = 'green'
else:
unused['class'] = 'red'
if available_time != 0:
utilization = (Decimal(total) / available_time) * 100
else:
utilization = 0
institutes_graph = get_institute_graph_url(start, end, machine_category)
machines_graph = get_machine_graph_url(start, end, machine_category)
trend_graph = get_trend_graph_url(start, end, machine_category)
return render_to_response('usage/usage_institute_list.html', locals(), context_instance=RequestContext(request))
def index(request, machine_category_id):
machine_category = get_object_or_404(
MachineCategory, pk=machine_category_id)
mc_list = MachineCategory.objects.exclude(id__exact=machine_category_id)
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 render_to_response(
'usage/progress.html',
{'task_id': result.task_id},
context_instance=RequestContext(request))
show_zeros = True
institute_list = Institute.active.all()
i_list = []
m_list = []
mc_cache = usage.get_machine_category_usage(machine_category, start, end)
total = mc_cache.cpu_time
total_jobs = mc_cache.no_jobs
available_time = mc_cache.available_time
avg_cpus = available_time / (60*24*24) / ((end-start).days + 1)
for m_cache in models.MachineCache.objects.filter(
machine__category=machine_category,
date=datetime.date.today(), start=start, end=end):
m = m_cache.machine
time = m_cache.cpu_time
jobs = m_cache.no_jobs
m_list.append({'machine': m, 'usage': time, 'jobs': jobs})
for i_cache in models.InstituteCache.objects.filter(
machine_category=machine_category,
date=datetime.date.today(), start=start, end=end):
i = i_cache.institute
time = i_cache.cpu_time
jobs = i_cache.no_jobs
try:
quota = InstituteQuota.objects.get(
institute=i, machine_category=machine_category)
display_quota = quota.quota
except InstituteQuota.DoesNotExist:
display_quota = None
if display_quota is None and time == 0 and jobs == 0:
continue
data_row = {
'institute': i,
'usage': time,
'jobs': jobs,
'quota': display_quota
}
if available_time != 0:
data_row['percent'] = Decimal(time) / Decimal(available_time) * 100
else:
data_row['percent'] = 0
if data_row['quota'] is not None:
if data_row['quota'] != 0:
data_row['p_used'] = (data_row['percent']
/ data_row['quota']) * 100
else:
data_row['p_used'] = None
data_row['diff'] = data_row['percent'] - data_row['quota']
if data_row['diff'] <= 0:
data_row['class'] = 'green'
else:
data_row['class'] = 'red'
else:
data_row['class'] = 'green'
data_row['diff'] = None
data_row['p_used'] = None
i_list.append(data_row)
# Unused Entry
unused = {'usage': available_time - total, 'quota': 0}
if available_time != 0:
unused['percent'] = (unused['usage'] / available_time) * 100
else:
unused['percent'] = 0
unused['diff'] = unused['percent'] - unused['quota'] / 100
if unused['diff'] <= 0:
unused['class'] = 'green'
else:
unused['class'] = 'red'
if available_time != 0:
utilization = (Decimal(total) / available_time) * 100
else:
utilization = 0
institutes_graph = graphs.get_institute_graph_url(
start, end, machine_category)
machines_graph = graphs.get_machine_graph_url(
start, end, machine_category)
trend_graph = graphs.get_trend_graph_url(
start, end, machine_category)
return render_to_response(
'usage/usage_institute_list.html', locals(),
context_instance=RequestContext(request))
