Refactor metering utility and view functions
Many of these functions have been copied to Tuskar-UI and then have diverged in both places. This is an attempt to consolidate these functions and eliminate any code duplication. These modifications to horizon utility and view metering functions should make it possible to delete the duplicated code from Tuskar-UI. Change-Id: Ie73b350303a3e42229d87dbbfccf7ecff859cbd7
This commit is contained in:
Ana Krivokapic
parent
f62df9a1d1
commit
bff1472f85
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@ -22,16 +22,14 @@ from horizon import exceptions
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from horizon import forms
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from horizon import tabs
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from horizon.utils import csvbase
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from horizon.utils import units
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from openstack_dashboard import api
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from openstack_dashboard.api import ceilometer
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from openstack_dashboard.dashboards.admin.metering import forms as \
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metering_forms
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from openstack_dashboard.dashboards.admin.metering import tabs as \
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metering_tabs
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from openstack_dashboard.utils import metering as utils_metering
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from openstack_dashboard.utils import metering as metering_utils
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LOG = logging.getLogger(__name__)
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@ -48,96 +46,7 @@ class CreateUsageReport(forms.ModalFormView):
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success_url = reverse_lazy('horizon:admin:metering:index')
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METER_API_MAPPINGS = {
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"instance": 'nova',
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"cpu": 'nova',
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"cpu_util": 'nova',
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"disk_read_requests": 'nova',
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"disk_write_requests": 'nova',
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"disk_read_bytes": 'nova',
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"disk_write_bytes": 'nova',
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"image": 'glance',
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"image_size": 'glance'
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}
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def get_resource_name(request, resource_id, resource_name, meter_name):
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resource = None
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try:
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if resource_name == "resource_id":
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meter_name = 'instance' if "instance" in meter_name else meter_name
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api_type = METER_API_MAPPINGS.get(meter_name, '')
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if api_type == 'nova':
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resource = api.nova.server_get(request, resource_id)
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elif api_type == 'glance':
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resource = api.glance.image_get(request, resource_id)
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except Exception:
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LOG.info(_("Failed to get the resource name: %s"), resource_id,
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exc_info=True)
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return resource.name if resource else resource_id
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class SamplesView(django.views.generic.TemplateView):
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template_name = "admin/metering/samples.csv"
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@staticmethod
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def series_for_meter(request, aggregates,
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resource_name,
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meter_name,
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stats_name,
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unit):
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"""Construct datapoint series for a meter from resource aggregates."""
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series = []
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for resource in aggregates:
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if resource.get_meter(meter_name):
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resource_id = getattr(resource, resource_name)
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point = {'unit': unit,
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'name': get_resource_name(request,
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resource_id,
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resource_name,
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meter_name),
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'data': []}
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for statistic in resource.get_meter(meter_name):
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date = statistic.duration_end[:19]
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value = float(getattr(statistic, stats_name))
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point['data'].append({'x': date, 'y': value})
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series.append(point)
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return series
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@staticmethod
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def normalize_series_by_unit(series):
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"""Transform series' values into a more human readable form:
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1) Determine the data point with the maximum value
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2) Decide the unit appropriate for this value (normalize it)
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3) Convert other values to this new unit, if necessary
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"""
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if not series:
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return series
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source_unit = target_unit = series[0]['unit']
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if not units.is_supported(source_unit):
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return series
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# Find the data point with the largest value and normalize it to
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# determine its unit - that will be the new unit
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maximum = max([d['y'] for point in series for d in point['data']])
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unit = units.normalize(maximum, source_unit)[1]
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# If unit needs to be changed, set the new unit for all data points
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# and convert all values to that unit
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if units.is_larger(unit, target_unit):
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target_unit = unit
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for i, point in enumerate(series[:]):
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if point['unit'] != target_unit:
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series[i]['unit'] = target_unit
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for j, d in enumerate(point['data'][:]):
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series[i]['data'][j]['y'] = units.convert(
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d['y'], source_unit, target_unit, fmt=True)[0]
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return series
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def get(self, request, *args, **kwargs):
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meter = request.GET.get('meter', None)
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if not meter:
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@ -152,30 +61,27 @@ class SamplesView(django.views.generic.TemplateView):
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group_by = request.GET.get('group_by', None)
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try:
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date_from, date_to = utils_metering.calc_date_args(date_from,
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date_from, date_to = metering_utils.calc_date_args(date_from,
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date_to,
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date_options)
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except Exception:
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exceptions.handle(self.request, _('Dates cannot be recognized.'))
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if group_by == 'project':
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query = utils_metering.ProjectAggregatesQuery(request,
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query = metering_utils.ProjectAggregatesQuery(request,
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date_from,
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date_to,
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3600 * 24)
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else:
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query = utils_metering.MeterQuery(request, date_from,
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query = metering_utils.MeterQuery(request, date_from,
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date_to, 3600 * 24)
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resources, unit = query.query(meter)
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resource_name = 'id' if group_by == "project" else 'resource_id'
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series = self.series_for_meter(request, resources,
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resource_name,
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meter_name,
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stats_attr,
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unit)
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series = metering_utils.series_for_meter(request, resources,
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group_by, meter,
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meter_name, stats_attr, unit)
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series = self.normalize_series_by_unit(series)
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series = metering_utils.normalize_series_by_unit(series)
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ret = {'series': series, 'settings': {}}
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return HttpResponse(json.dumps(ret), content_type='application/json')
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@ -226,13 +132,13 @@ def load_report_data(request):
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date_from = request.GET.get('date_from')
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date_to = request.GET.get('date_to')
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try:
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date_from, date_to = utils_metering.calc_date_args(date_from,
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date_from, date_to = metering_utils.calc_date_args(date_from,
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date_to,
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date_options)
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except Exception:
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exceptions.handle(request, _('Dates cannot be recognised.'))
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try:
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project_aggregates = utils_metering.ProjectAggregatesQuery(request,
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project_aggregates = metering_utils.ProjectAggregatesQuery(request,
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date_from,
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date_to,
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3600 * 24)
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@ -11,30 +11,43 @@
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# under the License.
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import datetime
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import logging
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from django.utils import timezone
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from django.utils.translation import ugettext_lazy as _
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from horizon.utils import units
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from openstack_dashboard import api
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import pytz
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def calc_period(date_from, date_to):
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LOG = logging.getLogger(__name__)
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METER_API_MAPPINGS = {
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"instance": 'nova',
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"cpu": 'nova',
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"cpu_util": 'nova',
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"disk_read_requests": 'nova',
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"disk_write_requests": 'nova',
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"disk_read_bytes": 'nova',
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"disk_write_bytes": 'nova',
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"image": 'glance',
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"image_size": 'glance'
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}
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def calc_period(date_from, date_to, number_of_samples=400):
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if date_from and date_to:
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if date_to < date_from:
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# TODO(lsmola) propagate the Value error through Horizon
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# handler to the client with verbose message.
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raise ValueError(_("To date to must be greater than From date."))
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# get the time delta in seconds
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delta = date_to - date_from
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if delta.days <= 0:
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# it's one day
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delta_in_seconds = 3600 * 24
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else:
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delta_in_seconds = delta.days * 24 * 3600 + delta.seconds
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# Lets always show 400 samples in the chart. Know that it is
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# maximum amount of samples and it can be lower.
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number_of_samples = 400
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delta_in_seconds = delta.days * 24 * 3600 + delta.seconds
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period = delta_in_seconds / number_of_samples
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else:
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# If some date is missing, just set static window to one day.
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@ -43,33 +56,116 @@ def calc_period(date_from, date_to):
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def calc_date_args(date_from, date_to, date_options):
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# TODO(lsmola) all timestamps should probably work with
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# current timezone. And also show the current timezone in chart.
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if date_options == "other":
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if date_from and not isinstance(date_from, datetime.date):
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try:
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date_from = datetime.datetime.strptime(date_from,
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"%Y-%m-%d")
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except Exception:
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raise ValueError(_("From-date is not recognized"))
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if date_to:
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if not isinstance(date_to, datetime.date):
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try:
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date_to = datetime.datetime.strptime(date_to,
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"%Y-%m-%d")
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except Exception:
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raise ValueError(_("To-date is not recognized"))
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else:
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date_to = timezone.now()
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try:
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if date_from:
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date_from = pytz.utc.localize(
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datetime.datetime.strptime(date_from, "%Y-%m-%d"))
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else:
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# TODO(lsmola) there should be probably the date
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# of the first sample as default, so it correctly
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# counts the time window. Though I need ordering
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# and limit of samples to obtain that.
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pass
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if date_to:
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date_to = pytz.utc.localize(
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datetime.datetime.strptime(date_to, "%Y-%m-%d"))
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# It returns the beginning of the day, I want the end of
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# the day, so I add one day without a second.
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date_to = (date_to + datetime.timedelta(days=1) -
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datetime.timedelta(seconds=1))
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else:
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date_to = timezone.now()
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except Exception:
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raise ValueError(_("The dates haven't been recognized"))
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else:
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try:
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date_to = timezone.now()
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date_from = date_to - datetime.timedelta(days=int(date_options))
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date_from = date_to - datetime.timedelta(days=float(date_options))
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except Exception:
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raise ValueError(_("The time delta must be an "
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"integer representing days."))
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raise ValueError(_("The time delta must be a number representing "
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"the time span in days"))
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return date_from, date_to
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def get_resource_name(request, resource_id, resource_name, meter_name):
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resource = None
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try:
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if resource_name == "resource_id":
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meter_name = 'instance' if "instance" in meter_name else meter_name
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api_type = METER_API_MAPPINGS.get(meter_name, '')
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if api_type == 'nova':
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resource = api.nova.server_get(request, resource_id)
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elif api_type == 'glance':
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resource = api.glance.image_get(request, resource_id)
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except Exception:
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LOG.info(_("Failed to get the resource name: %s"), resource_id,
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exc_info=True)
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return resource.name if resource else resource_id
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def series_for_meter(request, aggregates, group_by, meter_id,
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meter_name, stats_name, unit, label=None):
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"""Construct datapoint series for a meter from resource aggregates."""
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series = []
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for resource in aggregates:
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if resource.get_meter(meter_name):
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if label:
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name = label
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else:
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resource_name = ('id' if group_by == "project"
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else 'resource_id')
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resource_id = getattr(resource, resource_name)
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name = get_resource_name(request, resource_id,
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resource_name, meter_name)
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point = {'unit': unit,
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'name': name,
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'meter': meter_id,
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'data': []}
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for statistic in resource.get_meter(meter_name):
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date = statistic.duration_end[:19]
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value = float(getattr(statistic, stats_name))
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point['data'].append({'x': date, 'y': value})
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series.append(point)
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return series
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def normalize_series_by_unit(series):
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"""Transform series' values into a more human readable form:
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1) Determine the data point with the maximum value
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2) Decide the unit appropriate for this value (normalize it)
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3) Convert other values to this new unit, if necessary
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"""
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if not series:
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return series
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source_unit = target_unit = series[0]['unit']
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if not units.is_supported(source_unit):
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return series
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# Find the data point with the largest value and normalize it to
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# determine its unit - that will be the new unit
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maximum = max([d['y'] for point in series for d in point['data']])
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unit = units.normalize(maximum, source_unit)[1]
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# If unit needs to be changed, set the new unit for all data points
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# and convert all values to that unit
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if units.is_larger(unit, target_unit):
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target_unit = unit
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for i, point in enumerate(series[:]):
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if point['unit'] != target_unit:
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series[i]['unit'] = target_unit
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for j, d in enumerate(point['data'][:]):
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series[i]['data'][j]['y'] = units.convert(
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d['y'], source_unit, target_unit, fmt=True)[0]
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return series
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class ProjectAggregatesQuery(object):
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def __init__(self, request, date_from, date_to,
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period=None, additional_query=[]):
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