#!/usr/local/bin/python2.7 """ Copyright (c) 2016 Ad Schellevis All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -------------------------------------------------------------------------------------- fetch top usage from data provider """ import time import datetime import os import sys import ujson sys.path.insert(0, "/usr/local/opnsense/site-python") from lib.parse import parse_flow from lib.aggregate import BaseFlowAggregator import lib.aggregates import params app_params = {'start_time': '', 'end_time': '', 'key_fields': '', 'value_field': '', 'filter': '', 'max_hits': '', 'provider': '' } params.update_params(app_params) # handle input parameters valid_params = False if app_params['start_time'].isdigit(): start_time = int(app_params['start_time']) if app_params['end_time'].isdigit(): end_time = int(app_params['end_time']) if app_params['max_hits'].isdigit(): max_hits = int(app_params['max_hits']) if app_params['key_fields']: key_fields = app_params['key_fields'].split(',') if app_params['value_field']: value_field = app_params['value_field'] valid_params = True data_filter=app_params['filter'] timeseries=dict() if valid_params: # collect requested top result = dict() for agg_class in lib.aggregates.get_aggregators(): if app_params['provider'] == agg_class.__name__: # provider may specify multiple resolutions, we need to find the one most likely to serve the # beginning of our timeframe resolutions = sorted(agg_class.resolutions()) history_per_resolution = agg_class.history_per_resolution() for resolution in resolutions: if (resolution in history_per_resolution \ and time.time() - history_per_resolution[resolution] <= start_time ) \ or resolutions[-1] == resolution: selected_resolution = resolution break obj = agg_class(selected_resolution) result = obj.get_top_data(start_time, end_time, key_fields, value_field, data_filter, max_hits) print (ujson.dumps(result)) else: print ('missing parameters :') tmp = list() for key in app_params: tmp.append('/%s %s' % (key, app_params[key])) print (' %s %s'%(sys.argv[0], ' '.join(tmp))) print ('') print (' start_time : start time (seconds since epoch)') print (' end_time : end timestamp (seconds since epoch)') print (' key_fields : key field(s)') print (' value_field : field to sum') print (' filter : apply filter <field>=value') print (' provider : data provider classname') print (' max_hits : maximum number of hits (+1 for rest of data)') print (' sample : if provided, use these keys to generate sample data (e.g. em0,em1,em2)')