def setup(self, opts): FetchDriver.setup(self, opts) # set up the getter self.xslt = opts.get('Xslt', None) # transformation to be applied self.timefmt = opts.get("Timeformat", None) self.timezone = opts.get("Timezone", 'UTC') self.ignore_time = opts.get('IgnoreTimestamps', False) if self.xslt: with open(self.xslt, "r") as fp: self.xslt = etree.XSLT(etree.XML(fp.read()))
def setup(self, opts): """ We setup the driver by getting the parameters of scraper first and then setting up the timeseries """ FetchDriver.setup(self, opts) data = get_air_quality_init(opts={}) for i in range(0,len(data)): safar_city = self.add_timeseries('/'+data[i]['area']+'/pm2.5','AQI',description = 'PM2.5 readings for '+data[i]['area']) safar_city['Properties']['Timezone'] = 'India/Mumbai' safar_city['Metadata'] = {} safar_city['Metadata']['SourceName'] = data[i]['area'] safar_city['Metadata']['Area'] = data[i]['area'] safar_city['Metadata']['Latitude'] = data[i]['latitude'] safar_city['Metadata']['Longitude'] = data[i]['longtitude']