def open_page(self):
if not self.startdt:
self.startdt = self.push_hist
if not self.enddt:
self.enddt = dtutil.now()
start, end = urllib.quote(dtutil.strftime_tz(self.startdt, TIMEFMT)), \
urllib.quote(dtutil.strftime_tz(self.enddt, TIMEFMT))
url = self.url % (start, end)
url += "&mnuStartMonth=%i&mnuStartDay=%i&mnuStartYear=%i" % \
(self.startdt.month,
self.startdt.day,
self.startdt.year)
url += "&mnuStartTime=%i%%3A%i" % (self.startdt.hour,
self.startdt.minute)
url += "&mnuEndMonth=%i&mnuEndDay=%i&mnuEndYear=%i" % \
(self.enddt.month,
self.enddt.day,
self.enddt.year)
url += "&mnuEndTime=%i%%3A%i" % (self.enddt.hour, self.enddt.minute)
log.msg("loading " + url)
# send the auth preemptively to avoid the 403-redirect cycle...
auth = "Basic " + base64.encodestring(":".join(self.auth))[:-1]
d = self.agent.request("GET", url,
Headers({"Authorization": [auth]}))
d.addCallback(self.get_response)
return d
def open_page(self):
if not self.startdt:
self.startdt = self.push_hist
if not self.enddt:
self.enddt = dtutil.now()
start, end = urllib.quote(dtutil.strftime_tz(self.startdt, TIMEFMT)), \
urllib.quote(dtutil.strftime_tz(self.enddt, TIMEFMT))
url = self.url % (start, end)
url += "&mnuStartMonth=%i&mnuStartDay=%i&mnuStartYear=%i" % \
(self.startdt.month,
self.startdt.day,
self.startdt.year)
url += "&mnuStartTime=%i%%3A%i" % (self.startdt.hour,
self.startdt.minute)
url += "&mnuEndMonth=%i&mnuEndDay=%i&mnuEndYear=%i" % \
(self.enddt.month,
self.enddt.day,
self.enddt.year)
url += "&mnuEndTime=%i%%3A%i" % (self.enddt.hour, self.enddt.minute)
print "loading", url
self.fp = httputils.load_http(url, as_fp=True, auth=auth.BMOAUTH)
if not self.fp:
raise core.SmapException("timeout!")
self.reader = csv.reader(self.fp, dialect='excel-tab')
header = self.reader.next()
if len(header) == 0:
print "Warning: no data from", self.url
raise core.SmapException("no data!")
try:
self.field_map, self.map = make_field_idxs(self.meter_type,
header,
location=self.location)
except:
traceback.print_exc()
if not self.added:
self.added = True
for channel in self.map['sensors'] + self.map['meters']:
try:
self.add_timeseries('/%s/%s' % channel[2:4],
channel[4],
data_type='double')
self.set_metadata(
'/%s/%s' % channel[2:4], {
'Extra/ChannelName':
re.sub('\(.*\)', '', channel[0]).strip(),
})
except:
traceback.print_exc()
def open_page(self):
if not self.startdt:
self.startdt = self.push_hist
if not self.enddt:
self.enddt = dtutil.now()
start, end = urllib.quote(dtutil.strftime_tz(self.startdt, TIMEFMT)), \
urllib.quote(dtutil.strftime_tz(self.enddt, TIMEFMT))
url = self.url % (start, end)
url += "&mnuStartMonth=%i&mnuStartDay=%i&mnuStartYear=%i" % \
(self.startdt.month,
self.startdt.day,
self.startdt.year)
url += "&mnuStartTime=%i%%3A%i" % (self.startdt.hour,
self.startdt.minute)
url += "&mnuEndMonth=%i&mnuEndDay=%i&mnuEndYear=%i" % \
(self.enddt.month,
self.enddt.day,
self.enddt.year)
url += "&mnuEndTime=%i%%3A%i" % (self.enddt.hour, self.enddt.minute)
print "loading", url
self.fp = httputils.load_http(url, as_fp=True, auth=auth.BMOAUTH)
if not self.fp:
raise core.SmapException("timeout!")
self.reader = csv.reader(self.fp, dialect='excel-tab')
header = self.reader.next()
if len(header) == 0:
print "Warning: no data from", self.url
raise core.SmapException("no data!")
try:
self.field_map, self.map = make_field_idxs(self.meter_type, header,
location=self.location)
except:
traceback.print_exc()
if not self.added:
self.added = True
for channel in self.map['sensors'] + self.map['meters']:
try:
self.add_timeseries('/%s/%s' % channel[2:4], channel[4], data_type='double')
self.set_metadata('/%s/%s' % channel[2:4], {
'Extra/ChannelName' : re.sub('\(.*\)', '', channel[0]).strip(),
})
except:
traceback.print_exc()
def make_time_formatter(request, stags):
"""Return a function that propertly formats timestamps for a
particular request.
"""
if 'timefmt' in request.args:
try:
tz = stags['Properties']['Timezone']
except KeyError:
tz = 'Utc'
tz = dtutil.gettz(tz)
# potentially do timestamp stringification here.
# this could be a bit slow for large datasets...
if request.args['timefmt'][0] == 'iso8601':
fmt = dtutil.iso8601
elif request.args['timefmt'][0] == 'excel':
fmt = fmt = dtutil.excel
else:
fmt = lambda dt, tz: dtutil.strftime_tz(dt, '%s')
tz = dtutil.gettz('Utc')
def format(t):
return fmt(dtutil.ts2dt(t / 1000), tz)
return format
else:
return lambda x: str(int(x))
def write_one_stream(self, request, stream, stags, mime_header=False):
"""For a CSV downlod, add some hweaders and write the data to the stream
"""
writer = csv.writer(request)
if 'tags' in request.args and not 'none' in request.args['tags']:
request.write("# uuid: %s\n" % stream['uuid'])
request.write("# DownloadTime: " + time.ctime() + "\n")
request.write("# ")
request.write('\n# '.join(
(': '.join(x) for x in sorted(stags.iteritems()))))
request.write('\n')
if 'timefmt' in request.args:
# potentially do timestamp stringification here.
# this could be a bit slow for large datasets...
if request.args['timefmt'][0] == 'iso8601':
fmt = dtutil.iso8601
tz = dtutil.gettz(stags.get('Properties/Timezone', 'Utc'))
elif request.args['timefmt'][0] == 'excel':
fmt = fmt = dtutil.excel
tz = dtutil.gettz(stags.get('Properties/Timezone', 'Utc'))
else:
fmt = lambda dt, tz: dtutil.strftime_tz(dt, '%s')
tz = dtutil.gettz('Utc')
def row_action(row):
row[0] = fmt(dtutil.ts2dt(row[0] / 1000), tz)
writer.writerow(row)
map(row_action, stream['Readings'])
else:
map(writer.writerow, stream['Readings'])
def write_one_stream(self, request, stream, stags, mime_header=False):
"""For a CSV downlod, add some hweaders and write the data to the stream
"""
writer = csv.writer(request)
if 'tags' in request.args and not 'none' in request.args['tags']:
request.write("# uuid: %s\n" % stream['uuid'])
request.write("# DownloadTime: " + time.ctime() + "\n")
request.write("# ")
request.write('\n# '.join((': '.join(x) for x in sorted(stags.iteritems()))))
request.write('\n')
if 'timefmt' in request.args:
# potentially do timestamp stringification here.
# this could be a bit slow for large datasets...
if request.args['timefmt'][0] == 'iso8601':
fmt = dtutil.iso8601
tz = dtutil.gettz(stags.get('Properties/Timezone', 'Utc'))
elif request.args['timefmt'][0] == 'excel':
fmt = fmt = dtutil.excel
tz = dtutil.gettz(stags.get('Properties/Timezone', 'Utc'))
else:
fmt = lambda dt, tz: dtutil.strftime_tz(dt, '%s')
tz = dtutil.gettz('Utc')
def row_action(row):
row[0] = fmt(dtutil.ts2dt(row[0] / 1000), tz)
writer.writerow(row)
map(row_action, stream['Readings'])
else:
map(writer.writerow, stream['Readings'])
def make_time_formatter(request, stags):
"""Return a function that propertly formats timestamps for a
particular request.
"""
if 'timefmt' in request.args:
try:
tz = stags['Properties']['Timezone']
except KeyError:
tz = 'Utc'
tz = dtutil.gettz(tz)
# potentially do timestamp stringification here.
# this could be a bit slow for large datasets...
if request.args['timefmt'][0] == 'iso8601':
fmt = dtutil.iso8601
elif request.args['timefmt'][0] == 'excel':
fmt = fmt = dtutil.excel
else:
fmt = lambda dt, tz: dtutil.strftime_tz(dt, '%s')
tz = dtutil.gettz('Utc')
def format(t):
return fmt(dtutil.ts2dt(t / 1000), tz)
return format
else:
return lambda x: str(int(x))
def writeDROMScsv(self, value):
fcsv = open('meterdata.csv','w')
fcsv.write(','.join(['DateTime', 'MeterId', 'Value1', 'Value2']) + '\n')
for path, val in value:
if not 'Readings' in val: continue
cmps = split_path(path)
channel = join_path(cmps[1:])
for d in val['Readings']:
if d is None: continue
ts = dtutil.strftime_tz(dtutil.ts2dt(d[0] / 1000), "%Y-%m-%d %H:%M", tzstr='Local')
if ts is None: continue
v = d[1]
if v is None: continue
if val['Properties']['UnitofMeasure']=='Watts': v /= 1000.
v /= 4. # approximate kWh
fcsv.write(','.join([ts,channel,str(v)]) + '\n')
fcsv.close()
def read(self):
all_readings = self.client.latest(self.tempwhere)
for p in all_readings:
print '-'*20
md = self.client.tags('uuid = "'+p['uuid']+'"')[0]
print 'Room:', md['Metadata/Room']
print 'Reading:', p['Readings'][0][1]
ts = dtutil.ts2dt(p['Readings'][0][0]/1000)
print 'Time:', dtutil.strftime_tz(ts, tzstr='America/Los_Angeles')
avg_room_temp = sum([x['Readings'][0][1] for x in all_readings]) / float(len(all_readings))
# get difference between avg room temperature and thermostat temperature
new_diff = self.therm_temp - avg_room_temp
# periodically update output streams. Here a bogus adjustment
self.add('/heatSetpoint', self.heatSP + new_diff)
self.add('/coolSetpoint', self.coolSP + new_diff)
print "zone controller publish: ", self.heatSP, self.coolSP
"""
test script
"""
import glob
import os
from smap.contrib import dtutil
dir = "/Users/hdz_1989/Downloads/SDB/Todai/"
list = glob.glob(dir + '/*.dat')
f = open(dir + 'sample/' + 'ts_checking.txt', 'w')
for i in list:
fp = open(i, 'r')
j = 0
while j<3:
rd = fp.readline()
ts = float(rd.strip('\n').split()[0])
time = dtutil.strftime_tz(dtutil.ts2dt(ts), "%m-%d-%Y %H:%M:%S")
f.write("%s, " %time)
j += 1
rd = fp.readline()
ts = float(rd.strip('\n').split()[0])
time = dtutil.strftime_tz(dtutil.ts2dt(ts), "%m-%d-%Y %H:%M:%S")
f.write("%s\n" %time)
fp.close()
f.close()
def get_readings(self, market, start_date, stop_date):
readings = {'total_price': [], 'loss': [], 'energy': [], 'congestion': []}
print "get_readings", market
if market == 'DAM':
q = 'PRC_LMP'
m = 'DAM'
elif market == 'HASP':
q = 'PRC_HASP_LMP'
m = 'HASP'
elif market == 'RTM':
q = 'PRC_INTVL_LMP'
m = 'RTM'
else:
raise Exception("Invalid market: " + market)
url = 'http://oasis.caiso.com/mrtu-oasis/SingleZip?'
url += 'queryname=' + q
url += '&startdate=' + dtutil.strftime_tz(start_date, '%Y%m%d', 'US/Pacific')
url += '&enddate=' + dtutil.strftime_tz(stop_date, '%Y%m%d', 'US/Pacific')
url += '&market_run_id=' + m
url += '&node=' + self.location
logging.info("Get url %s" % url)
h = None
for d in [5, 20, 60]:
try:
h = urllib2.urlopen(url, timeout=50)
break
except urllib2.URLError:
logging.warn("urlopen failed.")
time.sleep(d)
if h == None:
raise Exception("Failed to open url: %s" % url)
z = zipfile.ZipFile(StringIO.StringIO(h.read()))
xml = z.read(z.namelist()[0])
b = BeautifulSoup.BeautifulSoup(xml)
sec_per_int = int( b.find('m:sec_per_interval').contents[0] )
rows = b.findAll('m:report_data')
for d in rows:
res = d.find('m:resource_name').contents[0]
item = d.find('m:data_item').contents[0]
day = d.find('m:opr_date').contents[0]
inter = int( d.find('m:interval_num').contents[0] )
val = float( d.find('m:value').contents[0] )
secs = (inter - 1) * sec_per_int
dt = dtutil.strptime_tz(day, '%Y-%m-%d', 'US/Pacific') + datetime.timedelta(seconds=secs)
timestamp = dtutil.dt2ts(dt)
key = None
if item == 'LMP_PRC':
key = 'total_price'
elif item == 'LMP_LOSS_PRC':
key = 'loss'
elif item == 'LMP_ENE_PRC':
key = 'energy'
elif item == 'LMP_CONG_PRC':
key = 'congestion'
else:
continue
readings[key].append((timestamp, val))
num_readings = len(readings[readings.keys()[0]])
for k in readings.keys():
if len(readings[k]) != num_readings:
raise Exception('Missing readings')
readings[k] = sorted(readings[k], key=lambda (t, v): t)
return readings
def get_readings(self, market, start_date, stop_date):
readings = {
'total_price': [],
'loss': [],
'energy': [],
'congestion': []
}
print "get_readings", market
if market == 'DAM':
q = 'PRC_LMP'
m = 'DAM'
elif market == 'HASP':
q = 'PRC_HASP_LMP'
m = 'HASP'
elif market == 'RTM':
q = 'PRC_INTVL_LMP'
m = 'RTM'
else:
raise Exception("Invalid market: " + market)
url = 'http://oasis.caiso.com/mrtu-oasis/SingleZip?'
url += 'queryname=' + q
url += '&startdate=' + dtutil.strftime_tz(start_date, '%Y%m%d',
'US/Pacific')
url += '&enddate=' + dtutil.strftime_tz(stop_date, '%Y%m%d',
'US/Pacific')
url += '&market_run_id=' + m
url += '&node=' + self.location
logging.info("Get url %s" % url)
h = None
for d in [5, 20, 60]:
try:
h = urllib2.urlopen(url, timeout=50)
break
except urllib2.URLError:
logging.warn("urlopen failed.")
time.sleep(d)
if h == None:
raise Exception("Failed to open url: %s" % url)
z = zipfile.ZipFile(StringIO.StringIO(h.read()))
xml = z.read(z.namelist()[0])
b = BeautifulSoup.BeautifulSoup(xml)
sec_per_int = int(b.find('m:sec_per_interval').contents[0])
rows = b.findAll('m:report_data')
for d in rows:
res = d.find('m:resource_name').contents[0]
item = d.find('m:data_item').contents[0]
day = d.find('m:opr_date').contents[0]
inter = int(d.find('m:interval_num').contents[0])
val = float(d.find('m:value').contents[0])
secs = (inter - 1) * sec_per_int
dt = dtutil.strptime_tz(
day, '%Y-%m-%d',
'US/Pacific') + datetime.timedelta(seconds=secs)
timestamp = dtutil.dt2ts(dt)
key = None
if item == 'LMP_PRC':
key = 'total_price'
elif item == 'LMP_LOSS_PRC':
key = 'loss'
elif item == 'LMP_ENE_PRC':
key = 'energy'
elif item == 'LMP_CONG_PRC':
key = 'congestion'
else:
continue
readings[key].append((timestamp, val))
num_readings = len(readings[readings.keys()[0]])
for k in readings.keys():
if len(readings[k]) != num_readings:
raise Exception('Missing readings')
readings[k] = sorted(readings[k], key=lambda (t, v): t)
return readings
class CaIsoPrice(SmapDriver):
MARKETS = [('DAM', 30 * 60, 'Day-ahead market'),
('HASP', 10 * 60, 'Hour-ahead scheduling process'),
('RTM', 2 * 60, 'Real-time market')]
FEEDS = [('total_price', '$', 'total price'), ('loss', '$', 'loss price'),
('congestion', '$', 'congestion price'),
('energy', '$', 'energy price')]
def setup(self, opts):
# get our location
self.last_reading = {}
for m, t, d in self.MARKETS:
self.last_reading[m] = 0
self.location = opts.get('Location', 'OAKLAND_1_N001')
self.set_metadata(
'/', {
'Location/Uri': 'http://oasis.caiso.com/mrtu-oasis/SingleZip',
'Extra/IsoNode': self.location,
'Extra/Driver': 'smap.drivers.caiso_price.CaIsoPrice'
})
# add the feeds
for (m, i, md) in self.MARKETS:
for (f, u, fd) in self.FEEDS:
path = '/%s/%s' % (m, f)
self.add_timeseries(path,
u,
data_type='double',
description=md + ' ' + fd)
def start(self):
for (market, interval, description) in self.MARKETS:
periodicSequentialCall(self.poll_stream, market,
False).start(interval)
def get_readings(self, market, start_date, stop_date):
readings = {
'total_price': [],
'loss': [],
'energy': [],
'congestion': []
}
print "get_readings", market
if market == 'DAM':
q = 'PRC_LMP'
m = 'DAM'
elif market == 'HASP':
q = 'PRC_HASP_LMP'
m = 'HASP'
elif market == 'RTM':
q = 'PRC_INTVL_LMP'
m = 'RTM'
else:
raise Exception("Invalid market: " + market)
url = 'http://oasis.caiso.com/mrtu-oasis/SingleZip?'
url += 'queryname=' + q
url += '&startdate=' + dtutil.strftime_tz(start_date, '%Y%m%d',
'US/Pacific')
url += '&enddate=' + dtutil.strftime_tz(stop_date, '%Y%m%d',
'US/Pacific')
url += '&market_run_id=' + m
url += '&node=' + self.location
logging.info("Get url %s" % url)
h = None
for d in [5, 20, 60]:
try:
h = urllib2.urlopen(url, timeout=50)
break
except urllib2.URLError:
logging.warn("urlopen failed.")
time.sleep(d)
if h == None:
raise Exception("Failed to open url: %s" % url)
z = zipfile.ZipFile(StringIO.StringIO(h.read()))
xml = z.read(z.namelist()[0])
b = BeautifulSoup.BeautifulSoup(xml)
sec_per_int = int(b.find('m:sec_per_interval').contents[0])
rows = b.findAll('m:report_data')
for d in rows:
res = d.find('m:resource_name').contents[0]
item = d.find('m:data_item').contents[0]
day = d.find('m:opr_date').contents[0]
inter = int(d.find('m:interval_num').contents[0])
val = float(d.find('m:value').contents[0])
secs = (inter - 1) * sec_per_int
dt = dtutil.strptime_tz(
day, '%Y-%m-%d',
'US/Pacific') + datetime.timedelta(seconds=secs)
timestamp = dtutil.dt2ts(dt)
key = None
if item == 'LMP_PRC':
key = 'total_price'
elif item == 'LMP_LOSS_PRC':
key = 'loss'
elif item == 'LMP_ENE_PRC':
key = 'energy'
elif item == 'LMP_CONG_PRC':
key = 'congestion'
else:
continue
readings[key].append((timestamp, val))
num_readings = len(readings[readings.keys()[0]])
for k in readings.keys():
if len(readings[k]) != num_readings:
raise Exception('Missing readings')
readings[k] = sorted(readings[k], key=lambda (t, v): t)
return readings
def poll_stream(self, market, load_old):
def _push_data(readings, market):
# Zip together the values for all keys
for vals in zip(*readings.values()):
if vals[0][0] > self.last_reading[market]:
# Add all smap points for this time
for (k, v) in zip(readings.keys(), vals):
logging.debug("add /%s/%s: %s" % (market, k, str(v)))
self.add('/%s/%s' % (market, k), *v)
self.last_reading[market] = vals[0][0]
# Load old data
if load_old == True:
for day in range(1, 2):
stop = dtutil.now() - datetime.timedelta(days=day)
start = stop - datetime.timedelta(days=2)
try:
readings = self.get_readings(market, start, stop)
_push_data(readings, market)
except Exception, e:
logging.exception('Error getting reading')
# Continuously get new data
try:
stop = dtutil.now()
start = stop - datetime.timedelta(days=1)
readings = self.get_readings(market, start, stop)
rt = readings['total_price'][-1][0]
if rt > self.last_reading[market]:
logging.info("NEW %s READING (%s) at time %s" %
(market,
dtutil.strftime_tz(dtutil.ts2dt(rt),
'%m/%d %H:%M', 'US/Pacific'),
dtutil.strftime_tz(dtutil.now(), '%m/%d %H:%M',
'US/Pacific')))
_push_data(readings, market)
# self.last_reading = rt
except Exception, e:
logging.exception('Error getting reading')
