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# -*- coding: utf-8 -*-
import os
import json
import traceback
import time
import itertools
import numpy
import bottle
import logging
logging.basicConfig()
from ebus.datastore import Datastore, Interval
datastore = Datastore("datastore-data")
app = bottle.Bottle("ebus")
@app.route('/')
def index_file():
return static_files("index.html")
@app.route('/static/:filename#.+#')
def static_files(filename):
return bottle.static_file(filename, root=os.path.join(os.path.dirname(__file__),"web_static"))
@app.put('/sensor/:name')
def sensor_data_put(name):
try:
value = bottle.request.POST.value
type = bottle.request.POST.type
timestamp = long(time.time()*1000)
print name,value,type,timestamp
if type == "int":
datastore.addValueInt(name, timestamp, long(value))
elif type == "float":
datastore.addValueFloat(name, timestamp, float(value))
elif type == "string":
datastore.addValueString(name, timestamp, str(value))
else:
return {'error':'INVALID_TYPE', msg:'Type {0} is invalid'.format(type)}
msg = "Stored {0} of type {1} with timestamp {2} to {3}".format(value,type,timestamp,name)
return {'error':None,'msg':msg}
except Exception,e:
traceback.print_exc()
msg = "failed to insert into {0}".format(name)
print msg
return {'error':str(e),'msg':msg}
@app.route('/sensor/:name/:startdate/:enddate')
def sensor_name_start_end(name,startdate,enddate):
startdate, enddate = long(startdate), long(enddate)
assert (enddate - startdate) < Interval.MONTH * 2
try:
data = sorted(datastore.get_range_n(name, startdate, enddate,800))
return {'name':name,
'config':datastore.get_config(name),
'data':data}
except Exception,e:
traceback.print_exc()
return {"data":None, "error":str(e)}
@app.route('/avg/:name/:startdate/:enddate')
def sensor_avg_start(name, startdate, enddate):
period = 15 * Interval.MIN
startdate, enddate = long(startdate), long(enddate)
assert (enddate - startdate) < Interval.MONTH * 2
try:
sel_rows = datastore.get_range_n(name, startdate, enddate, 5000)
data = itertools.groupby(sel_rows, lambda row: row[0]-(row[0]%period))
data = map(lambda (group_time, grouped_rows):
(long(group_time), numpy.average([row[1] for row in grouped_rows])),
data)
return {'sensor':name, 'error':None,'data':data}
except Exception,e:
return {'sensor':name, 'error':str(e), 'data':None}
# vim: autoindent tabstop=4 shiftwidth=4 expandtab softtabstop=4 filetype=python
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