1 files changed, 0 insertions, 133 deletions
diff --git a/ebus/webhdf/__init__.py b/ebus/webhdf/__init__.py
deleted file mode 100644
index f661800..0000000
--- a/ebus/webhdf/__init__.py
+++ /dev/null
@@ -1,133 +0,0 @@
-# -*- coding: utf-8 -*-
-import os
-import json
-import datetime
-import time
-import itertools
-import logging
-logging.basicConfig(level=logging.DEBUG)
-
-import numpy
-
-import bottle 
-
-import ebus.datastore
-
-datastore = ebus.datastore.Datastore("hdf-data")
-app = bottle.Bottle("ebus")
-
-lastflush = -1
-
-@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__),"static"))
-
-
-@app.get('/sensor/:name')
-def sensor_data_get(name):
-    try:
-        table = datastore.getTable(name)
-        with datastore:
-            data = table.readSorted(sortby="timestamp", checkCSI=True, start=0, stop=1,step=-1).tolist()[0]
-            return {'sensor':name,'error':None,'data':data}
-    except Exception,e:
-        return {'sensor':name,'data':None, 'error':str(e)}
-
-@app.put('/sensor/:name')
-@app.put('/sensor/:name/:timestamp')
-def sensor_data_put(name,timestamp=None):
-    FLUSH_INTERVAL=30 #sec
-    global lastflush
-
-    if not timestamp: timestamp = int(time.time())
-    try:
-        value = bottle.request.POST.value
-        type = bottle.request.POST.type
-
-        if type == "int":
-            klass = ebus.datastore.ValueInt
-        elif type == "float":
-            klass = ebus.datastore.ValueFloat
-        elif type == "string":
-            klass = ebus.datastore.ValueString
-	elif type == "":
-	    klass = None
-        else:
-            return {'error':'INVALID_TYPE', msg:'Type {0} is invalid'.format(type)}
-
-	msg = "Storing {0} of type {1} with timestamp {2} to {3}".format(value,type,timestamp,name)
-	logging.info(msg)
-
-        datastore.addValue(name, timestamp, value, klass, flush=False)
-
-        if time.time() - FLUSH_INTERVAL > lastflush:
-	    logging.info("call datastore.flush()")
-            datastore.flush()
-	    lastflush = time.time()
-
-        return {'error':None,'msg':msg}
-    except Exception,e:
-	logging.error("Error: " + "{0} name={1} value={2} type={3}".format(e, name, value, type))
-        return {'error':str(e),'msg':str(e)}
-
-
-
-@app.route('/sensor/:name/:startdate/:enddate')
-def sensor_name_start_end(name,startdate,enddate):
-    SAMPLING_STEPSIZE=500
-    NUMBER_OF_VALUES=250
-    try:
-        startdate, enddate = int(startdate), int(enddate)
-	logging.info("/sensor/ start={0} end={1}".format(startdate, enddate))
-        table=datastore.getTable(name)
-        with datastore:
-	    i = table.where("(timestamp >= startdate) & (timestamp <= enddate)",
-			    condvars={'startdate':startdate,'enddate':enddate,'timestamp':table.cols.timestamp},
-			    step=SAMPLING_STEPSIZE)
-	    timestamps = []
-	    try:
-	        for x in range(20):
-		    i.next()
-		    timestamps.append(i['timestamp'])
-	    except: pass
-
-	    if len(timestamps) > 10:
-		    diff = map(lambda (x1,x2): (x2-x1)/SAMPLING_STEPSIZE, zip(timestamps[:-1], timestamps[1:]))
-		    diff_avg = numpy.average(diff)
-		    time_period = enddate - startdate
-		    samples = time_period / diff_avg
-		    step = numpy.ceil(samples / float(NUMBER_OF_VALUES))
-
-		    data = [(x['timestamp'], x['value']) 
-			    for x in table.where("(timestamp >= startdate) & (timestamp <= enddate)", step=step)]
-		    logging.info("diff={0} samples={1} step={2} len={3} ({4})".format(diff_avg, samples, step, len(data),name))
-	    else:
-		    # Not enough data, sampling approach useless, deliver all data
-		    data = [(x['timestamp'], x['value']) for x in table.where("(timestamp >= startdate) & (timestamp <= enddate)")]
-            return {'sensor':name, 'error':None,'data':data}
-    except Exception,e:
-	logging.error("Error: " + str(e) + str(type(e)))
-        return {'sensor':name,'data':None, 'error':str(e)}
-
-@app.route('/avg/:name/:startdate')
-@app.route('/avg/:name/:startdate/:period')
-def sensor_avg_start(name, startdate, period=60*15): #15min
-    AVG_STEPSIZE=50
-    try:
-        startdate, enddate = int(startdate), int(time.time())
-	logging.info("/avg/ start={0} end={1}".format(startdate, enddate))
-        table=datastore.getTable(name)
-        with datastore:
-            sel_rows = table.where("(timestamp >= startdate) & (timestamp <=enddate)", step=AVG_STEPSIZE)
-            f_group = range(startdate, enddate, period)
-            data = map(lambda (group_id, grouped_rows): (group_id, numpy.average([row['value'] for row in grouped_rows])),
-                    itertools.groupby(sel_rows, lambda t: (t['timestamp']/period)*period))
-            data = map(lambda (timestamp,value): (timestamp, value), data)
-            return {'sensor':name, 'error':None,'data':data}
-    except Exception,e:
-            return {'sensor':name, 'error':str(e), 'data':None}
-