def loadRawdata(rawfile=None, updbmode=1):
"""
rawfile: rawdata csv file.
updbmode: update db mode: 1-all, 2-incr.
Init *algo* tables with rawdata csv(16 columns) -- SLOW if csv is big,
try offline.doClusterAll(rawdata) -> db.loadClusteredData() instead.
1) db.initTables(): init db tables if update all the db data.
2) db.updateIndexes(): update tables indexes, drop old idxs if only update db incrementally.
3) offline.doClusterIncr(): incremental clustering.
"""
dbips = DB_OFFLINE
doflush = True
for dbip in dbips:
dbsvr = dbsvrs[dbip]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
if updbmode == 1:
# Create WPP tables.
wppdb.initTables(doDrop=True)
doflush = False
# Update indexs.
wppdb.updateIndexes(doflush)
# Load csv clustered data into DB tables.
n_inserts = doClusterIncr(fd_csv=file(rawfile), wppdb=wppdb)
print 'Added: [%s] clusters, [%s] FPs' % (n_inserts['n_newcids'], n_inserts['n_newfps'])
# Init ver_uprecs in |wpp_uprecsver| if it's empty.
if wppdb.getRawdataVersion() is None:
wppdb.setRawdataVersion('0')
wppdb.close()
def loadRawdata(rawfile=None, updbmode=1):
"""
rawfile: rawdata csv file.
updbmode: update db mode: 1-all, 2-incr.
Init *algo* tables with rawdata csv(16 columns) -- SLOW if csv is big,
try offline.doClusterAll(rawdata) -> db.loadClusteredData() instead.
1) db.initTables(): init db tables if update all the db data.
2) db.updateIndexes(): update tables indexes, drop old idxs if only update db incrementally.
3) offline.doClusterIncr(): incremental clustering.
"""
dbips = DB_OFFLINE
doflush = True
for dbip in dbips:
dbsvr = dbsvrs[dbip]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
if updbmode == 1:
# Create WPP tables.
wppdb.initTables(doDrop=True)
doflush = False
# Update indexs.
wppdb.updateIndexes(doflush)
# Load csv clustered data into DB tables.
n_inserts = doClusterIncr(fd_csv=file(rawfile), wppdb=wppdb)
print 'Added: [%s] clusters, [%s] FPs' % (n_inserts['n_newcids'],
n_inserts['n_newfps'])
# Init ver_uprecs in |wpp_uprecsver| if it's empty.
if wppdb.getRawdataVersion() is None:
wppdb.setRawdataVersion('0')
wppdb.close()
def fixPos(posreq=None, has_google=False, mc=None):
xmlnodes = xmlparser(posreq).getchildren()
# Parameters default vals init.
lat, lon, ee = 39.9055, 116.3914, 5000
errinfo = 'AccuTooBad'; errcode = '102'
# logic control switch init.
pos_area = pos_pt = False # Default *PosLevel* is Point if not specified.
# WppDB connection init.
dbsvr = dbsvrs[DB_ONLINE]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
# lambda func init.
f = lambda x : [ node.attrib for node in xmlnodes if node.tag == x ]
plevel = f('PosLevel')
# Area location related parameters interpretation & default vals init.
plevel = plevel[0]['val'] if plevel else 'Point'
acode = addr = ''
if plevel == 'Hybrid': pos_area = pos_pt = True
elif plevel == 'Area': pos_area = True
else:
pos_pt = True
plevel = 'Point' # PosLevel default *Point*.
if pos_area: # Area location.
cell = f('CellInfo')
if cell:
laccid = '%s-%s' % (cell[0]['lac'], cell[0]['cid'])
acode_addr = wppdb.areaLocation(laccid)
if acode_addr:
acode, addr = acode_addr
errinfo='OK'; errcode='100'
lat = lon = ee = ''
if pos_pt: # Point location, which returns 3d coordinates.
macs = f('WLANIdentifier'); rsss = f('WLANMatcher'); need_google = False;
if macs and rsss:
macs = macs[0]['val'].split('|')
rsss = rsss[0]['val'].split('|')
INTERSET = min(CLUSTERKEYSIZE, len(macs))
idxs_max = argsort(rsss)[:INTERSET]
macsrsss = vstack((macs, rsss))[:,idxs_max]
wlanloc = fixPosWLAN(INTERSET, macsrsss, wppdb, DEBUG_ALGO)
if not wlanloc:
need_google = True
else: wlanloc = []
if not wlanloc:
if not pos_area: cell = f('CellInfo')
if cell:
if not pos_area:
laccid = '%s-%s' % (cell[0]['lac'], cell[0]['cid'])
celloc = wppdb.laccidLocation(laccid)
if not celloc:
need_google = True
wpplog.error('Cell location FAILED!')
elif celloc[2] > GOOG_ERR_LIMIT:
need_google = False # googleLocation err too big for wlanloc.
else: pass
else: celloc = []
loc = wlanloc or celloc
if loc:
lat, lon, ee = loc
errinfo = 'OK'; errcode = '100'
# TODO: make googleLocation async job when wlanloc fails & celloc succeeds.
# Try Google location, when wifi location failed && wifi info exists.
if need_google and has_google:
loc_google = googleLocation(macs=macs, rsss=rsss, cellinfo=cell[0], mc=mc)
if loc_google:
lat1, lon1, h, ee_goog = loc_google
if not loc:
lat, lon, ee = lat1, lon1, ee_goog
errinfo = 'OK'; errcode = '100'
# wifi location import. TODO: make google loc import job async when it's *succeeded*.
if macs and ee_goog <= GOOG_ERR_LIMIT:
t = f('Time')
t = t[0]['val'] if t else ''
fp = '1000, 1000101, %s%s%s, %s, %s, %s, %s' % \
(t,','*9,lat1, lon1, h, '|'.join(macs), '|'.join(rsss))
n = doClusterIncr(fd_csv=StringIO(fp), wppdb=wppdb, verb=False)
if n['n_newfps'] == 1:
wpplog.info('Added 1 WLAN FP from Google')
else:
wpplog.error('Failed to add FP from Google!')
# Cell location import.
if cell and not celloc:
if ee_goog <= GOOG_ERR_LIMIT:
loc_google[-1] = 500
wppdb.addCellLocation(laccid=laccid, loc=loc_google)
wpplog.info('Added 1 Cell FP from Google')
else: wpplog.error('Google location FAILED!')
wppdb.close()
if plevel == 'Hybrid': posresp = POS_RESP_FULL % (errcode, errinfo, lat, lon, ee, plevel, acode, addr)
elif plevel == 'Area': posresp = POS_RESP_AREA % (errcode, errinfo, plevel, acode, addr)
else: posresp = POS_RESP_PT % (errcode, errinfo, lat, lon, ee, plevel)
return posresp
def main():
import getopt
try:
opts, args = getopt.getopt(sys.argv[1:], "ac:f:hi:k:m:nr:st:uv",
["areacrawl","cluster","floor=","help","spid=","kml=","mode=","no-dump",
"rawdata","scan","to-rmp=","updatedb","verbose"])
except getopt.GetoptError:
usage()
sys.exit(99)
if not opts: usage(); sys.exit(0)
# global vars init.
crawl_area=False; updatedb=False; doLoadRawdata=False; scan=False
#spid=0; tormp=False; tfail=0; dokml=False;
rawfile=None; docluster=False; updbmode=1
global verbose,pp,floor,nodump
verbose=False; pp=None; nodump=False; floor=False
for o,a in opts:
if o in ("-a", "--areacrawl"):
crawl_area = True
elif o in ("-c", "--cluster"):
if not a.isdigit():
print '\ncluster type: %s should be an INTEGER!' % str(a)
usage(); sys.exit(99)
else:
# 1-All; 2-Incr.
cluster_type = int(a)
docluster = True
rmpfile = sys.argv[3]
if not os.path.isfile(rmpfile):
print 'Raw data file NOT exist: %s!' % rmpfile
sys.exit(99)
#elif o in ("-i", "--spid"):
# if a.isdigit(): spid = int(a)
# else:
# print '\nspid: %s should be an INTEGER!' % str(a)
# usage(); sys.exit(99)
elif o in ("-m", "--mode"):
if a.isdigit():
updbmode = int(a)
if not (1 <= updbmode <= 2):
print '\nError: updatedb mode: (%d) NOT supported yet!' % updbmode
usage(); sys.exit(99)
else:
print '\nmode: %s should be an INTEGER!' % str(a)
usage(); sys.exit(99)
elif o in ("-r", "--rawdata"):
if not os.path.isfile(a):
print 'Rawdata file NOT exist: %s' % a
sys.exit(99)
else:
doLoadRawdata = True
rawfile = a
elif o in ("-s", "--scan"):
scan = True
#elif o in ("-t", "--to-rmp"):
# if not os.path.isfile(a):
# print 'Raw data file NOT exist: %s' % a
# sys.exit(99)
# else:
# tormp = True
# rawfile = a
#elif o in ("-k", "--kml"):
# if not os.path.isfile(a):
# print 'cfprints table file NOT exist: %s' % a
# sys.exit(99)
# else:
# dokml = True
# cfpsfile = a
#elif o in ("-n", "--no-dump"):
# nodump = True
elif o in ("-f", "--floor"):
if a.isdigit():
floor = int(a)
else:
print '\nfloor: %s should be an INTEGER!\n' % str(a)
usage(); sys.exit(99)
elif o in ("-u", "--updatedb"):
updatedb = True
elif o in ("-v", "--verbose"):
verbose = True
pp = PrettyPrinter(indent=2)
elif o in ("-h", "--help"):
usage(); sys.exit(0)
else:
print 'Parameter NOT supported: %s' % o
usage(); sys.exit(99)
if doLoadRawdata:
loadRawdata(rawfile, updbmode)
# Update Algorithm related data.
if updatedb:
updateAlgoData()
if crawl_area:
crawlAreaLocData()
# Ordinary fingerprints clustering.
if docluster:
if cluster_type == 1:
doClusterAll(file(rmpfile))
elif cluster_type == 2:
dbips = DB_OFFLINE
for dbip in dbips:
dbsvr = dbsvrs[dbip]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
n_inserts = doClusterIncr(fd_csv=file(rmpfile), wppdb=wppdb)
print 'Added: [%s] clusters, [%s] FPs' % (n_inserts['n_newcids'], n_inserts['n_newfps'])
wppdb.close()
else: sys.exit('Unsupported cluster type code: %s!' % cluster_type)
# KML generation.
#if dokml:
# genKMLfile(cfpsfile)
## Raw data to fingerprint convertion.
#if tormp:
# fingerprint = []
# fingerprint = genFPs(rawfile)
# if not fingerprint:
# print 'Error: Fingerprint generation FAILED: %s' % rawfile
# sys.exit(99)
# if nodump is False:
# if not rawfile == None:
# date = strftime('%Y-%m%d')
# rmpfilename = DATPATH + date + RMPSUFFIX
# dumpCSV(rmpfilename, fingerprint)
# print '-'*65
# sys.exit(0)
# else:
# usage(); sys.exit(99)
# else:
# if verbose: pp.pprint(fingerprint)
# else: print fingerprint
# sys.exit(0)
# WLAN scan for FP raw data collection.
if scan:
collectFPs()
(ver_bzfile, _file, _lineno, str(e).replace('\n', ' '))
alerts['vers'].append(ver_bzfile)
print 'ERROR: Insert Rawdata Failed!'
continue
# Incr clustering.
# file described by fd_csv contains all *location enabled* rawdata from wpp_uprecsinfo.
strWhere = 'WHERE lat!=0 and lon!=0 and ver_uprecs=%s' % ver_bzfile
cols_ignored = 3 # 3 status cols to be ignored during clustering: ver_uprecs,area_ok,area_try.
cols_select = ','.join(wppdb.tbl_field[tab_rd][:-cols_ignored])
sql = wppdb.sqls['SQL_SELECT'] % ( cols_select, '%s %s'%(tab_rd,strWhere) )
rdata_loc = wppdb.execute(sql=sql, fetch_one=False)
if not rdata_loc: continue # NO FPs has location info.
str_rdata_loc = '\n'.join([ ','.join([str(col) for col in fp]) for fp in rdata_loc ])
fd_csv = StringIO(str_rdata_loc)
print 'FPs for Incr clustering selected & ready'
n_inserts = doClusterIncr(fd_csv=fd_csv, wppdb=wppdb, verb=False)
print 'AlgoData added: [%s] clusters, [%s] FPs' % (n_inserts['n_newcids'], n_inserts['n_newfps'])
# Move rawdata without location to another table: wpp_uprecs_noloc.
tab_rd_noloc = 'wpp_uprecs_noloc'
strWhere = 'lat=0 or lon=0'
sql = wppdb.sqls['SQL_INSERT_SELECT'] % ( tab_rd_noloc, '*', '%s WHERE %s'%(tab_rd,strWhere) )
wppdb.cur.execute(sql)
sql = wppdb.sqls['SQL_DELETE'] % (tab_rd, strWhere)
wppdb.cur.execute(sql)
wppdb.close()
print 'Move noloc rawdata -> |%s|' % tab_rd_noloc
if alerts['vers']:
# Send alert email to admin.
_func = sys._getframe().f_code.co_name
subject = "[!]WPP ERROR: %s->%s, ver: [%s]" % (_file, _func, ','.join(alerts['vers']))
body = ( errmsg['db'] % (tab_rd,'insert',alerts['details'],getIP()['eth0'],ctime()) ).decode('utf-8')
def main():
import getopt
try:
opts, args = getopt.getopt(sys.argv[1:], "ac:f:hi:k:m:nr:st:uv", [
"areacrawl", "cluster", "floor=", "help", "spid=", "kml=", "mode=",
"no-dump", "rawdata", "scan", "to-rmp=", "updatedb", "verbose"
])
except getopt.GetoptError:
usage()
sys.exit(99)
if not opts:
usage()
sys.exit(0)
# global vars init.
crawl_area = False
updatedb = False
doLoadRawdata = False
scan = False
#spid=0; tormp=False; tfail=0; dokml=False;
rawfile = None
docluster = False
updbmode = 1
global verbose, pp, floor, nodump
verbose = False
pp = None
nodump = False
floor = False
for o, a in opts:
if o in ("-a", "--areacrawl"):
crawl_area = True
elif o in ("-c", "--cluster"):
if not a.isdigit():
print '\ncluster type: %s should be an INTEGER!' % str(a)
usage()
sys.exit(99)
else:
# 1-All; 2-Incr.
cluster_type = int(a)
docluster = True
rmpfile = sys.argv[3]
if not os.path.isfile(rmpfile):
print 'Raw data file NOT exist: %s!' % rmpfile
sys.exit(99)
#elif o in ("-i", "--spid"):
# if a.isdigit(): spid = int(a)
# else:
# print '\nspid: %s should be an INTEGER!' % str(a)
# usage(); sys.exit(99)
elif o in ("-m", "--mode"):
if a.isdigit():
updbmode = int(a)
if not (1 <= updbmode <= 2):
print '\nError: updatedb mode: (%d) NOT supported yet!' % updbmode
usage()
sys.exit(99)
else:
print '\nmode: %s should be an INTEGER!' % str(a)
usage()
sys.exit(99)
elif o in ("-r", "--rawdata"):
if not os.path.isfile(a):
print 'Rawdata file NOT exist: %s' % a
sys.exit(99)
else:
doLoadRawdata = True
rawfile = a
elif o in ("-s", "--scan"):
scan = True
#elif o in ("-t", "--to-rmp"):
# if not os.path.isfile(a):
# print 'Raw data file NOT exist: %s' % a
# sys.exit(99)
# else:
# tormp = True
# rawfile = a
#elif o in ("-k", "--kml"):
# if not os.path.isfile(a):
# print 'cfprints table file NOT exist: %s' % a
# sys.exit(99)
# else:
# dokml = True
# cfpsfile = a
#elif o in ("-n", "--no-dump"):
# nodump = True
elif o in ("-f", "--floor"):
if a.isdigit():
floor = int(a)
else:
print '\nfloor: %s should be an INTEGER!\n' % str(a)
usage()
sys.exit(99)
elif o in ("-u", "--updatedb"):
updatedb = True
elif o in ("-v", "--verbose"):
verbose = True
pp = PrettyPrinter(indent=2)
elif o in ("-h", "--help"):
usage()
sys.exit(0)
else:
print 'Parameter NOT supported: %s' % o
usage()
sys.exit(99)
if doLoadRawdata:
loadRawdata(rawfile, updbmode)
# Update Algorithm related data.
if updatedb:
updateAlgoData()
if crawl_area:
crawlAreaLocData()
# Ordinary fingerprints clustering.
if docluster:
if cluster_type == 1:
doClusterAll(file(rmpfile))
elif cluster_type == 2:
dbips = DB_OFFLINE
for dbip in dbips:
dbsvr = dbsvrs[dbip]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
n_inserts = doClusterIncr(fd_csv=file(rmpfile), wppdb=wppdb)
print 'Added: [%s] clusters, [%s] FPs' % (
n_inserts['n_newcids'], n_inserts['n_newfps'])
wppdb.close()
else:
sys.exit('Unsupported cluster type code: %s!' % cluster_type)
# KML generation.
#if dokml:
# genKMLfile(cfpsfile)
## Raw data to fingerprint convertion.
#if tormp:
# fingerprint = []
# fingerprint = genFPs(rawfile)
# if not fingerprint:
# print 'Error: Fingerprint generation FAILED: %s' % rawfile
# sys.exit(99)
# if nodump is False:
# if not rawfile == None:
# date = strftime('%Y-%m%d')
# rmpfilename = DATPATH + date + RMPSUFFIX
# dumpCSV(rmpfilename, fingerprint)
# print '-'*65
# sys.exit(0)
# else:
# usage(); sys.exit(99)
# else:
# if verbose: pp.pprint(fingerprint)
# else: print fingerprint
# sys.exit(0)
# WLAN scan for FP raw data collection.
if scan:
collectFPs()
def updateAlgoData():
"""
Update from raw data into FPs directly used by location.fixPosWLAN() from WppDB(wpp_clusterid, wpp_cfps).
1) Retrieve latest incremental rawdata(csv) from remote FTP server(hosted by FPP).
2) Decompress bzip2, import CSV into wpp_uprecsinfo with its ver_uprecs, Update ver_uprecs in wpp_uprecsver.
3) Incr clustering inserted rawdata for direct algo use.
"""
dbips = DB_OFFLINE
for dbip in dbips:
dbsvr = dbsvrs[dbip]
wppdb = WppDB(dsn=dbsvr['dsn'], dbtype=dbsvr['dbtype'])
ver_wpp = wppdb.getRawdataVersion()
# Sync rawdata into wpp_uprecsinfo from remote FTP server.
print 'Probing rawdata version > [%s]' % ver_wpp
vers_fpp, localbzs = syncFtpUprecs(FTPCFG, ver_wpp)
if not vers_fpp:
print 'Not found!'
continue
else:
print 'Found new vers: %s' % vers_fpp
# Handle each bzip2 file.
alerts = {'vers': [], 'details': ''}
tab_rd = 'wpp_uprecsinfo'
for bzfile in localbzs:
# Filter out the ver_uprecs info from the name of each bzip file.
ver_bzfile = bzfile.split('_')[-1].split('.')[0]
# Update ver_uprecs in wpp_uprecsver to ver_bzfile.
wppdb.setRawdataVersion(ver_bzfile)
print '%s\nUpdate ver_uprecs -> [%s]' % ('-' * 40, ver_bzfile)
# Decompress bzip2.
sys.stdout.write('Decompress & append rawdata ... ')
csvdat = csv.reader(BZ2File(bzfile))
try:
indat = np_array([line for line in csvdat])
except csv.Error, e:
sys.exit('\n\nERROR: %s, line %d: %s!\n' %
(bzfile, csvdat.line_num, e))
# Append ver_uprecs(auto-incr),area_ok(0),area_try(0) to raw 16-col fp.
append_info = np_array([[ver_bzfile, 0, 0]
for i in xrange(len(indat))])
indat_withvers = np_append(indat, append_info, axis=1).tolist()
print 'Done'
# Import csv into wpp_uprecsinfo.
try:
sys.stdout.write('Import rawdata: ')
wppdb.insertMany(table_name=tab_rd,
indat=indat_withvers,
verb=True)
except Exception, e:
_lineno = sys._getframe().f_lineno
_file = sys._getframe().f_code.co_filename
alerts['details'] += '\n[ver:%s][%s:%s]: %s' % \
(ver_bzfile, _file, _lineno, str(e).replace('\n', ' '))
alerts['vers'].append(ver_bzfile)
print 'ERROR: Insert Rawdata Failed!'
continue
# Incr clustering.
# file described by fd_csv contains all *location enabled* rawdata from wpp_uprecsinfo.
strWhere = 'WHERE lat!=0 and lon!=0 and ver_uprecs=%s' % ver_bzfile
cols_ignored = 3 # 3 status cols to be ignored during clustering: ver_uprecs,area_ok,area_try.
cols_select = ','.join(wppdb.tbl_field[tab_rd][:-cols_ignored])
sql = wppdb.sqls['SQL_SELECT'] % (cols_select, '%s %s' %
(tab_rd, strWhere))
rdata_loc = wppdb.execute(sql=sql, fetch_one=False)
if not rdata_loc: continue # NO FPs has location info.
str_rdata_loc = '\n'.join(
[','.join([str(col) for col in fp]) for fp in rdata_loc])
fd_csv = StringIO(str_rdata_loc)
print 'FPs for Incr clustering selected & ready'
n_inserts = doClusterIncr(fd_csv=fd_csv, wppdb=wppdb, verb=False)
print 'AlgoData added: [%s] clusters, [%s] FPs' % (
n_inserts['n_newcids'], n_inserts['n_newfps'])