def kml(self, table, row_id):
cl = FT(settings.FT_CONSUMER_KEY, settings.FT_CONSUMER_SECRET, settings.FT_TOKEN, settings.FT_SECRET)
# TODO: do this better
if table == 1568452:
id = "ex_area"
else:
id = "name"
info = cl.sql("select geometry from %s where %s = %s" % (table, id, row_id))
polygon = info.split("\n")[1]
polygon = polygon.replace('"', "")
return polygon
def kml(self, table, row_id):
cl = FT(settings.FT_CONSUMER_KEY, settings.FT_CONSUMER_SECRET,
settings.FT_TOKEN, settings.FT_SECRET)
#TODO: do this better
if (table == 1568452):
id = 'ex_area'
else:
id = 'name'
info = cl.sql("select geometry from %s where %s = %s" %
(table, id, row_id))
polygon = info.split('\n')[1]
polygon = polygon.replace("\"", "")
return polygon
def kml(self, table, row_id):
cl = FT(settings.FT_CONSUMER_KEY,
settings.FT_CONSUMER_SECRET,
settings.FT_TOKEN,
settings.FT_SECRET)
#TODO: do this better
if (table == 1568452):
id = 'ex_area'
else:
id = 'name'
info = cl.sql("select geometry from %s where %s = %s" %
(table, id, row_id))
polygon = info.split('\n')[1]
polygon = polygon.replace("\"", "")
return polygon
def fusion_tables_names():
""" precache de fusion tables names """
for x in FustionTablesNames.all():
x.delete()
cl = FT(settings.FT_CONSUMER_KEY, settings.FT_CONSUMER_SECRET,
settings.FT_TOKEN, settings.FT_SECRET)
for desc, table, name in tables:
info = cl.sql("select %s, description from %s" % (name, table))
data = []
# sorry
for line in info.split('\n')[1:]:
if line:
tk = line.split(',')
#TODO: fix html decoding
data.append((tk[0], tk[1]))
FustionTablesNames(table_id=str(table),
json=json.dumps(dict(data))).put()
return "working"
def fusion_tables_names():
""" precache de fusion tables names """
for x in FustionTablesNames.all():
x.delete()
cl = FT(settings.FT_CONSUMER_KEY,
settings.FT_CONSUMER_SECRET,
settings.FT_TOKEN,
settings.FT_SECRET)
for desc, table, name in tables:
info = cl.sql("select %s, description from %s" % (name, table))
data = []
# sorry
for line in info.split('\n')[1:]:
if line:
tk = line.split(',')
#TODO: fix html decoding
data.append((tk[0], tk[1]))
FustionTablesNames(table_id=str(table), json=json.dumps(dict(data))).put()
return "working"
