def __init__(self, opts):
Transformer.__init__(self, opts)
if not 'yaml' in opts:
raise Exception('yaml=file option required')
f = open(opts.get('yaml'), 'r')
try:
self.label = yaml.full_load(f)
except AttributeError:
self.label = yaml.load(f)
f.close()
def test_transformer():
o = Transformer({})
with pytest.raises(Exception):
o.process([])
class Transformer1(Transformer):
def process(self, file):
pass
with pytest.raises(Exception):
class Transformer1(Transformer):
def process(self, file):
pass
def __init__(self, opts):
Transformer.__init__(self, opts)
net = opts.get('net', None)
self.v4net = opts.get('v4net', net)
self.v6net = opts.get('v6net', net)
if not self.v4net:
raise Exception('v4net (or net) must be given')
if not self.v6net:
raise Exception('v6net (or net) must be given')
if opts.get('nonstrict', False):
self.nonstrict = True
def __init__(self, opts):
Transformer.__init__(self, opts)
self.key = opts.get('key', 'mid')
self.func = opts.get('func', 'sum')
self.allow_invalid_keys = opts.get('allow_invalid_keys', False)
self.range = opts.get('range', None)
if self.allow_invalid_keys != False:
self.allow_invalid_keys = True
if self.range is None:
raise Exception('range must be given')
m = re.match(r'^/(\d+)$', self.range)
if m is None:
raise Exception('invalid range')
self.split_by = int(m.group(1))
if self.key != 'low' and self.key != 'mid' and self.key != 'high':
raise Exception('invalid key %r' % self.key)
if self.func != 'sum':
raise Exception('invalid func %r' % self.func)
nkey = high
nkey = int(nkey / self.split_by) * self.split_by
low = nkey
high = nkey + self.split_by - 1
if self.func == 'sum':
if low != high:
nkey = '%d-%d' % (low, high)
else:
nkey = str(nkey)
if nkey in dimension.values:
dimension.values[nkey] += v
else:
dimension.values[nkey] = v
if skipped:
dimension.values['skipped'] = skipped
def process(self, datasets):
for dataset in datasets:
for dimension in dataset.dimensions:
self._process(dimension)
import sys
if sys.version_info[0] == 3 and sys.version_info[1] == 5: # pragma: no cover
Transformer.__init_subclass__(ReRanger)
class Labler(Transformer):
label = None
def __init__(self, opts):
Transformer.__init__(self, opts)
if not 'yaml' in opts:
raise Exception('yaml=file option required')
f = open(opts.get('yaml'), 'r')
try:
self.label = yaml.full_load(f)
except AttributeError:
self.label = yaml.load(f)
f.close()
def process(self, datasets):
if self.label is None:
return
for dataset in datasets:
label = self.label.get(dataset.name, None)
if label is None:
continue
for d in dataset.dimensions:
_process(label, d)
import sys
if sys.version_info[0] == 3 and sys.version_info[1] == 5: # pragma: no cover
Transformer.__init_subclass__(Labler)
elif k == args.skipped_sum_key:
dimension.values['0'] = v
continue
try:
ip = ipaddress.ip_address(k)
except Exception as e:
if not self.nonstrict:
raise e
continue
if ip.version == 4:
nkey = str(ipaddress.IPv4Network('%s/%s' % (ip, self.v4net), strict=False).network_address)
else:
nkey = str(ipaddress.IPv6Network('%s/%s' % (ip, self.v6net), strict=False).network_address)
if not nkey in dimension.values:
dimension.values[nkey] = v
else:
dimension.values[nkey] += v
def process(self, datasets):
for dataset in datasets:
for dimension in dataset.dimensions:
self._process(dimension)
import sys
if sys.version_info[0] == 3 and sys.version_info[1] == 5: # pragma: no cover
Transformer.__init_subclass__(NetRemap)