def unserialise_compat(cls, version, obj, absolute=False):
if version == 1:
obj['raw_values'] = {}
if 'SERIES_META' in obj['metadata']:
obj['raw_values'] = dict([(k,v['RAW_VALUES']) for k,v in
obj['metadata']['SERIES_META'].items()
if 'RAW_VALUES' in v])
if not obj['raw_values']:
# No raw values were stored in the old data set. Fake them by
# using the interpolated values as 'raw'. This ensures there's
# always some data available as raw values, to facilitate
# relying on their presence in future code.
t0 = parse_date(obj['metadata'].get('T0', obj['metadata'].get('TIME')))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
for name in obj['results'].keys():
obj['raw_values'][name] = [{'t': x0+x, 'val': r} for x,r in
zip(obj['x_values'], obj['results'][name])]
obj['metadata']['FAKE_RAW_VALUES'] = True
if 'NETPERF_WRAPPER_VERSION' in obj['metadata']:
obj['metadata']['FLENT_VERSION'] = obj['metadata']['NETPERF_WRAPPER_VERSION']
del obj['metadata']['NETPERF_WRAPPER_VERSION']
return obj
def unserialise(cls, obj, absolute=False, SUFFIX=SUFFIX):
try:
version = int(obj['version'])
except (KeyError,ValueError):
version = 1
if version > FILEFORMAT_VERSION:
raise RuntimeError("File format version %d is too new. Please upgrade your version of Flent" % version)
if version < FILEFORMAT_VERSION:
obj = cls.unserialise_compat(version, obj, absolute)
metadata = dict(obj['metadata'])
if not 'TOTAL_LENGTH' in metadata or metadata['TOTAL_LENGTH'] is None:
metadata['TOTAL_LENGTH'] = max(obj['x_values'])
for t in TIME_SETTINGS:
if t in metadata and metadata[t] is not None:
metadata[t] = parse_date(metadata[t])
rset = cls(SUFFIX=SUFFIX, **metadata)
if absolute:
t0 = metadata.get('T0', metadata.get('TIME'))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
rset.x_values = [x+x0 for x in obj['x_values']]
rset._absolute = True
else:
rset.x_values = obj['x_values']
for k,v in list(obj['results'].items()):
rset.add_result(k,v)
rset.raw_values = obj['raw_values']
return rset
def unserialise_compat(cls, version, obj, absolute=False):
if version == 1:
obj['raw_values'] = {}
if 'SERIES_META' in obj['metadata']:
obj['raw_values'] = dict([
(k, v['RAW_VALUES'])
for k, v in obj['metadata']['SERIES_META'].items()
if 'RAW_VALUES' in v
])
if not obj['raw_values']:
# No raw values were stored in the old data set. Fake them by
# using the interpolated values as 'raw'. This ensures there's
# always some data available as raw values, to facilitate
# relying on their presence in future code.
t0 = parse_date(obj['metadata'].get(
'T0', obj['metadata'].get('TIME')))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
for name in obj['results'].keys():
obj['raw_values'][name] = [{
't': x0 + x,
'val': r
} for x, r in zip(obj['x_values'], obj['results'][name])]
obj['metadata']['FAKE_RAW_VALUES'] = True
if 'NETPERF_WRAPPER_VERSION' in obj['metadata']:
obj['metadata']['FLENT_VERSION'] = obj['metadata'][
'NETPERF_WRAPPER_VERSION']
del obj['metadata']['NETPERF_WRAPPER_VERSION']
return obj
def unserialise(cls, obj, absolute=False, SUFFIX=SUFFIX):
try:
version = int(obj['version'])
except (KeyError, ValueError):
version = 1
if version > FILEFORMAT_VERSION:
raise RuntimeError("File format version %d is too new. "
"Please upgrade your version of Flent" %
version)
if version < FILEFORMAT_VERSION:
obj = cls.unserialise_compat(version, obj, absolute)
metadata = dict(obj['metadata'])
if 'TOTAL_LENGTH' not in metadata or metadata['TOTAL_LENGTH'] is None:
metadata['TOTAL_LENGTH'] = max(obj['x_values'])
for t in TIME_SETTINGS:
if t in metadata and metadata[t] is not None:
metadata[t] = parse_date(metadata[t])
rset = cls(SUFFIX=SUFFIX, **metadata)
if absolute:
t0 = metadata.get('T0', metadata.get('TIME'))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
rset.x_values = [x + x0 for x in obj['x_values']]
rset._absolute = True
else:
rset.x_values = obj['x_values']
for k, v in list(obj['results'].items()):
rset.add_result(k, v)
rset.raw_values = obj['raw_values']
return rset
def unserialise(cls, obj, absolute=False, SUFFIX=SUFFIX):
try:
version = int(obj['version'])
except (KeyError, ValueError):
version = 1
if version > FILEFORMAT_VERSION:
raise RuntimeError("File format version %d is too new. "
"Please upgrade your version of Flent" %
version)
if version < FILEFORMAT_VERSION:
logger.debug(
"Found old file format version %d. "
"Converting to current version %d.", version,
FILEFORMAT_VERSION)
obj = cls.unserialise_compat(version, obj, absolute)
metadata = dict(obj['metadata'])
if 'TOTAL_LENGTH' not in metadata or metadata['TOTAL_LENGTH'] is None:
metadata['TOTAL_LENGTH'] = max(obj['x_values'])
# We need the minimum timestamp to guess a timezone offset, which we
# store for subsequent values because it shouldn't be used for
# BATCH_TIME
min_t = 10**10
offset = None
for v in obj['raw_values'].values():
min_t = min([min_t] + [i['t'] for i in v if 't' in i])
for t in TIME_SETTINGS:
if t in metadata and metadata[t] is not None:
metadata[t], offset = parse_date(metadata[t],
min_t=min_t,
offset=offset)
rset = cls(SUFFIX=SUFFIX, **metadata)
if absolute:
t0 = metadata.get('T0', metadata.get('TIME'))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
rset.x_values = [x + x0 for x in obj['x_values']]
rset._absolute = True
else:
rset.x_values = obj['x_values']
for k, v in list(obj['results'].items()):
rset.add_result(k, v)
rset.raw_values = obj['raw_values']
return rset
def unserialise_compat(cls, version, obj, absolute=False):
fake_raw = False
if version == 1:
obj['raw_values'] = {}
if 'SERIES_META' in obj['metadata']:
logger.debug("Moving raw values from SERIES_META")
obj['raw_values'] = dict([(k, v['RAW_VALUES']) for k, v in
obj['metadata']['SERIES_META'].items()
if 'RAW_VALUES' in v])
if not obj['raw_values']:
# No raw values were stored in the old data set. Fake them by
# using the interpolated values as 'raw'. This ensures there's
# always some data available as raw values, to facilitate
# relying on their presence in future code.
logger.debug("No raw values found; synthesising from parsed data")
t0, offset = parse_date(obj['metadata'].get(
'T0', obj['metadata'].get('TIME')))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
for name in obj['results'].keys():
obj['raw_values'][name] = [{'t': x0 + x, 'val': r} for x, r in
zip(obj['x_values'],
obj['results'][name])]
obj['metadata']['FAKE_RAW_VALUES'] = fake_raw = True
if 'NETPERF_WRAPPER_VERSION' in obj['metadata']:
logger.debug("Converting old NETPERF_WRAPPER_VERSION (%s) "
"to FLENT_VERSION",
obj['metadata']['NETPERF_WRAPPER_VERSION'])
obj['metadata']['FLENT_VERSION'] = obj[
'metadata']['NETPERF_WRAPPER_VERSION']
del obj['metadata']['NETPERF_WRAPPER_VERSION']
if version < 4 and not fake_raw:
# Version 4 moved the data transform logic to also be applied to
# raw_values data. So fixup the values in the raw_values structure
# to apply data transforms where they are missing.
logger.debug("Applying unit conversion to raw values")
converted = 0
for n, values in obj['raw_values'].items():
# Netperf UDP_RR values
if 'UDP' in n:
logger.debug("Converting data series '%s' from RR to ms", n)
for v in values:
# Unfortunately this is the best heuristic we have that
# this was a netperf UDP_RR runner, since old versions
# may not have recorded this fact in the metadata
if 'dur' in v:
v['val'] = transformers.rr_to_ms(v['val'])
converted += 1
# Convert HTTP latency values from seconds to milliseconds
elif n == 'HTTP latency':
logger.debug("Converting data series '%s' from s to ms", n)
for v in values:
if 'val' in v:
v['val'] = transformers.s_to_ms(v['val'])
converted += 1
# Turn airtime values from cumulative values into counts per
# interval
elif values and 'stations' in values[0]:
logger.debug("Converting airtime values for series '%s' from "
"cumulative to per-interval", n)
last_vals = {}
for v in values:
if 'stations' not in v:
continue
for s, d in v['stations'].items():
if s not in last_vals:
last_vals[s] = {}
last = last_vals[s]
for k in ('airtime_tx', 'airtime_rx'):
if k in d:
converted += 1
if k not in last:
last[k], d[k] = d[k], 0.0
else:
last[k], d[k] = d[k], d[k] - last[k]
# Ditto for qdisc drops and marks
elif values and ('dropped' in values[0] or
'ecn_mark' in values[0]):
logger.debug("Converting qdisc drops and marks for series "
"'%s' ""from cumulative to per-interval values",
n)
last = {}
for v in values:
for k in ('dropped', 'ecn_mark'):
if k in v:
converted += 1
if k not in last:
last[k], v[k] = v[k], 0.0
else:
last[k], v[k] = v[k], v[k] - last[k]
# Iperf UDP bandwidth is was reported in bits/s, now uses Mbits/s to
# be consistent with other bandwidth measurements
if 'SERIES_META' in obj['metadata']:
for k, v in obj['metadata']['SERIES_META'].items():
if 'MEAN_VALUE' in v and v.get('UNITS') == "bits/s":
logger.debug("Converting MEAN_VALUE units for series "
"'%s' from bit/s to Mbits/s", k)
converted += 1
v['MEAN_VALUE'] = transformers.bits_to_mbits(
v['MEAN_VALUE'])
v['UNITS'] = "Mbits/s"
logger.debug("Converted a total of %d data points.",
converted)
return obj
def unserialise_compat(cls, version, obj, absolute=False):
fake_raw = False
if version == 1:
obj['raw_values'] = {}
if 'SERIES_META' in obj['metadata']:
logger.debug("Moving raw values from SERIES_META")
obj['raw_values'] = dict([(k, v['RAW_VALUES']) for k, v in
obj['metadata']['SERIES_META'].items()
if 'RAW_VALUES' in v])
if not obj['raw_values']:
# No raw values were stored in the old data set. Fake them by
# using the interpolated values as 'raw'. This ensures there's
# always some data available as raw values, to facilitate
# relying on their presence in future code.
logger.debug("No raw values found; synthesising from parsed data")
t0 = parse_date(obj['metadata'].get(
'T0', obj['metadata'].get('TIME')))
x0 = timegm(t0.timetuple()) + t0.microsecond / 1000000.0
for name in obj['results'].keys():
obj['raw_values'][name] = [{'t': x0 + x, 'val': r} for x, r in
zip(obj['x_values'],
obj['results'][name])]
obj['metadata']['FAKE_RAW_VALUES'] = fake_raw = True
if 'NETPERF_WRAPPER_VERSION' in obj['metadata']:
logger.debug("Converting old NETPERF_WRAPPER_VERSION (%s) "
"to FLENT_VERSION",
obj['metadata']['NETPERF_WRAPPER_VERSION'])
obj['metadata']['FLENT_VERSION'] = obj[
'metadata']['NETPERF_WRAPPER_VERSION']
del obj['metadata']['NETPERF_WRAPPER_VERSION']
if version < 4 and not fake_raw:
# Version 4 moved the data transform logic to also be applied to
# raw_values data. So fixup the values in the raw_values structure
# to apply data transforms where they are missing.
logger.debug("Applying unit conversion to raw values")
converted = 0
for n, values in obj['raw_values'].items():
# Netperf UDP_RR values
if 'UDP' in n:
logger.debug("Converting data series '%s' from RR to ms", n)
for v in values:
# Unfortunately this is the best heuristic we have that
# this was a netperf UDP_RR runner, since old versions
# may not have recorded this fact in the metadata
if 'dur' in v:
v['val'] = transformers.rr_to_ms(v['val'])
converted += 1
# Convert HTTP latency values from seconds to milliseconds
elif n == 'HTTP latency':
logger.debug("Converting data series '%s' from s to ms", n)
for v in values:
if 'val' in v:
v['val'] = transformers.s_to_ms(v['val'])
converted += 1
# Turn airtime values from cumulative values into counts per
# interval
elif values and 'stations' in values[0]:
logger.debug("Converting airtime values for series '%s' from "
"cumulative to per-interval", n)
last_vals = {}
for v in values:
if 'stations' not in v:
continue
for s, d in v['stations'].items():
if s not in last_vals:
last_vals[s] = {}
last = last_vals[s]
for k in ('airtime_tx', 'airtime_rx'):
if k in d:
converted += 1
if k not in last:
last[k], d[k] = d[k], 0.0
else:
last[k], d[k] = d[k], d[k] - last[k]
# Ditto for qdisc drops and marks
elif values and ('dropped' in values[0] or
'ecn_mark' in values[0]):
logger.debug("Converting qdisc drops and marks for series "
"'%s' ""from cumulative to per-interval values",
n)
last = {}
for v in values:
for k in ('dropped', 'ecn_mark'):
if k in v:
converted += 1
if k not in last:
last[k], v[k] = v[k], 0.0
else:
last[k], v[k] = v[k], v[k] - last[k]
# Iperf UDP bandwidth is was reported in bits/s, now uses Mbits/s to
# be consistent with other bandwidth measurements
if 'SERIES_META' in obj['metadata']:
for k, v in obj['metadata']['SERIES_META'].items():
if 'MEAN_VALUE' in v and v.get('UNITS') == "bits/s":
logger.debug("Converting MEAN_VALUE units for series "
"'%s' from bit/s to Mbits/s", k)
converted += 1
v['MEAN_VALUE'] = transformers.bits_to_mbits(
v['MEAN_VALUE'])
v['UNITS'] = "Mbits/s"
logger.debug("Converted a total of %d data points.",
converted)
return obj
