def run(self):
sks = Device.objects.filter(enabled=True, module='netshark')
res = []
for sk in sks:
sk_dev = DeviceManager.get_device(sk.id)
for job in sk_dev.get_capture_jobs():
if_name = job.data['config']['interface_name']
start = str(nsec_string_to_datetime(job.packet_start_time))
end = str(nsec_string_to_datetime(job.packet_end_time))
bpf_filter = job.data['config'].get('bpf_filter', '')
if len(bpf_filter) > self.MAX_LENGTH:
bpf_filter = bpf_filter[:self.MAX_LENGTH - 2] + '...'
pkts_dropped = job.get_stats()['packets_dropped']
pkts_written = job.get_stats()['packets_written']
job_data = dict(netshark=sk.name,
job_id=job.data['id'],
job_name=job.data['config']['name'],
interface=if_name,
state=job.data['status']['state'],
size=job.data['status']['packet_size'],
start_time=start,
end_time=end,
bpf_filter=bpf_filter,
dpi_enabled=str(job.dpi_enabled),
index_enabled=str(job.index_enabled),
last_sec_dropped=pkts_dropped['last_second'],
last_min_dropped=pkts_dropped['last_minute'],
last_hr_dropped=pkts_dropped['last_hour'],
last_sec_written=pkts_written['last_second'],
last_min_written=pkts_written['last_minute'],
last_hr_written=pkts_written['last_hour']
)
res.append(job_data)
return QueryComplete(pandas.DataFrame(res))
def run(self):
sks = Device.objects.filter(enabled=True, module='netshark')
res = []
for sk in sks:
sk_dev = DeviceManager.get_device(sk.id)
for job in sk_dev.get_capture_jobs():
if_name = job.data['config']['interface_name']
start = str(nsec_string_to_datetime(job.packet_start_time))
end = str(nsec_string_to_datetime(job.packet_end_time))
bpf_filter = job.data['config'].get('bpf_filter', '')
if len(bpf_filter) > self.MAX_LENGTH:
bpf_filter = bpf_filter[:self.MAX_LENGTH - 2] + '...'
pkts_dropped = job.get_stats()['packets_dropped']
pkts_written = job.get_stats()['packets_written']
job_data = dict(netshark=sk.name,
job_id=job.data['id'],
job_name=job.data['config']['name'],
interface=if_name,
state=job.data['status']['state'],
size=job.data['status']['packet_size'],
start_time=start,
end_time=end,
bpf_filter=bpf_filter,
dpi_enabled=str(job.dpi_enabled),
index_enabled=str(job.index_enabled),
last_sec_dropped=pkts_dropped['last_second'],
last_min_dropped=pkts_dropped['last_minute'],
last_hr_dropped=pkts_dropped['last_hour'],
last_sec_written=pkts_written['last_second'],
last_min_written=pkts_written['last_minute'],
last_hr_written=pkts_written['last_hour'])
res.append(job_data)
return QueryComplete(pandas.DataFrame(res))
def _convert_sample_time(self, sample_timestamp):
if self.view.timestamp_format == APITimestampFormat.SECOND:
return timeutils.sec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.MILLISECOND:
return timeutils.msec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.MICROSECOND:
return timeutils.usec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.NANOSECOND:
return timeutils.nsec_string_to_datetime(sample_timestamp)
else:
raise ValueError('invalid time format %s' % str(view.timestamp_format))
def _convert_sample_time(self, sample_timestamp):
if self.view.timestamp_format == APITimestampFormat.SECOND:
return timeutils.sec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.MILLISECOND:
return timeutils.msec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.MICROSECOND:
return timeutils.usec_string_to_datetime(sample_timestamp)
elif self.view.timestamp_format == APITimestampFormat.NANOSECOND:
return timeutils.nsec_string_to_datetime(sample_timestamp)
else:
raise ValueError('invalid time format %s' %
str(view.timestamp_format))
def _to_native(string, legend_entry):
""" convert `string` to an appropriate native type given `legend_entry` """
if legend_entry['calculation'] == 'AVG':
string, den = string.split(':', 1)
denominator = int(den)
else:
denominator = 1
if legend_entry['type'].startswith('INT') \
or legend_entry['type'].startswith('UINT') \
or legend_entry['type'] in ( 'TCP_PORT', 'UDP_PORT'):
if legend_entry['base'] == 'DEC':
baseval = 10
elif legend_entry['base'] == 'HEX':
baseval = 16
else:
raise ValueError('do not know how to handle integer base %s' %
legend_entry['base'])
return int(string, baseval) / denominator
if legend_entry['type'] == 'DOUBLE':
return float(string) / denominator
if legend_entry['type'] == 'BOOLEAN':
if string.lower() == 'false' or string.lower() == '0':
return 0
elif string.lower() == 'true' or string.lower() == '1':
return 1
else:
# Booleans can be a count of successes
return int(string)
if legend_entry['type'] == 'ABSOLUTE_TIME':
return timeutils.nsec_string_to_datetime(string)
if legend_entry['type'] == 'RELATIVE_TIME':
return float(string) / denominator
# XXX anything with IPv4 or ETHER?
return string
def _to_native(string, legend_entry):
""" convert `string` to an appropriate native type given `legend_entry` """
if legend_entry['calculation'] == 'AVG':
string, den = string.split(':', 1)
denominator = int(den)
else:
denominator = 1
if (legend_entry['type'].startswith('INT')
or legend_entry['type'].startswith('UINT')
or legend_entry['type'] in ('TCP_PORT', 'UDP_PORT')):
if legend_entry['base'] == 'DEC':
baseval = 10
elif legend_entry['base'] == 'HEX':
baseval = 16
else:
raise ValueError('do not know how to handle integer base %s' %
legend_entry['base'])
return int(string, baseval) / denominator
if legend_entry['type'] == 'DOUBLE':
return float(string) / denominator
if legend_entry['type'] == 'BOOLEAN':
if string.lower() == 'false' or string.lower() == '0':
return 0
elif string.lower() == 'true' or string.lower() == '1':
return 1
else:
# Booleans can be a count of successes
return int(string)
if legend_entry['type'] == 'ABSOLUTE_TIME':
return timeutils.nsec_string_to_datetime(string)
if legend_entry['type'] == 'RELATIVE_TIME':
return float(string) / denominator
# XXX anything with IPv4 or ETHER?
return string
