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jc/jc/parsers/lsmod.py
2021-04-18 16:33:47 -07:00

197 lines
3.8 KiB
Python

"""jc - JSON CLI output utility `lsmod` command output parser
Usage (cli):
$ lsmod | jc --lsmod
or
$ jc lsmod
Usage (module):
import jc.parsers.lsmod
result = jc.parsers.lsmod.parse(lsmod_command_output)
Schema:
[
{
"module": string,
"size": integer,
"used": integer,
"by": [
string
]
}
]
Examples:
$ lsmod | jc --lsmod -p
[
...
{
"module": "nf_nat",
"size": 26583,
"used": 3,
"by": [
"nf_nat_ipv4",
"nf_nat_ipv6",
"nf_nat_masquerade_ipv4"
]
},
{
"module": "iptable_mangle",
"size": 12695,
"used": 1
},
{
"module": "iptable_security",
"size": 12705,
"used": 1
},
{
"module": "iptable_raw",
"size": 12678,
"used": 1
},
{
"module": "nf_conntrack",
"size": 139224,
"used": 7,
"by": [
"nf_nat",
"nf_nat_ipv4",
"nf_nat_ipv6",
"xt_conntrack",
"nf_nat_masquerade_ipv4",
"nf_conntrack_ipv4",
"nf_conntrack_ipv6"
]
},
...
]
$ lsmod | jc --lsmod -p -r
[
...
{
"module": "nf_conntrack",
"size": "139224",
"used": "7",
"by": [
"nf_nat",
"nf_nat_ipv4",
"nf_nat_ipv6",
"xt_conntrack",
"nf_nat_masquerade_ipv4",
"nf_conntrack_ipv4",
"nf_conntrack_ipv6"
]
},
{
"module": "ip_set",
"size": "45799",
"used": "0"
},
{
"module": "nfnetlink",
"size": "14519",
"used": "1",
"by": [
"ip_set"
]
},
{
"module": "ebtable_filter",
"size": "12827",
"used": "1"
},
{
"module": "ebtables",
"size": "35009",
"used": "2",
"by": [
"ebtable_nat",
"ebtable_filter"
]
},
...
]
"""
import jc.utils
import jc.parsers.universal
class info():
"""Provides parser metadata (version, author, etc.)"""
version = '1.5'
description = '`lsmod` command parser'
author = 'Kelly Brazil'
author_email = 'kellyjonbrazil@gmail.com'
# compatible options: linux, darwin, cygwin, win32, aix, freebsd
compatible = ['linux']
magic_commands = ['lsmod']
__version__ = info.version
def _process(proc_data):
"""
Final processing to conform to the schema.
Parameters:
proc_data: (List of Dictionaries) raw structured data to process
Returns:
List of Dictionaries. Structured data to conform to the schema.
"""
for entry in proc_data:
int_list = ['size', 'used']
for key in entry:
if key in int_list:
entry[key] = jc.utils.convert_to_int(entry[key])
return proc_data
def parse(data, raw=False, quiet=False):
"""
Main text parsing function
Parameters:
data: (string) text data to parse
raw: (boolean) output preprocessed JSON if True
quiet: (boolean) suppress warning messages if True
Returns:
List of Dictionaries. Raw or processed structured data.
"""
if not quiet:
jc.utils.compatibility(__name__, info.compatible)
cleandata = data.splitlines()
raw_output = []
if jc.utils.has_data(data):
cleandata[0] = cleandata[0].lower()
raw_output = jc.parsers.universal.simple_table_parse(cleandata)
for mod in raw_output:
if 'by' in mod:
mod['by'] = mod['by'].split(',')
if raw:
return raw_output
else:
return _process(raw_output)