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jc/jc/parsers/w.py

199 lines
4.7 KiB
Python

"""jc - JSON CLI output utility `w` command output parser
Usage (cli):
$ w | jc --w
or
$ jc w
Usage (module):
import jc.parsers.w
result = jc.parsers.w.parse(w_command_output)
Schema:
[
{
"user": string, # '-' = null
"tty": string, # '-' = null
"from": string, # '-' = null
"login_at": string, # '-' = null
"idle": string, # '-' = null
"jcpu": string,
"pcpu": string,
"what": string # '-' = null
}
]
Examples:
$ w | jc --w -p
[
{
"user": "root",
"tty": "tty1",
"from": null,
"login_at": "07:49",
"idle": "1:15m",
"jcpu": "0.00s",
"pcpu": "0.00s",
"what": "-bash"
},
{
"user": "root",
"tty": "ttyS0",
"from": null,
"login_at": "06:24",
"idle": "0.00s",
"jcpu": "0.43s",
"pcpu": "0.00s",
"what": "w"
},
{
"user": "root",
"tty": "pts/0",
"from": "192.168.71.1",
"login_at": "06:29",
"idle": "2:35m",
"jcpu": "0.00s",
"pcpu": "0.00s",
"what": "-bash"
}
]
$ w | jc --w -p -r
[
{
"user": "kbrazil",
"tty": "tty1",
"from": "-",
"login_at": "07:49",
"idle": "1:16m",
"jcpu": "0.00s",
"pcpu": "0.00s",
"what": "-bash"
},
{
"user": "kbrazil",
"tty": "ttyS0",
"from": "-",
"login_at": "06:24",
"idle": "2.00s",
"jcpu": "0.46s",
"pcpu": "0.00s",
"what": "w"
},
{
"user": "kbrazil",
"tty": "pts/0",
"from": "192.168.71.1",
"login_at": "06:29",
"idle": "2:36m",
"jcpu": "0.00s",
"pcpu": "0.00s",
"what": "-bash"
}
]
"""
import string
import jc.utils
class info():
"""Provides parser metadata (version, author, etc.)"""
version = '1.5'
description = '`w` command parser'
author = 'Kelly Brazil'
author_email = 'kellyjonbrazil@gmail.com'
# compatible options: linux, darwin, cygwin, win32, aix, freebsd
compatible = ['linux', 'darwin', 'cygwin', 'aix', 'freebsd']
magic_commands = ['w']
__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:
null_list = ['user', 'tty', 'from', 'login_at', 'idle', 'what']
for key in entry:
if key in null_list:
if entry[key] == '-':
entry[key] = None
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.
"""
jc.utils.compatibility(__name__, info.compatible, quiet)
jc.utils.input_type_check(data)
cleandata = data.splitlines()[1:]
raw_output = []
if jc.utils.has_data(data):
header_text = cleandata[0].lower()
# fixup for 'from' column that can be blank
from_col = header_text.find('from')
# clean up 'login@' header
# even though @ in a key is valid json, it can make things difficult
header_text = header_text.replace('login@', 'login_at')
headers = [h for h in ' '.join(header_text.strip().split()).split() if h]
# parse lines
raw_output = []
if cleandata:
for entry in cleandata[1:]:
output_line = {}
# normalize data by inserting Null for missing data
temp_line = entry.split(maxsplit=len(headers) - 1)
# fix from column, always at column 2
if 'from' in headers:
if entry[from_col] in string.whitespace:
temp_line.insert(2, '-')
output_line = dict(zip(headers, temp_line))
raw_output.append(output_line)
# strip whitespace from beginning and end of all string values
for row in raw_output:
for item in row:
if isinstance(row[item], str):
row[item] = row[item].strip()
if raw:
return raw_output
else:
return _process(raw_output)