mirror of
https://github.com/kellyjonbrazil/jc.git
synced 2025-06-23 00:29:59 +02:00
108 lines
2.0 KiB
Python
108 lines
2.0 KiB
Python
"""jc - JSON Convert `/proc/<pid>/io` file parser
|
|
|
|
Usage (cli):
|
|
|
|
$ cat /proc/1/io | jc --proc
|
|
|
|
or
|
|
|
|
$ jc /proc/1/io
|
|
|
|
or
|
|
|
|
$ cat /proc/1/io | jc --proc-pid-io
|
|
|
|
Usage (module):
|
|
|
|
import jc
|
|
result = jc.parse('proc', proc_pid_io_file)
|
|
|
|
or
|
|
|
|
import jc
|
|
result = jc.parse('proc_pid_io', proc_pid_io_file)
|
|
|
|
Schema:
|
|
|
|
All values are integers.
|
|
|
|
{
|
|
<keyName> integer
|
|
}
|
|
|
|
Examples:
|
|
|
|
$ cat /proc/1/io | jc --proc -p
|
|
{
|
|
"rchar": 4699288382,
|
|
"wchar": 2931802997,
|
|
"syscr": 661897,
|
|
"syscw": 890910,
|
|
"read_bytes": 168468480,
|
|
"write_bytes": 27357184,
|
|
"cancelled_write_bytes": 16883712
|
|
}
|
|
"""
|
|
from typing import Dict
|
|
import jc.utils
|
|
|
|
|
|
class info():
|
|
"""Provides parser metadata (version, author, etc.)"""
|
|
version = '1.0'
|
|
description = '`/proc/<pid>/io` file parser'
|
|
author = 'Kelly Brazil'
|
|
author_email = 'kellyjonbrazil@gmail.com'
|
|
compatible = ['linux']
|
|
hidden = True
|
|
|
|
|
|
__version__ = info.version
|
|
|
|
|
|
def _process(proc_data: Dict) -> Dict:
|
|
"""
|
|
Final processing to conform to the schema.
|
|
|
|
Parameters:
|
|
|
|
proc_data: (Dictionary) raw structured data to process
|
|
|
|
Returns:
|
|
|
|
Dictionary. Structured to conform to the schema.
|
|
"""
|
|
return proc_data
|
|
|
|
|
|
def parse(
|
|
data: str,
|
|
raw: bool = False,
|
|
quiet: bool = False
|
|
) -> Dict:
|
|
"""
|
|
Main text parsing function
|
|
|
|
Parameters:
|
|
|
|
data: (string) text data to parse
|
|
raw: (boolean) unprocessed output if True
|
|
quiet: (boolean) suppress warning messages if True
|
|
|
|
Returns:
|
|
|
|
Dictionary. Raw or processed structured data.
|
|
"""
|
|
jc.utils.compatibility(__name__, info.compatible, quiet)
|
|
jc.utils.input_type_check(data)
|
|
|
|
raw_output: Dict = {}
|
|
|
|
if jc.utils.has_data(data):
|
|
|
|
for line in filter(None, data.splitlines()):
|
|
key, val = line.split(':', maxsplit=1)
|
|
raw_output[key] = int(val)
|
|
|
|
return raw_output if raw else _process(raw_output)
|