mirror of
https://github.com/kellyjonbrazil/jc.git
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144 lines
3.0 KiB
Python
144 lines
3.0 KiB
Python
"""jc - JSON Convert `free` command output parser
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Usage (cli):
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$ free | jc --free
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or
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$ jc free
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Usage (module):
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import jc
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result = jc.parse('free', free_command_output)
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Schema:
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[
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{
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"type": string,
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"total": integer,
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"used": integer,
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"free": integer,
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"shared": integer,
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"buff_cache": integer,
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"available": integer
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}
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]
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Examples:
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$ free | jc --free -p
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[
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{
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"type": "Mem",
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"total": 3861340,
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"used": 220508,
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"free": 3381972,
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"shared": 11800,
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"buff_cache": 258860,
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"available": 3397784
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},
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{
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"type": "Swap",
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"total": 2097148,
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"used": 0,
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"free": 2097148
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}
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]
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$ free | jc --free -p -r
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[
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{
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"type": "Mem",
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"total": "2017300",
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"used": "213104",
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"free": "1148452",
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"shared": "1176",
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"buff_cache": "655744",
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"available": "1622204"
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},
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{
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"type": "Swap",
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"total": "2097148",
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"used": "0",
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"free": "2097148"
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}
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]
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"""
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import jc.utils
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import jc.parsers.universal
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class info():
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"""Provides parser metadata (version, author, etc.)"""
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version = '1.6'
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description = '`free` command parser'
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author = 'Kelly Brazil'
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author_email = 'kellyjonbrazil@gmail.com'
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compatible = ['linux']
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magic_commands = ['free']
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__version__ = info.version
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def _process(proc_data):
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"""
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Final processing to conform to the schema.
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Parameters:
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proc_data: (List of Dictionaries) raw structured data to process
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Returns:
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List of Dictionaries. Structured data to conform to the schema.
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"""
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int_list = {'total', 'used', 'free', 'shared', 'buff_cache', 'buffers', 'cache', 'available'}
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for entry in proc_data:
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for key in entry:
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if key in int_list:
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entry[key] = jc.utils.convert_to_int(entry[key])
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return proc_data
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def parse(data, raw=False, quiet=False):
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"""
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Main text parsing function
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Parameters:
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data: (string) text data to parse
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raw: (boolean) unprocessed output if True
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quiet: (boolean) suppress warning messages if True
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Returns:
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List of Dictionaries. Raw or processed structured data.
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"""
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jc.utils.compatibility(__name__, info.compatible, quiet)
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jc.utils.input_type_check(data)
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cleandata = data.splitlines()
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raw_output = []
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if jc.utils.has_data(data):
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cleandata[0] = cleandata[0].lower()
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cleandata[0] = cleandata[0].replace('buff/cache', 'buff_cache')
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cleandata[0] = 'type ' + cleandata[0]
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raw_output = jc.parsers.universal.simple_table_parse(cleandata)
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for entry in raw_output:
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entry['type'] = entry['type'].rstrip(':')
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if raw:
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return raw_output
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else:
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return _process(raw_output)
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