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123 lines
2.4 KiB
Python
123 lines
2.4 KiB
Python
"""jc - JSON Convert `/proc/filesystems` file parser
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Usage (cli):
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$ cat /proc/filesystems | jc --proc
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or
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$ jc /proc/filesystems
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or
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$ cat /proc/filesystems | jc --proc-filesystems
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Usage (module):
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import jc
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result = jc.parse('proc', proc_filesystems_file)
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or
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import jc
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result = jc.parse('proc_filesystems', proc_filesystems_file)
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Schema:
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[
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{
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"filesystem": string,
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"nodev": boolean
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}
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]
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Examples:
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$ cat /proc/filesystems | jc --proc -p
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[
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{
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"filesystem": "sysfs",
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"nodev": true
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},
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{
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"filesystem": "tmpfs",
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"nodev": true
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},
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{
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"filesystem": "bdev",
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"nodev": true
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},
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...
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]
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"""
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from typing import List, Dict
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import jc.utils
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class info():
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"""Provides parser metadata (version, author, etc.)"""
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version = '1.0'
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description = '`/proc/filesystems` file 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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hidden = True
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__version__ = info.version
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def _process(proc_data: List[Dict]) -> List[Dict]:
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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 to conform to the schema.
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"""
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return proc_data
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def parse(
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data: str,
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raw: bool = False,
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quiet: bool = False
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) -> List[Dict]:
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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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raw_output: List = []
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if jc.utils.has_data(data):
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for line in filter(None, data.splitlines()):
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split_line = line.split()
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output_line = {'filesystem': split_line[-1]}
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if len(split_line) == 2:
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output_line['nodev'] = True # type: ignore
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else:
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output_line['nodev'] = False # type: ignore
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raw_output.append(output_line)
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return raw_output if raw else _process(raw_output)
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