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117 lines
4.1 KiB
Python
117 lines
4.1 KiB
Python
"""jc - JSON CLI output utility universal Parsers"""
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import string
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from typing import List, Dict, Optional
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def simple_table_parse(data: List[str]) -> List[Dict]:
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"""
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Parse simple tables. The last column may contain data with spaces.
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Parameters:
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data: (list) Text data to parse that has been split into lines
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via .splitlines(). Item 0 must be the header row.
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Any spaces in header names should be changed to
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underscore '_'. You should also ensure headers are
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lowercase by using .lower().
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Also, ensure there are no blank lines (list items)
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in the data.
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Returns:
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List of Dictionaries
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"""
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# code adapted from Conor Heine at:
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# https://gist.github.com/cahna/43a1a3ff4d075bcd71f9d7120037a501
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headers = [h for h in ' '.join(data[0].strip().split()).split() if h]
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raw_data = map(lambda s: s.strip().split(None, len(headers) - 1), data[1:])
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raw_output = [dict(zip(headers, r)) for r in raw_data]
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return raw_output
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def sparse_table_parse(data: List[str], delim: Optional[str] ='\u2063') -> List[Dict]:
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"""
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Parse tables with missing column data or with spaces in column data.
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Parameters:
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data: (list) Text data to parse that has been split into lines
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via .splitlines(). Item 0 must be the header row.
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Any spaces in header names should be changed to
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underscore '_'. You should also ensure headers are
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lowercase by using .lower(). Do not change the
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position of header names as the positions are used
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to find the data.
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Also, ensure there are no blank lines (list items)
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in the data.
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delim: (string) Delimiter to use. By default `u\\2063`
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(invisible separator) is used since it is unlikely
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to ever be seen in terminal output. You can change
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this for troubleshooting purposes or if there is a
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delimiter conflict with your data.
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Returns:
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List of Dictionaries
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"""
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output = []
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header_text = data.pop(0)
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header_text = header_text + ' '
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header_list = header_text.split()
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# find each column index and end position
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header_search = [header_list[0]]
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for h in header_list[1:]:
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header_search.append(' ' + h + ' ')
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header_spec_list = []
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for i, column in enumerate(header_list[0:len(header_list) - 1]):
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header_spec = {
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'name': column,
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'end': header_text.find(header_search[i + 1])
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}
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header_spec_list.append(header_spec)
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# parse lines
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if data:
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for entry in data:
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output_line = {}
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# insert new separator since data can contain spaces
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for col in reversed(header_list):
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# find the right header_spec
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for h_spec in header_spec_list:
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if h_spec['name'] == col:
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h_end = h_spec['end']
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# check if the location contains whitespace. if not
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# then move to the left until a space is found
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while h_end > 0 and entry[h_end] not in string.whitespace:
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h_end -= 1
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# insert custom delimiter
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entry = entry[:h_end] + delim + entry[h_end + 1:]
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# create the entry list from the new custom delimiter
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entry_list = entry.split(delim, maxsplit=len(header_list) - 1)
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# clean up leading and trailing spaces in entry
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clean_entry_list = []
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for col in entry_list:
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clean_entry = col.strip()
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if clean_entry == '':
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clean_entry = None
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clean_entry_list.append(clean_entry)
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output_line = dict(zip(header_list, clean_entry_list))
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output.append(output_line)
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return output
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