2021-04-09 10:36:42 -07:00
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[Home](https://kellyjonbrazil.github.io/jc/)
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2022-01-25 17:07:47 -08:00
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<a id="jc.parsers.csv"></a>
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2020-07-30 16:20:24 -07:00
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2020-03-02 14:03:58 -08:00
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# jc.parsers.csv
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2022-03-04 13:27:39 -08:00
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jc - JSON Convert `csv` file parser
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2022-01-19 17:30:14 -08:00
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The `csv` parser will attempt to automatically detect the delimiter
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character. If the delimiter cannot be detected it will default to comma.
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The first row of the file must be a header row.
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Usage (cli):
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$ cat file.csv | jc --csv
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Usage (module):
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import jc
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result = jc.parse('csv', csv_output)
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Schema:
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CSV file converted to a Dictionary:
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https://docs.python.org/3/library/csv.html
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[
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{
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"column_name1": string,
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"column_name2": string
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}
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]
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Examples:
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$ cat homes.csv
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"Sell", "List", "Living", "Rooms", "Beds", "Baths", "Age", "Acres"...
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142, 160, 28, 10, 5, 3, 60, 0.28, 3167
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175, 180, 18, 8, 4, 1, 12, 0.43, 4033
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129, 132, 13, 6, 3, 1, 41, 0.33, 1471
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...
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$ cat homes.csv | jc --csv -p
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[
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{
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"Sell": "142",
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"List": "160",
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"Living": "28",
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"Rooms": "10",
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"Beds": "5",
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"Baths": "3",
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"Age": "60",
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"Acres": "0.28",
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"Taxes": "3167"
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},
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{
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"Sell": "175",
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"List": "180",
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"Living": "18",
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"Rooms": "8",
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"Beds": "4",
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"Baths": "1",
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"Age": "12",
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"Acres": "0.43",
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"Taxes": "4033"
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},
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{
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"Sell": "129",
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"List": "132",
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"Living": "13",
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"Rooms": "6",
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"Beds": "3",
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"Baths": "1",
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"Age": "41",
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"Acres": "0.33",
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"Taxes": "1471"
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},
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...
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]
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<a id="jc.parsers.csv.parse"></a>
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2022-03-05 12:15:14 -08:00
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### parse
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```python
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def parse(data: Union[str, bytes],
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raw: bool = False,
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quiet: bool = False) -> List[JSONDictType]
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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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### Parser Information
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Compatibility: linux, darwin, cygwin, win32, aix, freebsd
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2022-10-25 11:49:02 -07:00
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Version 1.5 by Kelly Brazil (kellyjonbrazil@gmail.com)
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