simple linter that checks datasets for IPA errors and inconsistencies
Checks linguistic datasets for IPA errors and inconsistencies. Usage:
This will either (1) print the IPA errors found in the dataset; (2) print nothing, meaning it found no errors; or (3) print an error message if it fails to read the file. In no case will the input file be modified.
The linter should be able to read any well-formed csv/tsv/tab dataset, assuming that there is an IPA data column. It also reads table-less lines and handles pipes; thus, even if you have a less common format like this one, you can still lint it by doing something like:
cat KSL.qlc | grep "^[[:digit:]]" | cut -f 6 | ipalint
--col COL specifies the column containing the IPA data; this can be either the column name or the column index (starting from 0). If this option is not set, ipalint will try to guess the column by looking at the column names.
--no-header treats the first row as data. The default is to treat the first row as header and not lint it.
--ignore-nfd ignores errors about an IPA string that are not in Unicode’s NFD normal form. With very few exceptions, IPA diacritics should be combining characters. However, in some situations this might be irrelevant for your purposes and you can ignore these errors.
--ignore-ws ignores errors about leading or trailing whitespace in IPA strings. If combined with the previous flag, ipalint will only report errors about symbols that are not part of the IPA chart.
--linewise outputs (line number, error message) tuples, one such tuple per line of output. The default is to output the set of errors and include the list of line numbers to the right of each error.
--no-lines only outputs the set of errors found in the data. Useful when you want a quick glimpse of what might be wrong. This flag is ignored if the previous one is set.
what is checked
This is a standard Python 3 package without dependencies. It is offered at the Cheese Shop, so you can install it through pip:
pip install ipalint
or, alternatively, you can clone this repo (safe to delete afterwards) and do:
python setup.py test python setup.py install
Of course, this could be happening within a virtualenv/venv as well.
MIT. Do as you please and praise the snake gods.
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