By using df[column] = df[column].apply(check...) we were re-writing
the DataFrame every time we returned from a check. We don't actuall
y need to return a value at all, as the point of checks is to print
a warning to the screen. In Python a "return" statement without a v
ariable returns None.
I haven't measured the impact of this, but I assume it will mean we
are faster and use less memory.
Works decenty well assuming the title, abstract, and citation fields
are an accurate representation of the language as identified by the
language field. Handles ISO 639-1 (alpha 2) and ISO 639-3 (alpha 3)
values seamlessly.
This includes updated pipenv environment, test data, pytest tests
for both correct and incorrect ISO 639-1 and ISO 639-3 languages,
and a new command line option "-e".
ISO 639-1 uses two-letter codes and ISO 639-3 uses three-letter codes.
Technically there ISO 639-2/T and ISO 639-2/B, which also uses three
letter codes, but those are not supported by the pycountry library
so I won't even worry about them.
See: https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes
Will validate against ISO 639-2 or ISO 639-3 depending on how long
the language field is. Otherwise will return that the language is
invalid.
Does not currently have any support for generic values like "Other".
These standalone characters often indicate issues with encoding or
copy/paste in languages with accents like French and Spanish. For
example: foreˆt should be forêt.
It is not possible to fix these issues automatically, but this will
print a warning so you can notify the owner of the data.
I'm only concerned with validating issue dates here. In DSpace they
are generally always YYYY, YYY-MM, or YYYY-MM-DD (though in theory
they could be any valid ISO8601 format).
This also checks for cases where the date is missing and where the
metadata has specified multiple dates like "1990||1991", as this is
valid, but there is no practical value for it in our system.
