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csv-metadata-quality/csv_metadata_quality/check.py
Alan Orth 884e8f970d
csv_metadata_quality/check.py: Simplify AGROVOC check
I recycled this code from a separate agrovoc-lookup.py script that
checks lines in a text file to see if they are valid AGROVOC terms
or not. There I was concerned about skipping comments or something
I think, but we don't need to check that here. We simply check the
term that is in the field and inform the user if it's valid or not.
2019-08-21 16:35:29 +03:00

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import pandas as pd
def issn(field):
"""Check if an ISSN is valid.
Prints the ISSN if invalid.
stdnum's is_valid() function never raises an exception.
See: https://arthurdejong.org/python-stdnum/doc/1.11/index.html#stdnum.module.is_valid
"""
from stdnum import issn
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
for value in field.split('||'):
if not issn.is_valid(value):
print(f'Invalid ISSN: {value}')
return field
def isbn(field):
"""Check if an ISBN is valid.
Prints the ISBN if invalid.
stdnum's is_valid() function never raises an exception.
See: https://arthurdejong.org/python-stdnum/doc/1.11/index.html#stdnum.module.is_valid
"""
from stdnum import isbn
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
for value in field.split('||'):
if not isbn.is_valid(value):
print(f'Invalid ISBN: {value}')
return field
def separators(field):
"""Check for invalid multi-value separators (ie "|" or "|||").
Prints the field with the invalid multi-value separator.
"""
import re
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
for value in field.split('||'):
# After splitting, see if there are any remaining "|" characters
match = re.findall(r'^.*?\|.*$', value)
if match:
print(f'Invalid multi-value separator: {field}')
return field
def date(field, field_name):
"""Check if a date is valid.
In DSpace the issue date is usually 1990, 1990-01, or 1990-01-01, but it
could technically even include time as long as it is ISO8601.
Also checks for other invalid cases like missing and multiple dates.
Prints the date if invalid.
"""
from datetime import datetime
if pd.isna(field):
print(f'Missing date ({field_name}).')
return
# Try to split multi-value field on "||" separator
multiple_dates = field.split('||')
# We don't allow multi-value date fields
if len(multiple_dates) > 1:
print(f'Multiple dates not allowed ({field_name}): {field}')
return field
try:
# Check if date is valid YYYY format
datetime.strptime(field, '%Y')
return field
except ValueError:
pass
try:
# Check if date is valid YYYY-MM format
datetime.strptime(field, '%Y-%m')
return field
except ValueError:
pass
try:
# Check if date is valid YYYY-MM-DD format
datetime.strptime(field, '%Y-%m-%d')
return field
except ValueError:
print(f'Invalid date ({field_name}): {field}')
return field
def suspicious_characters(field, field_name):
"""Warn about suspicious characters.
Look for standalone characters that could indicate encoding or copy/paste
errors for languages with accents. For example: foreˆt should be forêt.
"""
# Skip fields with missing values
if pd.isna(field):
return
# List of suspicious characters, for example: ́ˆ~`
suspicious_characters = ['\u00B4', '\u02C6', '\u007E', '\u0060']
for character in suspicious_characters:
# Find the position of the suspicious character in the string
suspicious_character_position = field.find(character)
# Python returns -1 if there is no match
if suspicious_character_position != -1:
# Create a temporary new string starting from the position of the
# suspicious character
field_subset = field[suspicious_character_position:]
# Print part of the metadata value starting from the suspicious
# character and spanning enough of the rest to give a preview,
# but not too much to cause the line to break in terminals with
# a default of 80 characters width.
suspicious_character_msg = f'Suspicious character ({field_name}): {field_subset}'
print(f'{suspicious_character_msg:1.80}')
return field
def language(field):
"""Check if a language is valid ISO 639-2 or ISO 639-3.
Prints the value if it is invalid.
"""
from pycountry import languages
# Skip fields with missing values
if pd.isna(field):
return
# need to handle "Other" values here...
# Try to split multi-value field on "||" separator
for value in field.split('||'):
# After splitting, check if language value is 2 or 3 characters so we
# can check it against ISO 639-2 or ISO 639-3 accordingly.
if len(value) == 2:
if not languages.get(alpha_2=value):
print(f'Invalid ISO 639-2 language: {value}')
pass
elif len(value) == 3:
if not languages.get(alpha_3=value):
print(f'Invalid ISO 639-3 language: {value}')
pass
else:
print(f'Invalid language: {value}')
return field
def agrovoc(field, field_name):
"""Check subject terms against AGROVOC REST API.
Function constructor expects the field as well as the field name because
many fields can now be validated against AGROVOC and we want to be able
to inform the user in which field the invalid term is.
Logic copied from agrovoc-lookup.py.
See: https://github.com/ilri/DSpace/blob/5_x-prod/agrovoc-lookup.py
Prints a warning if the value is invalid.
"""
from datetime import timedelta
import requests
import requests_cache
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
for value in field.split('||'):
request_url = f'http://agrovoc.uniroma2.it/agrovoc/rest/v1/agrovoc/search?query={value}'
# enable transparent request cache with thirty days expiry
expire_after = timedelta(days=30)
requests_cache.install_cache('agrovoc-response-cache', expire_after=expire_after)
request = requests.get(request_url)
# prune old cache entries
requests_cache.core.remove_expired_responses()
if request.status_code == requests.codes.ok:
data = request.json()
# check if there are any results
if len(data['results']) == 0:
print(f'Invalid AGROVOC ({field_name}): {value}')
return field
def filename_extension(field):
"""Check filename extension.
CSVs with a 'filename' column are likely meant as input for the SAFBuilder
tool, which creates a Simple Archive Format bundle for importing metadata
with accompanying PDFs or other files into DSpace.
This check warns if a filename has an uncommon extension (that is, other
than .pdf, .xls(x), .doc(x), ppt(x), case insensitive).
"""
import re
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
values = field.split('||')
# List of common filename extentions
common_filename_extensions = ['.pdf', '.doc', '.docx', '.ppt', '.pptx', '.xls', '.xlsx']
# Iterate over all values
for value in values:
# Assume filename extension does not match
filename_extension_match = False
for filename_extension in common_filename_extensions:
# Check for extension at the end of the filename
pattern = re.escape(filename_extension) + r'$'
match = re.search(pattern, value, re.IGNORECASE)
if match is not None:
# Register the match and stop checking for this filename
filename_extension_match = True
break
if filename_extension_match is False:
print(f'Filename with uncommon extension: {value}')
return field