mirror of
https://github.com/ilri/csv-metadata-quality.git
synced 2024-11-22 22:05:03 +01:00
Alan Orth
ed5612fbcf
This makes it easier to understand where the error is in case a CSV
has multiple date fields, for example:
Missing date (dc.date.issued).
Missing date (dc.date.issued[]).
If you have 126 items and you get 126 "Missing date" messages then
it's likely that 100 of the items have dates in one field, and the
others have dates in other field.
301 lines
8.4 KiB
Python
Executable File
301 lines
8.4 KiB
Python
Executable File
import pandas as pd
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def issn(field):
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"""Check if an ISSN is valid.
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Prints the ISSN if invalid.
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stdnum's is_valid() function never raises an exception.
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See: https://arthurdejong.org/python-stdnum/doc/1.11/index.html#stdnum.module.is_valid
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"""
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from stdnum import issn
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# Skip fields with missing values
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if pd.isna(field):
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return
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# Try to split multi-value field on "||" separator
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for value in field.split('||'):
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if not issn.is_valid(value):
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print(f'Invalid ISSN: {value}')
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return field
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def isbn(field):
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"""Check if an ISBN is valid.
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Prints the ISBN if invalid.
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stdnum's is_valid() function never raises an exception.
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See: https://arthurdejong.org/python-stdnum/doc/1.11/index.html#stdnum.module.is_valid
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"""
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from stdnum import isbn
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# Skip fields with missing values
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if pd.isna(field):
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return
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# Try to split multi-value field on "||" separator
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for value in field.split('||'):
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if not isbn.is_valid(value):
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print(f'Invalid ISBN: {value}')
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return field
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def separators(field):
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"""Check for invalid multi-value separators (ie "|" or "|||").
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Prints the field with the invalid multi-value separator.
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"""
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import re
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# Skip fields with missing values
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if pd.isna(field):
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return
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# Try to split multi-value field on "||" separator
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for value in field.split('||'):
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# After splitting, see if there are any remaining "|" characters
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match = re.findall(r'^.*?\|.*$', value)
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if match:
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print(f'Invalid multi-value separator: {field}')
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return field
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def date(field, field_name):
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"""Check if a date is valid.
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In DSpace the issue date is usually 1990, 1990-01, or 1990-01-01, but it
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could technically even include time as long as it is ISO8601.
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Also checks for other invalid cases like missing and multiple dates.
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Prints the date if invalid.
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"""
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from datetime import datetime
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if pd.isna(field):
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print(f'Missing date ({field_name}).')
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return
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# Try to split multi-value field on "||" separator
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multiple_dates = field.split('||')
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# We don't allow multi-value date fields
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if len(multiple_dates) > 1:
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print(f'Multiple dates not allowed ({field_name}): {field}')
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return field
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try:
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# Check if date is valid YYYY format
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datetime.strptime(field, '%Y')
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return field
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except ValueError:
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pass
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try:
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# Check if date is valid YYYY-MM format
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datetime.strptime(field, '%Y-%m')
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return field
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except ValueError:
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pass
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try:
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# Check if date is valid YYYY-MM-DD format
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datetime.strptime(field, '%Y-%m-%d')
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return field
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except ValueError:
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print(f'Invalid date ({field_name}): {field}')
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return field
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def suspicious_characters(field, field_name):
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"""Warn about suspicious characters.
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Look for standalone characters that could indicate encoding or copy/paste
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errors for languages with accents. For example: foreˆt should be forêt.
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"""
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# Skip fields with missing values
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if pd.isna(field):
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return
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# List of suspicious characters, for example: ́ˆ~`
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suspicious_characters = ['\u00B4', '\u02C6', '\u007E', '\u0060']
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for character in suspicious_characters:
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# Find the position of the suspicious character in the string
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suspicious_character_position = field.find(character)
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# Python returns -1 if there is no match
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if suspicious_character_position != -1:
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# Create a temporary new string starting from the position of the
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# suspicious character
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field_subset = field[suspicious_character_position:]
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# Print part of the metadata value starting from the suspicious
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# character and spanning enough of the rest to give a preview,
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# but not too much to cause the line to break in terminals with
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# a default of 80 characters width.
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suspicious_character_msg = f'Suspicious character ({field_name}): {field_subset}'
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print(f'{suspicious_character_msg:1.80}')
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return field
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def language(field):
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"""Check if a language is valid ISO 639-2 or ISO 639-3.
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Prints the value if it is invalid.
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"""
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from pycountry import languages
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# Skip fields with missing values
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if pd.isna(field):
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return
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# need to handle "Other" values here...
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# Try to split multi-value field on "||" separator
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for value in field.split('||'):
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# After splitting, check if language value is 2 or 3 characters so we
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# can check it against ISO 639-2 or ISO 639-3 accordingly.
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if len(value) == 2:
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if not languages.get(alpha_2=value):
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print(f'Invalid ISO 639-2 language: {value}')
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pass
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elif len(value) == 3:
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if not languages.get(alpha_3=value):
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print(f'Invalid ISO 639-3 language: {value}')
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pass
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else:
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print(f'Invalid language: {value}')
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return field
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def agrovoc(field, field_name):
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"""Check subject terms against AGROVOC REST API.
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Function constructor expects the field as well as the field name because
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many fields can now be validated against AGROVOC and we want to be able
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to inform the user in which field the invalid term is.
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Logic copied from agrovoc-lookup.py.
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See: https://github.com/ilri/DSpace/blob/5_x-prod/agrovoc-lookup.py
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Prints a warning if the value is invalid.
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"""
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from datetime import timedelta
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import re
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import requests
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import requests_cache
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# Skip fields with missing values
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if pd.isna(field):
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return
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# Try to split multi-value field on "||" separator
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for value in field.split('||'):
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# match lines beginning with words, paying attention to subjects with
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# special characters like spaces, quotes, dashes, parentheses, etc:
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# SUBJECT
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# ANOTHER SUBJECT
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# XANTHOMONAS CAMPESTRIS PV. MANIHOTIS
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# WOMEN'S PARTICIPATION
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# COMMUNITY-BASED FOREST MANAGEMENT
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# INTERACCIÓN GENOTIPO AMBIENTE
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# COCOA (PLANT)
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pattern = re.compile(r'^[\w\-\.\'\(\)]+?[\w\s\-\.\'\(\)]+$')
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if pattern.match(value):
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request_url = f'http://agrovoc.uniroma2.it/agrovoc/rest/v1/agrovoc/search?query={value}'
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# enable transparent request cache with thirty days expiry
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expire_after = timedelta(days=30)
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requests_cache.install_cache('agrovoc-response-cache', expire_after=expire_after)
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request = requests.get(request_url)
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# prune old cache entries
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requests_cache.core.remove_expired_responses()
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if request.status_code == requests.codes.ok:
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data = request.json()
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# check if there are any results
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if len(data['results']) == 0:
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print(f'Invalid AGROVOC ({field_name}): {value}')
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return field
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def filename_extension(field):
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"""Check filename extension.
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CSVs with a 'filename' column are likely meant as input for the SAFBuilder
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tool, which creates a Simple Archive Format bundle for importing metadata
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with accompanying PDFs or other files into DSpace.
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This check warns if a filename has an uncommon extension (that is, other
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than .pdf, .xls(x), .doc(x), ppt(x), case insensitive).
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"""
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import re
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# Skip fields with missing values
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if pd.isna(field):
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return
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# Try to split multi-value field on "||" separator
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values = field.split('||')
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# List of common filename extentions
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common_filename_extensions = ['.pdf', '.doc', '.docx', '.ppt', '.pptx', '.xls', '.xlsx']
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# Iterate over all values
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for value in values:
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# Assume filename extension does not match
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filename_extension_match = False
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for filename_extension in common_filename_extensions:
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# Check for extension at the end of the filename
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pattern = re.escape(filename_extension) + r'$'
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match = re.search(pattern, value, re.IGNORECASE)
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if match is not None:
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# Register the match and stop checking for this filename
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filename_extension_match = True
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break
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if filename_extension_match is False:
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print(f'Filename with uncommon extension: {value}')
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return field
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