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https://github.com/ilri/csv-metadata-quality.git
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@ -9,13 +9,37 @@ import sys
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def parse_args(argv):
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parser = argparse.ArgumentParser(description='Metadata quality checker and fixer.')
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parser.add_argument('--agrovoc-fields', '-a', help='Comma-separated list of fields to validate against AGROVOC, for example: dc.subject,cg.coverage.country')
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parser.add_argument('--input-file', '-i', help='Path to input file. Can be UTF-8 CSV or Excel XLSX.', required=True, type=argparse.FileType('r', encoding='UTF-8'))
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parser.add_argument('--output-file', '-o', help='Path to output file (always CSV).', required=True, type=argparse.FileType('w', encoding='UTF-8'))
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parser.add_argument('--unsafe-fixes', '-u', help='Perform unsafe fixes.', action='store_true')
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parser.add_argument('--version', '-V', action='version', version=f'CSV Metadata Quality v{VERSION}')
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parser.add_argument('--exclude-fields', '-x', help='Comma-separated list of fields to skip, for example: dc.contributor.author,dc.identifier.citation')
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parser = argparse.ArgumentParser(description="Metadata quality checker and fixer.")
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parser.add_argument(
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"--agrovoc-fields",
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"-a",
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help="Comma-separated list of fields to validate against AGROVOC, for example: dc.subject,cg.coverage.country",
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)
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parser.add_argument(
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"--input-file",
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"-i",
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help="Path to input file. Can be UTF-8 CSV or Excel XLSX.",
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required=True,
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type=argparse.FileType("r", encoding="UTF-8"),
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)
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parser.add_argument(
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"--output-file",
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"-o",
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help="Path to output file (always CSV).",
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required=True,
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type=argparse.FileType("w", encoding="UTF-8"),
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)
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parser.add_argument(
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"--unsafe-fixes", "-u", help="Perform unsafe fixes.", action="store_true"
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)
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parser.add_argument(
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"--version", "-V", action="version", version=f"CSV Metadata Quality v{VERSION}"
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)
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parser.add_argument(
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"--exclude-fields",
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"-x",
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help="Comma-separated list of fields to skip, for example: dc.contributor.author,dc.identifier.citation",
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)
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args = parser.parse_args()
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return args
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@ -40,11 +64,11 @@ def run(argv):
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skip = False
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# Split the list of excludes on ',' so we can test exact matches
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# rather than fuzzy matches with regexes or "if word in string"
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for exclude in args.exclude_fields.split(','):
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for exclude in args.exclude_fields.split(","):
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if column == exclude and skip is False:
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skip = True
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if skip:
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print(f'Skipping {column}')
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print(f"Skipping {column}")
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continue
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@ -58,7 +82,7 @@ def run(argv):
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# Fix: missing space after comma. Only run on author and citation
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# fields for now, as this problem is mostly an issue in names.
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if args.unsafe_fixes:
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match = re.match(r'^.*?(author|citation).*$', column)
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match = re.match(r"^.*?(author|citation).*$", column)
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if match is not None:
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df[column] = df[column].apply(fix.comma_space, field_name=column)
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@ -83,32 +107,32 @@ def run(argv):
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# Check: invalid AGROVOC subject
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if args.agrovoc_fields:
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# Identify fields the user wants to validate against AGROVOC
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for field in args.agrovoc_fields.split(','):
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for field in args.agrovoc_fields.split(","):
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if column == field:
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df[column] = df[column].apply(check.agrovoc, field_name=column)
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# Check: invalid language
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match = re.match(r'^.*?language.*$', column)
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match = re.match(r"^.*?language.*$", column)
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if match is not None:
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df[column] = df[column].apply(check.language)
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# Check: invalid ISSN
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match = re.match(r'^.*?issn.*$', column)
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match = re.match(r"^.*?issn.*$", column)
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if match is not None:
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df[column] = df[column].apply(check.issn)
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# Check: invalid ISBN
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match = re.match(r'^.*?isbn.*$', column)
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match = re.match(r"^.*?isbn.*$", column)
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if match is not None:
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df[column] = df[column].apply(check.isbn)
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# Check: invalid date
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match = re.match(r'^.*?date.*$', column)
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match = re.match(r"^.*?date.*$", column)
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if match is not None:
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df[column] = df[column].apply(check.date, field_name=column)
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# Check: filename extension
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if column == 'filename':
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if column == "filename":
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df[column] = df[column].apply(check.filename_extension)
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# Write
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