mirror of
https://github.com/ilri/csv-metadata-quality.git
synced 2024-11-16 02:57:04 +01:00
Alan Orth
9100efdf50
Add a setup.py so that installation is easier and a standalone CLI
script called csv-metadata-quality is provided. Now the user only
needs to run this from a virtual environment inside the project
directory:
$ pip install .
Eventually I could publish this on PyPi when I settle on a more
appropriate package name.
See: https://packaging.python.org/tutorials/packaging-projects/
See: https://chriswarrick.com/blog/2014/09/15/python-apps-the-right-way-entry_points-and-scripts/
77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
import argparse
|
|
import csv_metadata_quality.check as check
|
|
import csv_metadata_quality.fix as fix
|
|
import pandas as pd
|
|
import re
|
|
|
|
|
|
def parse_args(argv):
|
|
parser = argparse.ArgumentParser(description='Metadata quality checker and fixer.')
|
|
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'))
|
|
parser.add_argument('--output-file', '-o', help='Path to output file (always CSV).', required=True, type=argparse.FileType('w', encoding='UTF-8'))
|
|
parser.add_argument('--unsafe-fixes', '-u', help='Perform unsafe fixes.', action='store_true')
|
|
args = parser.parse_args()
|
|
|
|
return args
|
|
|
|
|
|
def run(argv):
|
|
args = parse_args(argv)
|
|
|
|
# Read all fields as strings so dates don't get converted from 1998 to 1998.0
|
|
df = pd.read_csv(args.input_file, dtype=str)
|
|
|
|
for column in df.columns.values.tolist():
|
|
# Fix: whitespace
|
|
df[column] = df[column].apply(fix.whitespace)
|
|
|
|
# Fix: newlines
|
|
if args.unsafe_fixes:
|
|
df[column] = df[column].apply(fix.newlines)
|
|
|
|
# Fix: unnecessary Unicode
|
|
df[column] = df[column].apply(fix.unnecessary_unicode)
|
|
|
|
# Check: invalid multi-value separator
|
|
df[column] = df[column].apply(check.separators)
|
|
|
|
# Check: suspicious characters
|
|
df[column] = df[column].apply(check.suspicious_characters)
|
|
|
|
# Fix: invalid multi-value separator
|
|
if args.unsafe_fixes:
|
|
df[column] = df[column].apply(fix.separators)
|
|
# Run whitespace fix again after fixing invalid separators
|
|
df[column] = df[column].apply(fix.whitespace)
|
|
|
|
# Fix: duplicate metadata values
|
|
df[column] = df[column].apply(fix.duplicates)
|
|
|
|
# Check: invalid AGROVOC subject
|
|
match = re.match(r'.*?dc\.subject.*$', column)
|
|
if match is not None:
|
|
df[column] = df[column].apply(check.agrovoc)
|
|
|
|
# Check: invalid language
|
|
match = re.match(r'^.*?language.*$', column)
|
|
if match is not None:
|
|
df[column] = df[column].apply(check.language)
|
|
|
|
# Check: invalid ISSN
|
|
match = re.match(r'^.*?issn.*$', column)
|
|
if match is not None:
|
|
df[column] = df[column].apply(check.issn)
|
|
|
|
# Check: invalid ISBN
|
|
match = re.match(r'^.*?isbn.*$', column)
|
|
if match is not None:
|
|
df[column] = df[column].apply(check.isbn)
|
|
|
|
# Check: invalid date
|
|
match = re.match(r'^.*?date.*$', column)
|
|
if match is not None:
|
|
df[column] = df[column].apply(check.date)
|
|
|
|
# Write
|
|
df.to_csv(args.output_file, index=False)
|