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Author SHA1 Message Date
renovate[bot]
3329ce2535
Merge 56de42b090 into 2341c56c40 2024-06-30 18:05:29 +00:00
2341c56c40
poetry.lock: run poetry update 2024-04-25 12:50:30 +03:00
5be2195325
Add fix for normalizing DOIs 2024-04-25 12:49:19 +03:00
736948ed2c
csv_metadata_quality/check.py: run rye fmt 2024-04-12 13:40:55 +03:00
ee0b448355
csv_metadata_quality/check.py: remove unused import 2024-04-12 11:07:36 +03:00
renovate[bot]
56de42b090
chore(deps): update dependency pytest to v8
All checks were successful
continuous-integration/drone/push Build is passing
2024-01-27 22:53:41 +00:00
9 changed files with 548 additions and 471 deletions

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@ -5,6 +5,9 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## Unreleased
### Added
- Ability to normalize DOIs to https://doi.org URI format
### Fixed
- Fixed regex so we don't run the invalid multi-value separator fix on
`dcterms.bibliographicCitation` fields

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@ -31,6 +31,7 @@ If you use the DSpace CSV metadata quality checker please cite:
- Check for countries with missing regions (and attempt to fix with `--unsafe-fixes`)
- Remove duplicate metadata values
- Check for duplicate items, using the title, type, and date issued as an indicator
- [Normalize DOIs](https://www.crossref.org/documentation/member-setup/constructing-your-dois/) to https://doi.org URI format
## Installation
The easiest way to install CSV Metadata Quality is with [poetry](https://python-poetry.org):
@ -125,7 +126,6 @@ This currently uses the [Python langid](https://github.com/saffsd/langid.py) lib
- Better logging, for example with INFO, WARN, and ERR levels
- Verbose, debug, or quiet options
- Warn if an author is shorter than 3 characters?
- Validate DOIs? Normalize to https://doi.org format? Or use just the DOI part: 10.1016/j.worlddev.2010.06.006
- Warn if two items use the same file in `filename` column
- Add tests for application invocation, ie `tests/test_app.py`?
- Validate ISSNs or journal titles against CrossRef API?

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@ -141,6 +141,11 @@ def run(argv):
# Fix: unnecessary Unicode
df[column] = df[column].apply(fix.unnecessary_unicode)
# Fix: normalize DOIs
match = re.match(r"^.*?identifier\.doi.*$", column)
if match is not None:
df[column] = df[column].apply(fix.normalize_dois)
# Fix: invalid and unnecessary multi-value separators. Skip the title
# and abstract fields because "|" is used to indicate something like
# a subtitle.

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@ -2,7 +2,7 @@
import logging
import re
from datetime import datetime, timedelta
from datetime import datetime
import country_converter as coco
import pandas as pd
@ -133,7 +133,7 @@ def suspicious_characters(field, field_name):
return
# List of suspicious characters, for example: ́ˆ~`
suspicious_characters = ["\u00B4", "\u02C6", "\u007E", "\u0060"]
suspicious_characters = ["\u00b4", "\u02c6", "\u007e", "\u0060"]
for character in suspicious_characters:
# Find the position of the suspicious character in the string

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@ -395,3 +395,74 @@ def countries_match_regions(row, exclude):
row[region_column_name] = "||".join(missing_regions)
return row
def normalize_dois(field):
"""Normalize DOIs.
DOIs are meant to be globally unique identifiers. They are case insensitive,
but in order to compare them robustly they should be normalized to a common
format:
- strip leading and trailing whitespace
- lowercase all ASCII characters
- convert all variations to https://doi.org/10.xxxx/xxxx URI format
Return string with normalized DOI.
See: https://www.crossref.org/documentation/member-setup/constructing-your-dois/
"""
# Skip fields with missing values
if pd.isna(field):
return
# Try to split multi-value field on "||" separator
values = field.split("||")
# Initialize an empty list to hold the de-duplicated values
new_values = []
# Iterate over all values (most items will only have one DOI)
for value in values:
# Strip leading and trailing whitespace
new_value = value.strip()
new_value = new_value.lower()
# Convert to HTTPS
pattern = re.compile(r"^http://")
match = re.findall(pattern, new_value)
if match:
new_value = re.sub(pattern, "https://", new_value)
# Convert dx.doi.org to doi.org
pattern = re.compile(r"dx\.doi\.org")
match = re.findall(pattern, new_value)
if match:
new_value = re.sub(pattern, "doi.org", new_value)
# Replace values like doi: 10.11648/j.jps.20140201.14
pattern = re.compile(r"^doi: 10\.")
match = re.findall(pattern, new_value)
if match:
new_value = re.sub(pattern, "https://doi.org/10.", new_value)
# Replace values like 10.3390/foods12010115
pattern = re.compile(r"^10\.")
match = re.findall(pattern, new_value)
if match:
new_value = re.sub(pattern, "https://doi.org/10.", new_value)
if new_value != value:
print(f"{Fore.GREEN}Normalized DOI: {Fore.RESET}{value}")
new_values.append(new_value)
new_field = "||".join(new_values)
return new_field

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@ -37,3 +37,6 @@ Mojibake,2021-03-18,,,,Publicaçao CIAT,,,,Report,,,,
Title missing from citation,2021-12-05,,,,,,,,,"Orth, A. 2021. Title missing f rom citation.",,,
Country missing region,2021-12-08,,,,,Kenya,,,,,,,
Subregion field shouldnt trigger region checks,2022-12-07,,,,,Kenya,,,,,,Eastern Africa,Baringo
DOI with HTTP and dx.doi.org,2024-04-23,,,,,,,,,,http://dx.doi.org/10.1016/j.envc.2023.100794,,
DOI with colon,2024-04-23,,,,,,,,,,doi: 10.11648/j.jps.20140201.14,,
Upper case bare DOI,2024-04-23,,,,,,,,,,10.19103/AS.2018.0043.16,,

1 dc.title dcterms.issued dc.identifier.issn dc.identifier.isbn dcterms.language dcterms.subject cg.coverage.country filename dcterms.license dcterms.type dcterms.bibliographicCitation cg.identifier.doi cg.coverage.region cg.coverage.subregion
37 Country missing region 2021-12-08 Kenya
38 Subregion field shouldn’t trigger region checks 2022-12-07 Kenya Eastern Africa Baringo
39 DOI with HTTP and dx.doi.org 2024-04-23 http://dx.doi.org/10.1016/j.envc.2023.100794
40 DOI with colon 2024-04-23 doi: 10.11648/j.jps.20140201.14
41 Upper case bare DOI 2024-04-23 10.19103/AS.2018.0043.16
42

921
poetry.lock generated

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@ -23,7 +23,7 @@ pycountry = "^23.12.7"
py3langid = "^0.2.2"
[tool.poetry.group.dev.dependencies]
pytest = "^7.2.1"
pytest = "^8.0.0"
flake8 = "^7.0.0"
pytest-clarity = "^1.0.1"
black = "^23.1.0"

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@ -152,3 +152,11 @@ def test_fix_country_not_matching_region():
series_correct = pd.Series(data=d_correct)
pd.testing.assert_series_equal(result, series_correct)
def test_fix_normalize_dois():
"""Test normalizing a DOI."""
value = "doi: 10.11648/j.jps.20140201.14"
assert fix.normalize_dois(value) == "https://doi.org/10.11648/j.jps.20140201.14"