1
0
mirror of https://github.com/ilri/csv-metadata-quality.git synced 2025-05-09 22:56:01 +02:00

21 Commits

Author SHA1 Message Date
c8f5539d21 Update requirements
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Generated with poetry export:

    $ poetry export --without-hashes -f requirements.txt > requirements.txt
    $ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt

I am trying `--without-hashes` to work around an error on pip install
when running in CI:

    ERROR: In --require-hashes mode, all requirements must have their versions pinned with ==.
2021-07-06 15:47:44 +03:00
382d0d6aed Run poetry update 2021-07-06 15:37:57 +03:00
b8f4be9ebb pyproject.toml: Update pytest-clarity and black
These seem to have much newer versions that didn't get updated in
this project due to the version pinning selector I was using with
poetry.

In the case of pytest-clarity the previous version was 0.3.1 and
the version selector was a caret (^), which will never update the
left-most (major) number. Now they seem to be on 1.x.x so it will
be OK in the future.

In the case of black, they use weird numbering so it's anyone's
guess how this will work! Luckily it's only used for linting and
formatting.
2021-07-06 15:30:41 +03:00
4e2eab68b0 Update requests-cache
Apparently we were stuck on an older version of requests-cache due
to the fact that we were using the caret, which will never update
the left-most (major) version. Upstream requests-cache is currently
version 0.6.4, and there seems to have been some changes to the API.
2021-07-06 15:24:39 +03:00
55165cb4ce Update requirements
All checks were successful
continuous-integration/drone/push Build is passing
Generated with poetry export:

    $ poetry export --without-hashes -f requirements.txt > requirements.txt
    $ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt

I am trying `--without-hashes` to work around an error on pip install
when running in CI:

    ERROR: In --require-hashes mode, all requirements must have their versions pinned with ==.
2021-06-14 12:52:47 +03:00
93d3eabfba poetry.lock: Run poetry update 2021-06-14 12:52:28 +03:00
a8fe623f4c csv_metadata_quality/check.py: Remove unnecessary pass
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LGTM warned that these pass statements are not necessary.

See: https://lgtm.com/rules/910088/
2021-04-20 08:20:13 +03:00
dbc0437d59 CHANGELOG.md: Add note about Python deps
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2021-04-14 16:16:02 +03:00
96ce1daa90 Update requirements
Generated with poetry export:

    $ poetry export --without-hashes -f requirements.txt > requirements.txt
    $ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt

I am trying `--without-hashes` to work around an error on pip install
when running in CI:

    ERROR: In --require-hashes mode, all requirements must have
their versions pinned with ==.
2021-04-14 16:15:28 +03:00
3adb52d7c0 poetry.lock: Run poetry update 2021-04-14 16:14:37 +03:00
f958d1879f poetry.lock: Run poetry update
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2021-04-02 16:19:16 +03:00
bd8943f36a csv_metadata_quality/app.py: Don't crash if fields are missing
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We don't need to crash if someone feeds us a CSV file that is miss-
ing commont DSpace fields like title, type, and subject.
2021-03-21 19:47:29 +02:00
28f9026286 README.md: Minor edit
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2021-03-19 16:26:31 +02:00
cfe09f7126 Add SPDX short license identifier to all Python files
See: https://spdx.github.io/spdx-spec/appendix-V-using-SPDX-short-identifiers-in-source-files/
2021-03-19 16:04:40 +02:00
8eddb76aab Bump version to 0.4.8-dev
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2021-03-19 11:53:56 +02:00
a04dbc50db Add notes about checking and fixing mojibake 2021-03-19 11:48:27 +02:00
28335ed159 Update requirements
Generated with poetry export:

    $ poetry export --without-hashes -f requirements.txt > requirements.txt
    $ poetry export --without-hashes --dev -f requirements.txt > requirements-dev.txt

I am trying `--without-hashes` to work around an error on pip install
when running in CI:

    ERROR: In --require-hashes mode, all requirements must have
their versions pinned with ==.
2021-03-19 10:29:15 +02:00
773a0a2695 poetry.lock: Run poetry update 2021-03-19 10:28:55 +02:00
39a4b1a487 Add mojibake to data/test.csv and tests 2021-03-19 10:28:33 +02:00
898bb412c3 Add checks and unsafe fixes for mojibake
This detects whether text has likely been encoded in one encoding
and decoded in another, perhaps multiple times. This often results
in display of "mojibake" characters.

For example, a file encoded in UTF-8 is opened as CP-1252 (Windows
Latin codepage) in Microsoft Excel, and saved again as UTF-8. You
will see strings like this in the resulting file:

    - CIAT Publicaçao
    - CIAT Publicación

The correct version of these in UTF-8 would be:

    - CIAT Publicaçao
    - CIAT Publicación

I use a code snippet from Martijn Pieters on StackOverflow to de-
tect whether a string is "weird" as determined by the excellent
"fixes text for you" (ftfy) Python library, then check if a weird
string encodes as CP-1252 or not. If so, I can try to fix it.

See: https://stackoverflow.com/questions/29071995/identify-garbage-unicode-string-using-python
2021-03-19 10:22:21 +02:00
e92ec5d371 README.md: Add note about duplicate checking
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2021-03-17 10:12:03 +02:00
17 changed files with 661 additions and 377 deletions

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@ -4,6 +4,13 @@ All notable changes to this project will be documented in this file.
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 check for, and fix, "mojibake" characters using [ftfy](https://github.com/LuminosoInsight/python-ftfy)
### Updated
- Python dependencies
## [0.4.7] - 2021-03-17
### Changed
- Fixing invalid multi-value separators like `|` and `|||` is no longer class-

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@ -20,7 +20,9 @@ If you use the DSpace CSV metadata quality checker please cite:
- Perform [Unicode normalization](https://withblue.ink/2019/03/11/why-you-need-to-normalize-unicode-strings.html) on strings using `--unsafe-fixes`
- Remove unnecessary Unicode like [non-breaking spaces](https://en.wikipedia.org/wiki/Non-breaking_space), [replacement characters](https://en.wikipedia.org/wiki/Specials_(Unicode_block)#Replacement_character), etc
- Check for "suspicious" characters that indicate encoding or copy/paste issues, for example "foreˆt" should be "forêt"
- Check for "mojibake" characters (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
## Installation
The easiest way to install CSV Metadata Quality is with [poetry](https://python-poetry.org):
@ -61,7 +63,7 @@ While it is *theoretically* possible for a single `|` character to be used legit
This will also remove unnecessary trailing multi-value separators, for example `Kenya||Tanzania||`.
## Unsafe Fixes
You can enable several "unsafe" fixes with the `--unsafe-fixes` option. Currently this will remove newlines and perform Unicode normalization.
You can enable several "unsafe" fixes with the `--unsafe-fixes` option. Currently this will remove newlines, perform Unicode normalization, and attempt to fix "mojibake" characters.
### Newlines
This is considered "unsafe" because some systems give special importance to vertical space and render it properly. DSpace does not support rendering newlines in its XMLUI and has, at times, suffered from parsing errors that cause the import process to fail if an input file had newlines. The `--unsafe-fixes` option strips Unix line feeds (U+000A).
@ -74,6 +76,14 @@ This is considered "unsafe" because some systems give special importance to vert
Read more about [Unicode normalization](https://withblue.ink/2019/03/11/why-you-need-to-normalize-unicode-strings.html).
### Encoding Issues aka "Mojibake"
[Mojibake](https://en.wikipedia.org/wiki/Mojibake) is a phenomenon that occurs when text is decoded using an unintended character encoding. This usually presents itself in the form of strange, garbled characters in the text. Enabling "unsafe" fixes will attempt to correct these, for example:
- CIAT PublicaçaoCIAT Publicaçao
- CIAT PublicaciónCIAT Publicación
Pay special attention to the output of the script as well as the resulting file to make sure no new issues have been introduced. The ideal way to solve these issues is to avoid it in the first place. See [this guide about opening CSVs in UTF-8 format in Excel](https://www.itg.ias.edu/content/how-import-csv-file-uses-utf-8-character-encoding-0).
## AGROVOC Validation
You can enable validation of metadata values in certain fields against the AGROVOC REST API with the `--agrovoc-fields` option. For example, in addition to agricultural subjects, many countries and regions are also present AGROVOC. Enable this validation by specifying a comma-separated list of fields:
@ -116,10 +126,6 @@ This currently uses the [Python langid](https://github.com/saffsd/langid.py) lib
- Warn if item is Open Access, but missing a license
- Warn if item has an ISSN but no journal title
- Update journal titles from ISSN
- Check for duplicates
- If I check titles only, then I might miss if one is a Report and another is a Presentation
- I could just check each item against each other item, but that sounds slow...
- Perhaps I could check for the number of unique values in a few rows, like title and doi, and see if it is the same as the total number of items
## License
This work is licensed under the [GPLv3](https://www.gnu.org/licenses/gpl-3.0.en.html).

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@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
from sys import argv
from csv_metadata_quality import app

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@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
import argparse
import re
import signal
@ -107,6 +109,13 @@ def run(argv):
# Check: suspicious characters
df[column].apply(check.suspicious_characters, field_name=column)
# Check: mojibake
df[column].apply(check.mojibake, field_name=column)
# Fix: mojibake
if args.unsafe_fixes:
df[column] = df[column].apply(fix.mojibake, field_name=column)
# Fix: invalid and unnecessary multi-value separators
df[column] = df[column].apply(fix.separators, field_name=column)
# Run whitespace fix again after fixing invalid separators
@ -155,13 +164,16 @@ def run(argv):
# Check: duplicate items
# We extract just the title, type, and date issued columns to analyze
duplicates_df = df.filter(
regex=r"dcterms\.title|dc\.title|dcterms\.type|dc\.type|dcterms\.issued|dc\.date\.issued"
)
check.duplicate_items(duplicates_df)
try:
duplicates_df = df.filter(
regex=r"dcterms\.title|dc\.title|dcterms\.type|dc\.type|dcterms\.issued|dc\.date\.issued"
)
check.duplicate_items(duplicates_df)
# Delete the temporary duplicates DataFrame
del duplicates_df
# Delete the temporary duplicates DataFrame
del duplicates_df
except IndexError:
pass
##
# Perform some checks on rows so we can consider items as a whole rather

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@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
import os
import re
from datetime import datetime, timedelta
@ -11,6 +13,8 @@ from pycountry import languages
from stdnum import isbn as stdnum_isbn
from stdnum import issn as stdnum_issn
from csv_metadata_quality.util import is_mojibake
def issn(field):
"""Check if an ISSN is valid.
@ -174,13 +178,9 @@ def language(field):
if len(value) == 2:
if not languages.get(alpha_2=value):
print(f"{Fore.RED}Invalid ISO 639-1 language: {Fore.RESET}{value}")
pass
elif len(value) == 3:
if not languages.get(alpha_3=value):
print(f"{Fore.RED}Invalid ISO 639-3 language: {Fore.RESET}{value}")
pass
else:
print(f"{Fore.RED}Invalid language: {Fore.RESET}{value}")
@ -216,7 +216,7 @@ def agrovoc(field, field_name):
)
# prune old cache entries
requests_cache.core.remove_expired_responses()
requests_cache.remove_expired_responses()
# Try to split multi-value field on "||" separator
for value in field.split("||"):
@ -301,8 +301,6 @@ def spdx_license_identifier(field):
if value not in spdx_license_list.LICENSES:
print(f"{Fore.YELLOW}Non-SPDX license identifier: {Fore.RESET}{value}")
pass
return
@ -345,3 +343,22 @@ def duplicate_items(df):
)
else:
items.append(item_title_type_date)
def mojibake(field, field_name):
"""Check for mojibake (text that was encoded in one encoding and decoded in
in another, perhaps multiple times). See util.py.
Prints the string if it contains suspected mojibake.
"""
# Skip fields with missing values
if pd.isna(field):
return
if is_mojibake(field):
print(
f"{Fore.YELLOW}Possible encoding issue ({field_name}): {Fore.RESET}{field}"
)
return

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@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
import re
import langid

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@ -1,10 +1,13 @@
# SPDX-License-Identifier: GPL-3.0-only
import re
from unicodedata import normalize
import pandas as pd
from colorama import Fore
from ftfy import fix_text
from csv_metadata_quality.util import is_nfc
from csv_metadata_quality.util import is_mojibake, is_nfc
def whitespace(field, field_name):
@ -253,3 +256,22 @@ def normalize_unicode(field, field_name):
field = normalize("NFC", field)
return field
def mojibake(field, field_name):
"""Attempts to fix mojibake (text that was encoded in one encoding and deco-
ded in another, perhaps multiple times). See util.py.
Return fixed string.
"""
# Skip fields with missing values
if pd.isna(field):
return field
if is_mojibake(field):
print(f"{Fore.GREEN}Fixing encoding issue ({field_name}): {Fore.RESET}{field}")
return fix_text(field)
else:
return field

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@ -1,3 +1,8 @@
# SPDX-License-Identifier: GPL-3.0-only
from ftfy.badness import sequence_weirdness
def is_nfc(field):
"""Utility function to check whether a string is using normalized Unicode.
Python's built-in unicodedata library has the is_normalized() function, but
@ -12,3 +17,35 @@ def is_nfc(field):
from unicodedata import normalize
return field == normalize("NFC", field)
def is_mojibake(field):
"""Determines whether a string contains mojibake.
We commonly deal with CSV files that were *encoded* in UTF-8, but decoded
as something else like CP-1252 (Windows Latin). This manifests in the form
of "mojibake", for example:
- CIAT Publicaçao
- CIAT Publicación
This uses the excellent "fixes text for you" (ftfy) library to determine
whether a string contains characters that have been encoded in one encoding
and decoded in another.
Inspired by this code snippet from Martijn Pieters on StackOverflow:
https://stackoverflow.com/questions/29071995/identify-garbage-unicode-string-using-python
Return boolean.
"""
if not sequence_weirdness(field):
# Nothing weird, should be okay
return False
try:
field.encode("sloppy-windows-1252")
except UnicodeEncodeError:
# Not CP-1252 encodable, probably fine
return False
else:
# Encodable as CP-1252, Mojibake alert level high
return True

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@ -1 +1,3 @@
VERSION = "0.4.7"
# SPDX-License-Identifier: GPL-3.0-only
VERSION = "0.4.8-dev"

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@ -32,3 +32,4 @@ Unnecessary multi-value separator,2021-01-03,0378-5955||,,,,,,,
Invalid SPDX license identifier,2021-03-11,,,,,,,CC-BY,
Duplicate Title,2021-03-17,,,,,,,,Report
Duplicate Title,2021-03-17,,,,,,,,Report
Mojibake,2021-03-18,,,,CIAT Publicaçao,,,,Report

1 dc.title dcterms.issued dc.identifier.issn dc.identifier.isbn dcterms.language dcterms.subject cg.coverage.country filename dcterms.license dcterms.type
32 Duplicate Title 2021-03-17 Report
33 Duplicate Title 2021-03-17 Report
34 Mojibake 2021-03-18 CIAT Publicaçao Report
35

734
poetry.lock generated

File diff suppressed because it is too large Load Diff

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@ -1,6 +1,6 @@
[tool.poetry]
name = "csv-metadata-quality"
version = "0.4.7"
version = "0.4.8-dev"
description="A simple, but opinionated CSV quality checking and fixing pipeline for CSVs in the DSpace ecosystem."
authors = ["Alan Orth <alan.orth@gmail.com>"]
license="GPL-3.0-only"
@ -16,18 +16,19 @@ pandas = "^1.0.4"
python-stdnum = "^1.13"
xlrd = "^1.2.0"
requests = "^2.23.0"
requests-cache = "^0.5.2"
requests-cache = "~0.6.4"
pycountry = "^19.8.18"
langid = "^1.1.6"
colorama = "^0.4.4"
spdx-license-list = "^0.5.2"
ftfy = "^5.9"
[tool.poetry.dev-dependencies]
pytest = "^6.1.1"
ipython = { version = "^7.18.1", python = "^3.7" }
flake8 = "^3.8.4"
pytest-clarity = "^0.3.0-alpha.0"
black = "20.8b1"
pytest-clarity = "^1.0.1"
black = "^21.6b0"
isort = "^5.5.4"
csvkit = "^1.0.5"

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@ -2,74 +2,80 @@ agate-dbf==0.2.2
agate-excel==0.2.3
agate-sql==0.5.6
agate==1.6.2
appdirs==1.4.4; python_version >= "3.6"
appdirs==1.4.4; python_full_version >= "3.6.2"
appnope==0.1.2; python_version >= "3.7" and python_version < "4.0" and sys_platform == "darwin"
atomicwrites==1.4.0; python_version >= "3.6" and python_full_version < "3.0.0" and sys_platform == "win32" and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6") or sys_platform == "win32" and python_version >= "3.6" and python_full_version >= "3.4.0" and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6")
attrs==20.3.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
babel==2.9.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
attrs==21.2.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
babel==2.9.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
backcall==0.2.0; python_version >= "3.7" and python_version < "4.0"
black==20.8b1; python_version >= "3.6"
certifi==2020.12.5; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
chardet==4.0.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
click==7.1.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
black==21.6b0; python_full_version >= "3.6.2"
certifi==2021.5.30; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
chardet==4.0.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
click==8.0.1; python_version >= "3.6" and python_full_version >= "3.6.2"
colorama==0.4.4; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
commonmark==0.9.1; python_version >= "3.6" and python_version < "4.0" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0")
csvkit==1.0.5
dbfread==2.0.7
decorator==4.4.2; python_version >= "3.7" and python_full_version < "3.0.0" and python_version < "4.0" or python_version >= "3.7" and python_version < "4.0" and python_full_version >= "3.2.0"
et-xmlfile==1.0.1; python_version >= "3.6"
flake8==3.9.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
greenlet==1.0.0; python_version >= "3" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3"
idna==2.10; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
importlib-metadata==3.7.3; python_version < "3.8" and python_version >= "3.6" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.5.0" and python_version < "3.8" and python_version >= "3.6") and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.4.0" and python_version >= "3.6" and python_version < "3.8") and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6") and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.6.0" and python_version < "3.8" and python_version >= "3.6")
decorator==5.0.9; python_version >= "3.7" and python_version < "4.0"
et-xmlfile==1.1.0; python_version >= "3.6"
flake8==3.9.2; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
ftfy==5.9; python_version >= "3.5"
greenlet==1.1.0; python_version >= "3" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3"
idna==2.10; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
importlib-metadata==4.6.1; python_version < "3.8" and python_version >= "3.6" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.5.0" and python_version < "3.8" and python_version >= "3.6") and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.4.0" and python_version >= "3.6" and python_version < "3.8") and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6") and python_full_version >= "3.6.2" and (python_version >= "3.6" and python_full_version < "3.0.0" and python_version < "3.8" or python_full_version >= "3.6.0" and python_version < "3.8" and python_version >= "3.6")
iniconfig==1.1.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
ipython-genutils==0.2.0; python_version >= "3.7" and python_version < "4.0"
ipython==7.21.0; python_version >= "3.7" and python_version < "4.0"
ipython==7.25.0; python_version >= "3.7" and python_version < "4.0"
isodate==0.6.0
isort==5.7.0; python_version >= "3.6" and python_version < "4.0"
isort==5.9.1; python_full_version >= "3.6.1" and python_version < "4.0"
itsdangerous==2.0.1; python_version >= "3.6"
jedi==0.18.0; python_version >= "3.7" and python_version < "4.0"
langid==1.1.6
leather==0.3.3
matplotlib-inline==0.1.2; python_version >= "3.7" and python_version < "4.0"
mccabe==0.6.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
mypy-extensions==0.4.3; python_version >= "3.6"
numpy==1.20.1; python_version >= "3.7" and python_full_version >= "3.7.1"
mypy-extensions==0.4.3; python_full_version >= "3.6.2"
numpy==1.21.0; python_version >= "3.7" and python_full_version >= "3.7.1"
openpyxl==3.0.7; python_version >= "3.6"
packaging==20.9; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
pandas==1.2.3; python_full_version >= "3.7.1"
packaging==21.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
pandas==1.3.0; python_full_version >= "3.7.1"
parsedatetime==2.6
parso==0.8.1; python_version >= "3.7" and python_version < "4.0"
pathspec==0.8.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
parso==0.8.2; python_version >= "3.7" and python_version < "4.0"
pathspec==0.8.1; python_full_version >= "3.6.2"
pexpect==4.8.0; python_version >= "3.7" and python_version < "4.0" and sys_platform != "win32"
pickleshare==0.7.5; python_version >= "3.7" and python_version < "4.0"
pluggy==0.13.1; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
prompt-toolkit==3.0.17; python_version >= "3.7" and python_version < "4.0" and python_full_version >= "3.6.1"
pprintpp==0.4.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
prompt-toolkit==3.0.19; python_version >= "3.7" and python_version < "4.0" and python_full_version >= "3.6.1"
ptyprocess==0.7.0; python_version >= "3.7" and python_version < "4.0" and sys_platform != "win32"
py==1.10.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
pycodestyle==2.7.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
pycountry==19.8.18
pyflakes==2.3.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
pygments==2.8.1; python_version >= "3.7" and python_version < "4.0"
pyicu==2.6
pyparsing==2.4.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
pytest-clarity==0.3.0a0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.4.0")
pytest==6.2.2; python_version >= "3.6"
pyflakes==2.3.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
pygments==2.9.0; python_version >= "3.7" and python_version < "4.0" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0")
pyicu==2.7.4
pyparsing==2.4.7; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
pytest-clarity==1.0.1; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.4.0")
pytest==6.2.4; python_version >= "3.6"
python-dateutil==2.8.1; python_full_version >= "3.7.1"
python-slugify==4.0.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
python-slugify==5.0.2; python_version >= "3.6"
python-stdnum==1.16
pytimeparse==1.1.8
pytz==2021.1; python_full_version >= "3.7.1"
regex==2020.11.13; python_version >= "3.6"
requests-cache==0.5.2
regex==2021.7.6; python_full_version >= "3.6.2"
requests-cache==0.6.4; python_version >= "3.6"
requests==2.25.1; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
six==1.15.0; python_full_version >= "3.7.1"
rich==10.5.0; python_version >= "3.6" and python_version < "4.0" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0")
six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.3.0")
spdx-license-list==0.5.2
sqlalchemy==1.4.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
termcolor==1.1.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
text-unidecode==1.3; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
toml==0.10.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6"
sqlalchemy==1.4.20; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
text-unidecode==1.3; python_version >= "3.6"
toml==0.10.2; python_full_version >= "3.6.2" and python_version >= "3.6" and (python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.6")
traitlets==5.0.5; python_version >= "3.7" and python_version < "4.0"
typed-ast==1.4.2; python_version >= "3.6"
typing-extensions==3.7.4.3; python_version < "3.8" and python_version >= "3.6"
urllib3==1.26.4; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version < "4"
typed-ast==1.4.3; python_version < "3.8" and python_full_version >= "3.6.2"
typing-extensions==3.10.0.0; python_version < "3.8" and python_full_version >= "3.6.2" and python_version >= "3.6" and (python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0")
url-normalize==1.4.3; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
urllib3==1.26.6; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version < "4" and python_version >= "3.6"
wcwidth==0.2.5; python_version >= "3.7" and python_version < "4.0" and python_full_version >= "3.6.1"
xlrd==1.2.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.4.0")
zipp==3.4.1; python_version < "3.8" and python_version >= "3.6"
zipp==3.5.0; python_version < "3.8" and python_version >= "3.6"

View File

@ -1,17 +1,21 @@
certifi==2020.12.5; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
chardet==4.0.0; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
certifi==2021.5.30; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
chardet==4.0.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
colorama==0.4.4; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
idna==2.10; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0"
ftfy==5.9; python_version >= "3.5"
idna==2.10; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.6"
itsdangerous==2.0.1; python_version >= "3.6"
langid==1.1.6
numpy==1.20.1; python_version >= "3.7" and python_full_version >= "3.7.1"
pandas==1.2.3; python_full_version >= "3.7.1"
numpy==1.21.0; python_version >= "3.7" and python_full_version >= "3.7.1"
pandas==1.3.0; python_full_version >= "3.7.1"
pycountry==19.8.18
python-dateutil==2.8.1; python_full_version >= "3.7.1"
python-stdnum==1.16
pytz==2021.1; python_full_version >= "3.7.1"
requests-cache==0.5.2
requests-cache==0.6.4; python_version >= "3.6"
requests==2.25.1; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.5.0")
six==1.15.0; python_full_version >= "3.7.1"
six==1.16.0; python_full_version >= "3.7.1" and python_version >= "3.6"
spdx-license-list==0.5.2
urllib3==1.26.4; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version < "4"
url-normalize==1.4.3; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
urllib3==1.26.6; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version < "4" and python_version >= "3.6"
wcwidth==0.2.5; python_version >= "3.5"
xlrd==1.2.0; (python_version >= "2.7" and python_full_version < "3.0.0") or (python_full_version >= "3.4.0")

View File

@ -14,7 +14,7 @@ install_requires = [
setuptools.setup(
name="csv-metadata-quality",
version="0.4.7",
version="0.4.8-dev",
author="Alan Orth",
author_email="aorth@mjanja.ch",
description="A simple, but opinionated CSV quality checking and fixing pipeline for CSVs in the DSpace ecosystem.",

View File

@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
import pandas as pd
from colorama import Fore
@ -339,3 +341,29 @@ def test_check_duplicate_item(capsys):
captured.out
== f"{Fore.YELLOW}Possible duplicate (dc.title): {Fore.RESET}{item_title}\n"
)
def test_check_no_mojibake():
"""Test string with no mojibake."""
field = "CIAT Publicaçao"
field_name = "dcterms.isPartOf"
result = check.mojibake(field, field_name)
assert result == None
def test_check_mojibake(capsys):
"""Test string with mojibake."""
field = "CIAT Publicaçao"
field_name = "dcterms.isPartOf"
result = check.mojibake(field, field_name)
captured = capsys.readouterr()
assert (
captured.out
== f"{Fore.YELLOW}Possible encoding issue ({field_name}): {Fore.RESET}{field}\n"
)

View File

@ -1,3 +1,5 @@
# SPDX-License-Identifier: GPL-3.0-only
import csv_metadata_quality.fix as fix
@ -108,3 +110,12 @@ def test_fix_decomposed_unicode():
field_name = "dc.contributor.author"
assert fix.normalize_unicode(value, field_name) == "Ouédraogo, Mathieu"
def test_fix_mojibake():
"""Test string with no mojibake."""
field = "CIAT Publicaçao"
field_name = "dcterms.isPartOf"
assert fix.mojibake(field, field_name) == "CIAT Publicaçao"