# CSV Metadata Quality [![Build Status](https://travis-ci.org/alanorth/csv-metadata-quality.svg?branch=master)](https://travis-ci.org/alanorth/csv-metadata-quality) [![builds.sr.ht status](https://builds.sr.ht/~alanorth/csv-metadata-quality.svg)](https://builds.sr.ht/~alanorth/csv-metadata-quality?) A simple but opinionated metadata quality checker and fixer designed to work with CSVs in the DSpace ecosystem. Supports multi-value fields using the standard DSpace value separator ("||"). Despite the name it does support reading Excel files. Requires Python 3.6 or greater. CSV and Excel support comes from the [Pandas](https://pandas.pydata.org/) library. ## Functionality - Read/write CSV files ✓ - Read Excel files ✓ - Validate dates, ISSNs, ISBNs, and multi-value separators ("||") ✓ - Fix leading, trailing, and excessive whitespace ✓ - Fix invalid multi-value separators ("|") 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 could indicate encoding or copy/paste issues, for example "foreˆt" should be "forêt" ✓ ## Installation The easiest way to install CSV Metadata Quality is with [pipenv](https://github.com/pypa/pipenv): ``` $ git clone https://git.sr.ht/~alanorth/csv-metadata-quality $ cd csv-metadata-quality $ pipenv install $ pipenv shell ``` Otherwise, if you don't have pipenv, you can use a vanilla Python virtual environment: ``` $ git clone https://git.sr.ht/~alanorth/csv-metadata-quality $ cd csv-metadata-quality $ python3 -m venv venv $ source venv/bin/activate $ pip install -r requirements.txt ``` ## Usage Run CSV Metadata Quality with the `--help` flag to see available options: ``` $ python -m csv_metadata_quality --help ``` To validate and clean a CSV file you must specify input and output files using the `-i` and `-o` options. For example, using the included test file: ``` $ python -m csv_metadata_quality -i data/test.csv -o /tmp/test.csv ``` You can enable "unsafe fixes" with the `--unsafe-fixes` option. This will attempt to fix things like invalid multi-value separators ("|"). It's possible that a metadata value could legitimately use "|" but in my experience this is rather always an error where the user meant to enter multiple values for a field, for example `Kenya||Tanzania`. ## Todo - Reporting / summary - Real logging - Detect and fix duplicate values like "Alan||Alan" ## License This work is licensed under the [GPLv3](https://www.gnu.org/licenses/gpl-3.0.en.html). The license allows you to use and modify the work for personal and commercial purposes, but if you distribute the work you must provide users with a means to access the source code for the version you are distributing. Read more about the [GPLv3 at TL;DR Legal](https://tldrlegal.com/license/gnu-general-public-license-v3-(gpl-3)).