From df670e81b9c01138711dbfef1734eed681377e43 Mon Sep 17 00:00:00 2001 From: Alan Orth Date: Tue, 26 Jan 2021 14:38:50 +0200 Subject: [PATCH] README.md: Use badge from my Drone CI I'm not using SourceHut anymore. --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 59b69c9..f763f71 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# CSV Metadata Quality ![GitHub Actions](https://github.com/ilri/csv-metadata-quality/workflows/Build%20and%20Test/badge.svg) [![builds.sr.ht status](https://builds.sr.ht/~alanorth/csv-metadata-quality.svg)](https://builds.sr.ht/~alanorth/csv-metadata-quality?) +# CSV Metadata Quality ![GitHub Actions](https://github.com/ilri/csv-metadata-quality/workflows/Build%20and%20Test/badge.svg) [![Build Status](https://ci.mjanja.ch/api/badges/alanorth/csv-metadata-quality/status.svg)](https://ci.mjanja.ch/alanorth/csv-metadata-quality) A simple, but opinionated metadata quality checker and fixer designed to work with CSVs in the DSpace ecosystem (though it could theoretically work on any CSV that uses Dublin Core fields as columns). The implementation is essentially a pipeline of checks and fixes that begins with splitting multi-value fields on the standard DSpace "||" separator, trimming leading/trailing whitespace, and then proceeding to more specialized cases like ISSNs, ISBNs, languages, etc. Requires Python 3.7 or greater (3.8 recommended). CSV and Excel support comes from the [Pandas](https://pandas.pydata.org/) library, though your mileage may vary with Excel because this is much less tested.