From 6cc1401f88dc002f5a23aae064d5121fccb7d556 Mon Sep 17 00:00:00 2001 From: Alan Orth Date: Thu, 11 Mar 2021 13:41:58 +0200 Subject: [PATCH] pyproject.toml: Minimum Python is technically 3.7.1 See: https://pandas.pydata.org/pandas-docs/stable/whatsnew/v1.2.0.html --- README.md | 2 +- pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8d31b9b..900bfa8 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # DSpace CSV Metadata Quality Checker ![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, unnecessary Unicode, AGROVOC terms, 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. +Requires Python 3.7.1 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. If you use the DSpace CSV metadata quality checker please cite: diff --git a/pyproject.toml b/pyproject.toml index 092ebf0..238f868 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,7 @@ homepage = "https://github.com/ilri/csv-metadata-quality" csv-metadata-quality = 'csv_metadata_quality.__main__:main' [tool.poetry.dependencies] -python = "^3.8" +python = "^3.7.1" pandas = "^1.0.4" python-stdnum = "^1.13" xlrd = "^1.2.0"