Constructs a mapping list between research themes ("portals") and EDS/LDAP organization code to work with our Figshare patron management software (ReQUIAM). This code will generate a CSV file that is used for automation. The code imports a Google Sheet that is maintained by the Data Repository Team. The advantages of using Google Sheets are:
- Easy of use (no need to format CSV)
- Advanced spreadsheet capabilities with
MATCH(), and permitting/prohibiting cells for modification - Documentation capabilities via comments and version history management
- Ability to grant access to University of Arizona Libraries staff for coordinated maintenance
With the above Google Sheet that is imported as a CSV file using pandas, it
generates a CSV file called data/research_themes.csv.
There are two versions of this file:
- Trusted version,
master: [raw] [rendered] - Under developement,
develop: [raw] [rendered]
The workflow describes how version control will be conducted with
these two different branches. In general, after a maintainer implements a
change to the Google Sheet, s/he will perform an update to the develop
branch. Once that has been reviewed, a pull request will be done to merge the
changes into the master branch.
These instructions will have the code running on your local or virtual machine.
You will need the following to have a working copy of this software. See installation steps:
First, install a working version of Python (>=3.7.9). We recommend using the Anaconda package installer.
After you have Anaconda installed, you will want to create a separate conda environment
and activate it:
$ (sudo) conda create -n rsh_themes python=3.7
$ conda activate rsh_themes
Next, clone this repository into a parent folder:
(rsh_themes) $ cd /path/to/parent/folder
(rsh_themes) $ git clone https://github.com/ualibraries/ReQUIAM_csv.git
With the activated conda environment, you can install with the setup.py script:
(rsh_themes) $ cd /path/to/parent/folder/ReQUIAM_csv
(rsh_themes) $ (sudo) python setup.py develop
This will automatically installed the required numpy and pandas packages.
You can confirm installation via conda list
(rsh_themes) $ conda list requiam_csv
You should see that the version is 0.12.0.
Configuration settings are specified through the default.ini
file. These settings include the Google Sheet information and CSV file names
(do not change as this will break ReQUIAM).
To test the installation and create a temporary CSV file that does not affect
the main CSV file, the following command will run and generate a file called
dry_run.csv:
(rsh_themes) $ python requiam_csv/script_run
By default, the script does a "dry run." To execute the script and override
the main CSV file (data/research_themes.csv), include the execute argument
(rsh_themes) $ python requiam_csv/script_run --execute
The recommended workflow to commit changes on the main CSV file is as follows:
- First, switch to
developbranch:git checkout develop - Conduct a dry run execution
- Compare the two CSV files: 'data/research_themes.csv' and 'data/dry_run.csv'
- If the changes are what you expect, conduct the full execution
- Update the version number in README.md,
__init__.py, and setup.py - Perform a
git addandgit commitfor 'data/research_themes.csv' and the above files todevelop - Create a pull request here
- Update your local git repository with
git pull --all
We use SemVer for versioning. For the versions available, see the tags on this repository.
- Chun Ly, Ph.D. (@astrochun) - University of Arizona Libraries, Research Engagement
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE file for details.