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Gerber, Mike 4bb3379ab1 🐛 Use tqdm's write() instead of logging during scanning
2022-05-10 17:57:36 +02:00
.circleci ✔️ CircleCI: - Python 3.5 + Python 3.10 2022-03-31 21:10:13 +02:00
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qurator 🐛 Use tqdm's write() instead of logging during scanning 2022-05-10 17:57:36 +02:00
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LICENSE 📝 modstool: Add LICENSE 2019-10-11 13:41:33 +02:00
README.md 🚧 modstool: Replace Travis with CircleCI 2021-02-10 18:46:25 +01:00
requirements-test.txt 🚧 Add support for ALTO Description 2022-05-04 20:02:27 +02:00
requirements.txt 🐛 Fix install on Python 3.10 2022-04-07 15:17:19 +02:00
setup.py 🚧 Add support for ALTO Description 2022-05-04 20:02:27 +02:00

README.md

Extract the MODS metadata of a bunch of METS files into a pandas DataFrame.

Build Status

Column names are derived from the corresponding MODS elements. Some domain knowledge is used to convert elements to a useful column, e.g. produce sets instead of ordered lists for topics, etc. Parts of the tool are specific to our environment/needs at the State Library Berlin and may need to be changed for your library.

Usage

modstool /path/to/a/directory/containing/mets_files

Example

In this example we convert the MODS metadata contained in the METS files in /srv/data/digisam_mets-sample-300 to a pandas DataFrame under mods_info_df.pkl. This file can then be read by your data scientist using pd.read_pickle().

% modstool /srv/data/digisam_mets-sample-300
INFO:root:Scanning directory /srv/data/digisam_mets-sample-300
301it [00:00, 19579.19it/s]
INFO:root:Processing METS files
100%|████████████████████████████████████████| 301/301 [00:01<00:00, 162.59it/s]
INFO:root:Writing DataFrame to mods_info_df.pkl