qurator-spk
/
modstool
mirror of https://github.com/qurator-spk/modstool.git
1
0
Fork 0
Code Issues Releases Wiki Activity
You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
72 Commits
2 Branches
0 Tags
923 KiB
Python 100%
 
fix/use-temp-sqlite3
master
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '5c2dfa8505'
${ noResults }
Go to file
Mike Gerber 5c2dfa8505 ✔ Add another (large) METS example 1 year ago
.circleci ✔️ CircleCI: - Python 3.5 + Python 3.10 3 years ago
.vscode ⚙️ Add VSCode settings 3 years ago
qurator ✔ Add another (large) METS example 1 year ago
.editorconfig ⚙️ Add .editorconfig 3 years ago
.gitignore 🧹 .gitignore pyenv's .python-version 1 year ago
LICENSE 📝 modstool: Add LICENSE 5 years ago
README.md 🎨 Fix link to CircleCI project 3 years ago
requirements-test.txt 🚧 Add support for ALTO Description 3 years ago
requirements.txt 🐛 Fix install on Python 3.10 3 years ago
setup.py 🎨 Rename the Python package to mods4pandas 3 years ago

README.md

Extract the MODS/ALTO metadata of a bunch of METS/ALTO files into pandas DataFrames.

Build Status

mods4pandas converts the MODS metadata from METS files into a pandas DataFrame.

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.

alto4pandas converts the metadata from ALTO files into a pandas DataFrame.

Column names are derived from the corresponding ALTO elements. Some columns contain descriptive statistics (e.g. counts or mean) of the corresponding ALTO elements or attributes.

Usage

mods4pandas /path/to/a/directory/containing/mets_files

alto4pandas /path/to/a/directory/full/of/alto_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().

% mods4pandas /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

In the next example we convert the metadata from the ALTO files in the test data directory:

% alto4pandas qurator/mods4pandas/tests/data/alto
Scanning directory qurator/mods4pandas/tests/data/alto
Scanning directory qurator/mods4pandas/tests/data/alto/PPN636777308
Scanning directory qurator/mods4pandas/tests/data/alto/734008031
Scanning directory qurator/mods4pandas/tests/data/alto/PPN895016346
Scanning directory qurator/mods4pandas/tests/data/alto/PPN640992293
Scanning directory qurator/mods4pandas/tests/data/alto/alto-ner
Scanning directory qurator/mods4pandas/tests/data/alto/PPN767883624
Scanning directory qurator/mods4pandas/tests/data/alto/PPN715049151
Scanning directory qurator/mods4pandas/tests/data/alto/749782137
Scanning directory qurator/mods4pandas/tests/data/alto/weird-ns
INFO:alto4pandas:Processing ALTO files
INFO:alto4pandas:Writing DataFrame to alto_info_df.pkl