OAPapersLoader
This repository contains python loaders for OAPapers corpus and derived datasets. It accompanies the repository https://github.com/KNOT-FIT-BUT/OAPapers and provides more lightweight solution without exhaustive dependencies to load the OAPapers corpus and derived datasets.
Install
pip install oapaersloader
Usage
An example of loading OARelatedWork dataset with references:
from oapapersloader.datasets import OARelatedWork, OADataset
with OARelatedWork("train.jsonl", "train.jsonl.index") as dataset, \
OADataset("references.jsonl", "references.jsonl.index") as references:
d = dataset[0]
print("Document:", dataset[0].title)
print("Cited paper:", references.get_by_id(d.citations[0]).title)
The OARelatedWork will load the target papers with related work sections and the OADataset will load dataset of all references that can be used for loading cited papers.
1 maintainer
Metadata
1 maintainer
Release files for oapapersloader 1.0.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| oapapersloader-1.0.1.tar.gz | 18.4 kB | Without provenance | Details for oapapersloader-1.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| oapapersloader-1.0.1-py3-none-any.whl | Python 3 | none | any | Details for oapapersloader-1.0.1-py3-none-any.whl |
Total release size: 34.3 kB
Release files / oapapersloader-1.0.1.tar.gz
| Download URL | oapapersloader-1.0.1.tar.gz |
|---|---|
| Size | 18.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / oapapersloader-1.0.1-py3-none-any.whl
| Download URL | oapapersloader-1.0.1-py3-none-any.whl |
|---|---|
| Size | 16.0 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
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twine/5.0.0 CPython/3.10.14
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