Dataset:

Task Categories: other
Languages: en
Multilinguality: monolingual
Size Categories: 100K<n<1M
Licenses: apache-2.0
Language Creators: machine-generated
Annotations Creators: no-annotations
Source Datasets: original

Dataset Card for ethpy150open

Dataset Summary

A redistributable subset of the ETH Py150 corpus, introduced in the ICML 2020 paper 'Learning and Evaluating Contextual Embedding of Source Code'

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English

Dataset Structure

List of dicts of { "filepath": The relative URL containing the path to the file on GitHub "license": The license used for that specific file or repository }

Data Instances

{ "filepath": "0rpc/zerorpc-python/setup.py", "license": "mit" }, { "filepath": "0rpc/zerorpc-python/zerorpc/heartbeat.py", "license": "mit" },

Data Fields

  • filepath: The relative URL containing the path to the file on GitHub
  • license: The license used for that specific file or repository

Data Splits

Train Valid Test
Dataset Split 74749 8302 41457

Dataset Creation

The original dataset is at https://www.sri.inf.ethz.ch/py150

Curation Rationale

To generate a more redistributable version of the dataset

Source Data

Initial Data Collection and Normalization

All the urls are filepaths relative to GitHub and the master branch was used as available at the time

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Apache License 2.0

Citation Information

@inproceedings{kanade2020learning, title={Learning and Evaluating Contextual Embedding of Source Code}, author={Kanade, Aditya and Maniatis, Petros and Balakrishnan, Gogul and Shi, Kensen}, booktitle={International Conference on Machine Learning}, pages={5110--5121}, year={2020}, organization={PMLR} }

Contributions

Thanks to @Bharat123rox for adding this dataset.

Update on GitHub
Explore dataset Edit dataset tags

Models trained or fine-tuned on eth_py150_open

None yet