eth_py150_open / README.md
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---
annotations_creators:
- no-annotations
language_creators:
- machine-generated
languages:
- en
licenses:
- apache-2-0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids:
- other-other-contextual-embeddings
---
# Dataset Card for ethpy150open
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://www.sri.inf.ethz.ch/py150
- **Repository:** https://github.com/google-research-datasets/eth_py150_open
- **Paper:** https://proceedings.icml.cc/static/paper_files/icml/2020/5401-Paper.pdf
- **Leaderboard:** None
- **Point of Contact:** Aditya Kanade <kanade@iisc.ac.in>, Petros Maniatis <maniatis@google.com>
### Dataset Summary
A redistributable subset of the [ETH Py150 corpus](https://www.sri.inf.ethz.ch/py150), introduced in the ICML 2020 paper ['Learning and Evaluating Contextual Embedding of Source Code'](https://proceedings.icml.cc/static/paper_files/icml/2020/5401-Paper.pdf)
### 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}
}