
# Dataset Card for ethpy150open

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [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)
  - [Contributions](#contributions)

## 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}
}

### Contributions

Thanks to [@Bharat123rox](https://github.com/Bharat123rox) for adding this dataset.
task_categories:other annotations_creators:no-annotation language_creators:machine-generated multilinguality:monolingual size_categories:100K<n<1M source_datasets:original language:en license:apache-2.0 contextual-embeddings region:us
{"annotations_creators": ["no-annotation"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "paperswithcode_id": "eth-py150-open", "pretty_name": "ethpy150open", "tags": ["contextual-embeddings"], "dataset_info": {"features": [{"name": "filepath", "dtype": "string"}, {"name": "license", "dtype": "string"}], "config_name": "eth_py150_open", "splits": [{"name": "train", "num_bytes": 5414978, "num_examples": 74749}, {"name": "test", "num_bytes": 3006199, "num_examples": 41457}, {"name": "validation", "num_bytes": 598524, "num_examples": 8302}], "download_size": 13875671, "dataset_size": 9019701}}
TAGS
#task_categories-other #annotations_creators-no-annotation #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-apache-2.0 #contextual-embeddings #region-us 

Dataset Card for ethpy150open
=============================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository: URL
* Paper: URL
* Leaderboard: None
* Point of Contact: Aditya Kanade [kanade@URL](mailto:kanade@URL), Petros Maniatis [maniatis@URL](mailto:maniatis@URL)


### 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


### 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/URL",
"license": "mit"
},
{
"filepath": "0rpc/zerorpc-python/zerorpc/URL",
"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



Dataset Creation
----------------


The original dataset is at URL


### 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?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


Apache License 2.0


@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.



### 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 ### 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/URL",
"license": "mit"
},
{
"filepath": "0rpc/zerorpc-python/zerorpc/URL",
"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



Dataset Creation
----------------


The original dataset is at URL ### 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? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


Apache License 2.0


@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.
TAGS
#task_categories-other #annotations_creators-no-annotation #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-apache-2.0 #contextual-embeddings #region-us 
 ### 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 ### 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/URL",
"license": "mit"
},
{
"filepath": "0rpc/zerorpc-python/zerorpc/URL",
"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



Dataset Creation
----------------


The original dataset is at URL ### 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? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


Apache License 2.0


@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.
passage: TAGS
#task_categories-other #annotations_creators-no-annotation #language_creators-machine-generated #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-original #language-English #license-apache-2.0 #contextual-embeddings #region-us 
### 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### 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/URL",
"license": "mit"
},
{
"filepath": "0rpc/zerorpc-python/zerorpc/URL",
"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



Dataset Creation
----------------


The original dataset is at URL### 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?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------### Social Impact of Dataset### Discussion of Biases### Other Known Limitations


Additional Information
----------------------### Dataset Curators