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Datasets:
gabeorlanski
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tp3

Tasks:
Text Generation
Text2Text Generation
Translation
Modalities:
Text
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
code
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metadata
license: apache-2.0
task_categories:
  - text-generation
  - text2text-generation
  - translation
language:
  - en
tags:
  - code
pretty_name: BabelCode TP3
size_categories:
  - 1K<n<10K

Dataset Card for Translating Python Programming Puzzles (TP3)

Dataset Description

How To Use This Dataset

To quickly evaluate TP3 predictions, save the qid and language keys along with the postprocessed prediction code in a JSON lines file. Then follow the install instructions for BabelCode, and you can evaluate your predictions.

Dataset Summary

The Translating Python Programming Puzzles (TP3) dataset is created from the verification functions in the Python Programming Puzzles dataset (Schuster et al., 2021) to create this dataset. These functions are hand-crafted by the authors and are used to check if an answer satisfies the constraints of the puzzle. These puzzles range in difficulty from basic character checking to competitive programming problems.

Supported Tasks and Leaderboards

Languages

BC-TP3 supports:

  • C++
  • C#
  • Dart
  • Go
  • Haskell
  • Java
  • Javascript
  • Julia
  • Kotlin
  • Lua
  • PHP
  • R
  • Rust
  • Scala
  • TypeScript

Dataset Structure 

>>> from datasets import load_dataset
>>> load_dataset("gabeorlanski/tp3")
DatasetDict({
    test: Dataset({
        features: ['qid', 'title', 'language', 'text', 'signature_with_docstring', 'signature', 'arguments', 'entry_fn_name', 'entry_cls_name', 'test_code', 'source'],
        num_rows: 5920
    })
})

Data Fields

  • qid: The question ID used for running tests.
  • title: The title of the question.
  • language: The programming language of the example.
  • text: The description of the problem.
  • signature: The signature for the problem.
  • signature_with_docstring: The signature with the adequately formatted docstring for the given problem.
  • arguments: The arguments of the problem.
  • entry_fn_name: The function's name to use an entry point.
  • entry_cls_name: The class name to use an entry point.
  • test_code: The raw testing script used in the language. If you want to use this, replace PLACEHOLDER_FN_NAME (and PLACEHOLDER_CLS_NAME if needed) with the corresponding entry points. Next, replace PLACEHOLDER_CODE_BODY with the postprocessed prediction.
  • source: The source solution in Python.

Dataset Creation

See section 2 and section 4.4 of the BabelCode Paper to learn more about how the datasets are translated.

For information on how the original P3 dataset was collected, please see Programming Puzzles paper.

Dataset Curators

Google Research

Licensing Information

CC-BY-4.0

Citation Information 

@article{orlanski2023measuring,
  title={Measuring The Impact Of Programming Language Distribution},
  author={Orlanski, Gabriel and Xiao, Kefan and Garcia, Xavier and Hui, Jeffrey and Howland, Joshua and Malmaud, Jonathan and Austin, Jacob and Singh, Rishah and Catasta, Michele},
  journal={arXiv preprint arXiv:2302.01973},
  year={2023}
}
@inproceedings{
    schuster2021programming,
    title={Programming Puzzles},
    author={Tal Schuster and Ashwin Kalyan and Alex Polozov and Adam Tauman Kalai},
    booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    year={2021},
    url={https://arxiv.org/abs/2106.05784}
}