metadata

license: apache-2.0
task_categories:
  - text-generation
size_categories:
  - 10M<n<100M

Dataset Card for Python-Text2Code

Repository: https://github.com/huawei-noah/noah-research/tree/master/NLP/text2code_mrpt
Paper [optional]: https://aclanthology.org/2024.eacl-long.72.pdf
Point of Contact: Fenia Christopoulou

Dataset Description

The data were crawled from existing, public repositories from GitHub before May 2021. Duplicate files based on the rowKey of each file’s MD5 were removed and files that met the following criteria were kept: (a) the file size is under 1MB; (b) the code is Python3 compatible, using Abstract Syntactic Tree (AST) parsing; (c) there are fewer than 100 characters per line on average; (d) and there are fewer than 1,000 characters in any single line.

We then applied AST parsing (via Tree-sitter) on the remaining Python files to extract valid functions and their corresponding docstrings. Docstrings were used a "problem descriptions" and were separated from the code. Functions without a docstring were discarded. We then replaced new lines, indentation and dedentation with <NEW_LINE>, <INDENT> and <DEDENT>, respectively, to normalise spaces, which effectively reduced the length of the sequences. Finally, kept instances with a maximum length of 1024 tokens (docstring+code).

The final dataset contains 23,526,586 text-to-code pairs in Python.

Data Fields

Each instance contains 3 fields:

id: Unique ID of each pair
code: The python code
docstring: The docstring/problem description

Data Splits

There is a single data split in the dataset. We randomly sampled 0.1% of the dataset to serve as validation set.

Citation

BibTeX:

@inproceedings{christopoulou-etal-2024-text,
    title = "Text-to-Code Generation with Modality-relative Pre-training",
    author = "Christopoulou, Fenia  and
      Zhang, Guchun  and
      Lampouras, Gerasimos",
    editor = "Graham, Yvette  and
      Purver, Matthew",
    booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2024",
    address = "St. Julian{'}s, Malta",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.eacl-long.72",
    pages = "1194--1208"
}


## Dataset Card Authors [optional]

Fenia Christopoulou