dataset_info:
features:
- name: zip
dtype: string
- name: filename
dtype: string
- name: contents
dtype: string
- name: type_annotations
sequence: string
- name: type_annotation_starts
sequence: int64
- name: type_annotation_ends
sequence: int64
splits:
- name: train
num_bytes: 4206116750
num_examples: 548536
download_size: 1334224020
dataset_size: 4206116750
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: openrail
pretty_name: ManyTypes4Py Reconstruction
ManyTypes4Py-Reconstructed
This is a reconstruction of the original code from the ManyTypes4Py paper from the following paper
A. M. Mir, E. Latoškinas and G. Gousios, "ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference," IEEE/ACM International Conference on Mining Software Repositories (MSR), 2021, pp. 585-589
The artifact (v0.7) for ManyTypes4Py does not have the original Python files. Instead, each file is pre-processed into a stream of types without comments, and the contents of each repository are stored in a single JSON file. This reconstructed dataset has raw Python code.
More specifically:
We extract the list of repositories from the "clean" subset of ManyTypes4Py, which are the repositories that type-check with mypy.
We attempt to download all repositories, but only succeed in fetching 4,663 (out of ~5.2K).
We augment each file with the text of each type annotation, as well as their start and end positions (in bytes) in the code.
Internal Note
The dataset construction code is on the Discovery cluster at /work/arjunguha-research-group/arjun/projects/ManyTypesForPy_reconstruction.