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-*
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.