File size: 1,856 Bytes
d46eb19 bbc8ed4 d46eb19 d145edd bbc8ed4 9ee5545 bbc8ed4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
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:
1. We extract the list of repositories from the "clean" subset of ManyTypes4Py,
which are the repositories that type-check with *mypy*.
2. We attempt to download all repositories, but only succeed in fetching
4,663 (out of ~5.2K).
3. 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`.
[ManyTypes4Py paper]: https://arxiv.org/abs/2104.04706
[The artifact]: https://zenodo.org/records/4719447 |