configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: code
dtype: string
- name: code_codestyle
dtype: int64
- name: style_context
dtype: string
- name: style_context_codestyle
dtype: int64
- name: label
dtype: int64
splits:
- name: train
num_bytes: 3604934957
num_examples: 308000
- name: test
num_bytes: 645620388
num_examples: 56400
download_size: 671035436
dataset_size: 4250555345
license: mit
tags:
- python
- code-style
- random
size_categories:
- 100K<n<1M
Dataset Card for "python_codestyles-random-1k"
This dataset contains negative and positive examples with python code of compliance with a code style. A positive
example represents compliance with the code style (label is 1). Each example is composed of two components, the first
component consists of a code that either conforms to the code style or violates it and the second component
corresponding to an example code that already conforms to a code style. In total, the dataset contains 1.000 completely
different code styles. The code styles differ in at least one codestyle rule, which is called a random codestyle
dataset variant. The dataset consists of a training and test group, with none of the code styles overlapping between
groups. In addition, both groups contain completely different underlying codes.
The examples contain source code from the following repositories:
| repository | tag or commit |
|---|---|
| TheAlgorithms/Python | f614ed72170011d2d439f7901e1c8daa7deac8c4 |
| huggingface/transformers | v4.31.0 |
| huggingface/datasets | 2.13.1 |
| huggingface/diffusers | v0.18.2 |
| huggingface/accelerate | v0.21.0 |
You can find the corresponding code styles of the examples in the file additional_data.json.
The code styles in the file are split by training and test group and the index corresponds to the class for the
columns code_codestyle and style_context_codestyle in the dataset.
There are 364.400 samples in total and 182.200 positive and 182.200 negative samples.